Publications

Book and Thesis

1. Chi, Ed H.  A Framework for Visualizing Information. Kluwer Academic Publishers, April 2002. (Order from Amazon)

2. Chi, Ed H. A Framework for Information Visualization Spreadsheets. Ph.D. Thesis. University of Minnesota, Computer Science Department. March, 1999.

Journal Articles

1. Amy X. Zhang, Jilin Chen, Wei Chai, Jinjun Xu, Lichan Hong, Ed H. Chi. Evaluation and Refinement of Clustered Search Results with the Crowd. ACM TiiS, June 2018.  ACM

2. Alireza Sahami Shirazi, James Clawson, Yashar Hassanpour, Mohammad J. Tourian, Albrecht Schmidt, Ed H. Chi, Marko Borazio, Kristof Van Laerhoven. Already up? using mobile phones to track & share sleep behavior. Int. J. Hum.-Comput. Stud. 71(9): 878-888 (2013)

3. Ed H. Chi. Technical Perspective: Who Knows? Searching for Expertise on the Social Web. Commun. ACM 55, 4 (April 2012), p. 110.  ACM doi PDF

4. Ed H. Chi, Sean Munson, Gerhard Fischer, Sarah Vieweg, Cynthia Parr. Advancing the Design of Technology-Mediated Social Participation Systems. IEEE Computer, vol. 43, no. 11, pp. 29-35, Nov. 2010. doi

5. Brynn M. Evans, Ed H. Chi. An elaborated model of social search. Information Processing & Management. 46, 6 (November 2010), 656-678. DOI

6. Chi, Ed H. Information Seeking Can Be Social. IEEE Computer, vol. 42, no. 3, pp. 42-46, Mar. 2009, IEEE Press. doi

7. Chi, Ed H. The Social Web: Research and Opportunities. In IEEE Computer, 41(9), pp. 88-91. September 2008. IEEE CS Press. IEEE

8. Ed H. Chi, Lichan Hong, Julie Heiser, Stuart K. Card, Michelle Gumbrecht. ScentIndex and ScentHighlights: Productive Reading Techniques for Conceptually Reorganizing Subject Indexes and Highlighting Passages.  In Information Visualization Journal, Special Issue on Visual Analytics, pp. 32--47, March 2007. Palgrave.

9. Ed H. Chi. Introducing Wearable Force Sensors in Martial Arts. IEEE Pervasive Computing, Vol. 4, No. 3, pp. 47--53. July, 2005. IEEE Press.

10. Ed H. Chi, Gaetano Borriello, Guerney Hunt, Nigel Davies. Pervasive Computing in Sports Technologies: Guest Editor's Introduction. IEEE Pervasive Computing, Vol. 4, No. 3, pp. 22--25. July, 2005. IEEE Press.

11. Christopher Olston, Ed H. Chi. ScentTrails: Integrating browsing and searching on the Web. ACM Transactions on Computer-Human Interaction, Vol. 10, Part 3, pp. 177--197. Sept, 2003. ACM Press. GDrive. 

12. Ed H. Chi. Improving Web Usability Through Visualization. IEEE Internet Computing, pp. 64--71. March, 2002. IEEE Press.

13. Ed H. Chi, John T. Riedl, Elizabeth Shoop, Phillip Barry. A Novel Visualization Method for Biological Sequence Similarity Reports. Journal of Electronic Imaging: Special Issue on Visualization and Data Analysis, pp. . October, 2000. SPIE, Bellingham, WA.

14. Ed H. Chi, John Riedl, Phillip Barry, Joseph Konstan. Principles for Information Visualization Spreadsheets. IEEE Computer Graphics and Applications (Special Issue on Visualization), pp. 30--38. July/August, 1998. IEEE CS Press.

Chapters in Books

1. Serge Egelman, Ed H Chi, Steven Dow. Crowdsourcing in HCI Research. In: Ways of Knowing in HCI. Judith S. Olson and Wendy A. Kellogg (ed.), pp. 267-289, 2014. Springer, New York.

2. Daniel M Russell, Ed H Chi. Looking Back: Retrospective Study Methods for HCI. In: Ways of Knowing in HCI. Judith S. Olson and Wendy A. Kellogg (ed.), pp. 373-393, 2014. Springer, New York.

3. Chi, Ed H. Sensors and Ubiquitous Computing Technologies in Sports. In: Computers in Sport, P. Dabnichki and Arnold Baca (ed.), pp. 249--268, 2008. WIT Press, Boston, MA.

4. Chi, Ed H. Web Analysis Tools Based on InfoScent(tm): How Cognitive Modelling Explain Reader navigational Decisions. In: Writing and Digital Media, Van Waes, L., Leijten, M., & Neuwirth, C., (eds.), May 2006. Elsevier Science. (This book received the Computers and Composition Distinguished Book Award 2007.)

5. Chi, Ed H. Scent of the Web. In: Human Factors and Web Development, Julie Ratner (ed.), pp. 265--285, 2002. Hillsdale, New Jersey: Erlbaum.

Conference Papers and arXiv preprints

[link to google scholar profile]

1. Yi Su, Xiangyu Wang, Elaine Ya Le, Liang Liu, Yuening Li, Haokai Lu, Benjamin Lipshitz, Sriraj Badam, Lukasz Heldt, Shuchao Bi, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, and Minmin Chen. 2024. Long-Term Value of Exploration: Measurements, Findings and Algorithms. In Proceedings of the 17th ACM International Conference on Web Search and Data Mining (WSDM '24). Association for Computing Machinery, New York, NY, USA, 636–644. https://doi.org/10.1145/3616855.3635833 [Best Paper Award]

2. Coleman, Benjamin, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed Chi, and Derek Cheng. Unified Embedding: Battle-tested feature representations for web-scale ML systems." Advances in Neural Information Processing Systems 36 (2024).

3. Rajput, Shashank, Nikhil Mehta, Anima Singh, Raghunandan Hulikal Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong et al. "Recommender systems with generative retrieval." Advances in Neural Information Processing Systems 36 (2024).

4. Sachdeva, Noveen, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, Lichan Hong, Ed H. Chi, James Caverlee, Julian McAuley, and Derek Zhiyuan Cheng. "How to Train Data-Efficient LLMs." arXiv preprint arXiv:2402.09668 (2024).

5. Roh, Yuji, Qingyun Liu, Huan Gui, Zhe Yuan, Yujin Tang, Steven Euijong Whang, Liang Liu et al. "LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views." arXiv preprint arXiv:2402.04644 (2024).

6. Wang, Jianling, Haokai Lu, James Caverlee, Ed Chi, and Minmin Chen. "Large Language Models as Data Augmenters for Cold-Start Item Recommendation." arXiv preprint arXiv:2402.11724 (2024).

7. Zhou, Pei, Jay Pujara, Xiang Ren, Xinyun Chen, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou, Swaroop Mishra, and Huaixiu Steven Zheng. "Self-discover: Large language models self-compose reasoning structures." arXiv preprint arXiv:2402.03620 (2024).

8. Cao, Yuwei, Nikhil Mehta, Xinyang Yi, Raghunandan Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, and Maheswaran Sathiamoorthy. "Aligning Large Language Models with Recommendation Knowledge." arXiv preprint arXiv:2404.00245 (2024).

9. Wang, Jianling, Haokai Lu, James Caverlee, Ed Chi, and Minmin Chen. "Large Language Models as Data Augmenters for Cold-Start Item Recommendation." arXiv preprint arXiv:2402.11724 (2024).

10. Team, Gemini, et al. "Gemini: a family of highly capable multimodal models." arXiv preprint arXiv:2312.11805 (2023).

11. Ma, Xiao, Swaroop Mishra, Ariel Liu, Sophie Su, Jilin Chen, Chinmay Kulkarni, Heng-Tze Cheng, Quoc Le, and Ed Chi. "Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses." arXiv preprint arXiv:2312.00763 (2023).

12. Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Ed Chi, Jilin Chen, and Alex Beutel. 2023. Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 127–139, Singapore. Association for Computational Linguistics.

13. Qingyun Liu, Zhe Zhao, Liang Liu, Zhen Zhang, Junjie Shan, Yuening Li, Shuchao Bi, Lichan Hong, and Ed H. Chi. 2023. Multitask Ranking System for Immersive Feed and No More Clicks: A Case Study of Short-Form Video Recommendation. In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM '23). Association for Computing Machinery, New York, NY, USA, 4709–4716. https://doi.org/10.1145/3583780.3615489

14. Gui, Huan, Ruoxi Wang, Ke Yin, Long Jin, Maciej Kula, Taibai Xu, Lichan Hong, and Ed H. Chi. "Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems." arXiv preprint arXiv:2311.05884 (2023).

15. Tang, Jiaxi, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, and Ed H. Chi. "Improving Training Stability for Multitask Ranking Models in Recommender Systems." arXiv preprint arXiv:2302.09178 (2023). [arxiv]

16. Shi, Freda, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed Chi, Nathanael Schärli, and Denny Zhou. "Large language models can be easily distracted by irrelevant context." International Conference on Machine Learning, 31210-31227,2023. PMLR. arXiv preprint arXiv:2302.00093 (2023). [arxiv]

17. Hu, Ziniu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, and Ed H. Chi. "Improving Multi-Task Generalization via Regularizing Spurious Correlation." Advances in Neural Information Processing Systems 35 (2022): 11450-11466. [arxiv]

18. Su, Yi; Wang, Xiangyu; Le, Elaine Ya; Liu, Liang; Li, Yuening; Lu, Haokai; Lipshitz, Benjamin; Badam, Sriraj; Heldt, Lukasz; Bi, Shuchao. Value of exploration: Measurements, findings and algorithms. arXiv preprint arXiv:2305.07764, 2023.

19. Balashankar, Ananth; Wang, Xuezhi; Qin, Yao; Packer, Ben; Thain, Nithum; Chen, Jilin; Chi, Ed H; Beutel, Alex. Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals. arXiv preprint arXiv:2305.13535, 2023.

20. Christakopoulou, Konstantina; Lalama, Alberto; Adams, Cj; Qu, Iris; Amir, Yifat; Chucri, Samer; Vollucci, Pierce; Soldo, Fabio; Bseiso, Dina; Scodel, Sarah. Large language models for user interest journeys. arXiv preprint arXiv:2305.15498, 2023.

21. Ding, Kaize; Liang, Albert Jiongqian; Perozzi, Bryan; Chen, Ting; Wang, Ruoxi; Hong, Lichan; Chi, Ed H; Liu, Huan; Cheng, Derek Zhiyuan. HyperFormer: Learning expressive sparse feature representations via hypergraph transformer,Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2062-2066, 2023.

22. Li, Pan; Wang, Yuyan; Chi, Ed H; Chen, Minmin. Hierarchical Reinforcement Learning for Modeling User Novelty-Seeking Intent in Recommender Systems. arXiv preprint arXiv:2306.01476, 2023.

23. Jianling Wang, Haokai Lu, Sai Zhang, Bart Locanthi, Haoting Wang, Dylan Greaves, Benjamin Lipshitz, Sriraj Badam, Ed H. Chi, Cristos J. Goodrow, Su-Lin Wu, Lexi Baugher, and Minmin Chen. 2023. Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '23). Association for Computing Machinery, New York, NY, USA, 5082–5091. https://doi.org/10.1145/3580305.3599826 [ACM]

24. Pan Li; Wang, Yuyan; Chi, Ed H; Chen, Minmin. Prompt tuning large language models on personalized aspect extraction for recommendations. arXiv preprint arXiv:2306.01475, 2023.

25. Singh, Anima; Vu, Trung; Keshavan, Raghunandan; Mehta, Nikhil; Yi, Xinyang; Hong, Lichan; Heldt, Lukasz; Wei, Li; Chi, Ed; Sathiamoorthy, Maheswaran. Better Generalization with Semantic IDs: A case study in Ranking for Recommendations,arXiv preprint arXiv:2306.08121, 2023.

26. Yi, Xinyang; Wang, Shao-Chuan; He, Ruining; Chandrasekaran, Hariharan; Wu, Charles; Heldt, Lukasz; Hong, Lichan; Chen, Minmin; Chi, Ed H. Online Matching: A Real-time Bandit System for Large-scale Recommendations,Proceedings of the 17th ACM Conference on Recommender Systems, 403-414, 2023.

27. Yi, Xinyang; Wang, Shao-Chuan; He, Ruining; Chandrasekaran, Hariharan; Wu, Charles; Heldt, Lukasz; Hong, Lichan; Chen, Minmin; Chi, Ed H. Online Matching: A Real-time Bandit System for Large-scale Recommendations,Proceedings of the 17th ACM Conference on Recommender Systems, 403-414, 2023.

28. Mehta, Nikhil; Singh, Anima; Yi, Xinyang; Jain, Sagar; Hong, Lichan; Chi, Ed H. Density Weighting for Multi-Interest Personalized Recommendation,arXiv preprint arXiv:2308.01563, 2023.

29. Cheng, Derek; Patel, Dhaval; Pang, Linsey; Mehta, Sameep; Xie, Kexin; Chi, Ed H; Liu, Wei; Chawla, Nitesh; Bailey, James. Foundations and Applications in Large-scale AI Models: Pre-training, Fine-tuning, and Prompt-based Learning. Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 5853-5854,2023.

30. Cheng, Derek Zhiyuan; Wang, Ruoxi; Kang, Wang-Cheng; Coleman, Benjamin; Zhang, Yin; Ni, Jianmo; Valverde, Jonathan; Hong, Lichan; Chi, Ed. Efficient Data Representation Learning in Google-scale Systems,Proceedings of the 17th ACM Conference on Recommender Systems, 267-271, 2023.

31. Zheng, Huaixiu Steven; Mishra, Swaroop; Chen, Xinyun; Cheng, Heng-Tze; Chi, Ed H; Le, Quoc V; Zhou, Denny. Take a step back: Evoking reasoning via abstraction in large language models. arXiv preprint arXiv:2310.06117, 2023.

32. Yasunaga, Michihiro; Chen, Xinyun; Li, Yujia; Pasupat, Panupong; Leskovec, Jure; Liang, Percy; Chi, Ed H; Zhou, Denny. Large language models as analogical reasoners, arXiv preprint arXiv:2310.01714, 2023.

33. Zhao, Zhe; Liu, Qingyun; Gui, Huan; An, Bang; Hong, Lichan; Chi, Ed H. Talking Models: Distill Pre-trained Knowledge to Downstream Models via Interactive Communication, arXiv preprint arXiv:2310.03188, 2023.

34. Zheng, Huaixiu Steven; Mishra, Swaroop; Chen, Xinyun; Cheng, Heng-Tze; Chi, Ed H; Le, Quoc V; Zhou, Denny. Step-Back Prompting Enables Reasoning Via Abstraction in Large Language Models. The Twelfth International Conference on Learning Representations, 2023.

35. Chang, Bo, Alexandros Karatzoglou, Yuyan Wang, Can Xu, Ed H. Chi, and Minmin Chen. (2022). Latent User Intent Modeling for Sequential Recommenders. Companion Proceedings of the ACM Web Conference 2023.  pp. 427-431,2023. arXiv preprint arXiv:2211.09832. [arxiv]

36. Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Alex Castro-Ros, Marie Pellat, Kevin Robinson, Dasha Valter, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Zhao, Yanping Huang, Andrew Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei. (2022). Scaling instruction-finetuned language models. arXiv preprint arXiv:2210.11416. [arxiv]

37. Suzgun, Mirac, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery et al. Challenging BIG-Bench tasks and whether chain-of-thought can solve them. arXiv preprint arXiv:2210.09261 (2022). [arxiv]

38. Flavien Prost, Ben Packer, Jilin Chen, Li Wei, Pierre Kremp, Nicholas Blumm, Susan Wang, Tulsee Doshi, Tonia Osadebe, Lukasz Heldt, Ed H. Chi, Alex Beutel. Simpson's Paradox in Recommender Fairness: Reconciling differences between per-user and aggregated evaluations. arXiv preprint arXiv:2210.07755 (2022). [arxiv]

39. Konstantina Christakopoulou, Can Xu, Sai Zhang, Sriraj Badam, Trevor Potter, Daniel Li, Hao Wan, Xinyang Yi, Ya Le, Chris Berg, Eric Bencomo Dixon, Ed H. Chi, Minmin Chen. Reward Shaping for User Satisfaction in a REINFORCE Recommender. arXiv preprint arXiv:2209.15166 (2022). [arxiv]

40. Yuyan Wang, Mohit Sharma, Can Xu, Sriraj Badam, Qian Sun, Lee Richardson, Lisa Chung, Ed H. Chi, and Minmin Chen. 2022. Surrogate for Long-Term User Experience in Recommender Systems. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD '22). Association for Computing Machinery, New York, NY, USA, 4100–4109. https://doi.org/10.1145/3534678.3539073

41. Wei, Jason, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V. Le, and Denny Zhou. Chain-of-thought prompting elicits reasoning in large language models. Advances in neural information processing systems 35 (2022): 24824-24837. [NeurIPS]

42. Wang, Xuezhi, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, and Denny Zhou. Rationale-augmented ensembles in language models. arXiv preprint arXiv:2207.00747 (2022).

43. Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus. 2022. Emergent Abilities of Large Language Models. arXiv preprint arXiv:2206.07682.

44. Zhou, Denny, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, and Ed Chi. Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. arXiv preprint arXiv:2205.10625 (2022).

45. Wen, Hongyi, Xinyang Yi, Tiansheng Yao, Jiaxi Tang, Lichan Hong, and Ed H. Chi. "Distributionally-robust Recommendations for Improving Worst-case User Experience." In Proceedings of the ACM Web Conference 2022, pp. 3606-3610. 2022. (Web4Good Special Track)

46. Yuyan Wang, Zhe Zhao, Bo Dai, Christopher Fifty, Dong Lin, Lichan Hong, Li Wei, and Ed H. Chi. 2022. Can Small Heads Help? Understanding and Improving Multi-Task Generalization. In Proceedings of the ACM Web Conference 2022 (WWW '22). Association for Computing Machinery, New York, NY, USA, 3009–3019. https://doi.org/10.1145/3485447.3512021

47. Jianling Wang, Elaine Le, Bo Chang, Yuyan Wang, Ed Chi, Minmin Chen. Learning to Augment for Casual User Recommendation.  In Proceedings of the ACM Web Conference 2022, pp. 2183-2194. 2022. [ACM]

48. Wang, Xuezhi, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi,  Denny Zhou. Self-consistency improves chain of thought reasoning in language models. arXiv preprint arXiv:2203.11171 (2022).

49. Yun He, Steven Zheng, Yi Tay, Jai Gupta, Yu Du, Vamsi Aribandi, Zhe Zhao, Yaguang Li, Zhao Chen, Donald Metzler, Heng-Tze Cheng, Ed H. Chi. HyperPrompt: Prompt-based Task-Conditioning of Transformers. Proceedings of the 39th International Conference on Machine Learning, PMLR 162:8678-8690, 2022.

50. Furkan Kocayusufoglu, Tao Wu, Anima Singh, Georgios Roumpos, Heng-Tze Cheng, Sagar Jain, Ed Chi, and Ambuj Singh. 2022. Multi-Resolution Attention for Personalized Item Search. In Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining (WSDM '22). Association for Computing Machinery, New York, NY, USA, 508–516. https://doi.org/10.1145/3488560.3498426

51. Kiran Vodrahalli, Rakesh Shivanna, Maheswaran Sathiamoorthy, Sagar Jain, and Ed H. Chi. Nonlinear initialization methods for low-rank neural networks. arXiv preprint arXiv:2202.00834 (2022).

52. Kiran Vodrahalli, Rakesh Shivanna, Maheswaran Sathiamoorthy, Sagar Jain, Ed H. Chi. Algorithms for Efficiently Learning Low-Rank Neural Networks. arXiv preprint arXiv:2202.00834 (2022).

53. Bo Chang, Can Xu, Matthieu Lê‎, Jingchen Feng, Ya Le, Sriraj Badam, Ed Chi, Minmin Chen. Recency Dropout for Recurrent Recommender Systems. Submitted. arXiv preprint arXiv:2201.11016 (2022).

54. Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Vincent Zhao, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Pranesh Srinivasan, Laichee Man, Kathleen Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Aguera-Arcas, Claire Cui, Marian Croak, Ed Chi, Quoc Le. (2022). LaMDA: Language Models for Dialog Applications. arXiv preprint arXiv:2201.08239.

55. Nikhil Mehta, Anima Singh, Xinyang Yi, Sagar Jain, Lichan Hong, Ed Chi. Density Weighting for Multi-interest Personalized Retrieval. Submitted 2022.

56. Qin, Yao, Xuezhi Wang, Alex Beutel, and Ed Chi. Improving calibration through the relationship with adversarial robustness. Advances in Neural Information Processing Systems 34 (2021).

57. Ananth Balashankar, Xuezhi Wang, Ben Packer, Nithum Thain, Ed Chi, Alex Beutel. Can We Improve Model Robustness through Secondary Attribute Counterfactuals? Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021. [ACL]

58. Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel. What are effective labels for augmented data? Improving robustness with AutoLabel.  ICML workshop on Uncertainty and Robustness in Deep Learning, 2021. [OpenReview] [arxiv]

59. Qin, Yao; Wang, Xuezhi; Lakshminarayanan, Balaji; Chi, Ed H; Beutel, Alex. What are effective labels for augmented data? improving calibration and robustness with autolabel. IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 365-376,2023. IEEE.

60. Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix Yu, Ting Chen, Aditya Menon, Lichan Hong, Ed H Chi, Steve Tjoa, Jieqi Kang, Evan Ettinger. Self-supervised Learning for Large-scale Item Recommendations. Proceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM), 2021. [ACM]

61. Minmin Chen, Yuyan Wang, Can Xu, Ya Le, Mohit Sharma, Lee Richardson, Su-Lin Wu, Ed Chi. Values of User Exploration in Recommender Systems.  Fifteenth ACM Conference on Recommender Systems, RecSys 2021. [ACM]

62. Konstantina Christakopoulou, Can Xu, Sai Zhang, Sriraj Badam, Trevor Potter, Daniel Li, Hao Wan, Xinyang Yi, Ya Le, Chris Berg, Eric Bencomo Dixon, Ed H. Chi, Minmin Chen.  Reward Shaping for User Satisfaction in a REINFORCE Recommender.  RL for Real Life workshop @ ICML 2021

63. Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H Chi.  Learning to Embed Categorical Features without Embedding Tables for Recommendation.  Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining (KDD), 2021. [ACM]

64. Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H Chi. DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. arXiv preprint 2021. [arXiv:2106.03760] 

65. Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H Chi. Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. arXiv preprint. 2021. [arXiv:2106.02705]

66. Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H Chi, Jilin Chen, Alex Beutel. Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective.  arXiv preprint. 2021. [arXiv:2105.09985]

67. Minmin Chen, Bo Chang, Can Xu, Ed H Chi. User Response Models to Improve a REINFORCE Recommender System. Proceedings of the 14th ACM International Conference on Web Search and Data Mining. WSDM 2021. [ACM]

68. Ruohan Zhan, Konstantina Christakopoulou, Elaine Le, Jayden Ooi, Martin Mladenov, Alex Beutel, Craig Boutilier, Ed H. Chi, Minmin Chen. Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. TheWebConf, 2021. [ACM]

69. Yin Zhang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong and Ed H. Chi. A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. TheWebConf 2021. [arXiv:2010.15982]

70. Ruoxi Wang, Rakesh Shivanna, Derek Cheng, Sagar Jain, Dong Lin, Lichan Hong and Ed Chi. DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems. TheWebConf 2021. [arXiv:2008.13535]

71. Zhe Chen, Yuyan Wang, Dong Lin, Derek Zhiyuan Cheng, Lichan Hong, Ed H. Chi, Claire Cui. Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems. WSDM, 2021. [arXiv:2008.07032]

72. Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei. Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. AISTATS 2021. [arXiv:2006.05067]

73. Xuezhi Wang, Nithum Thain, Anu Sinha, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel. Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems. WSDM, 2021. [ArXiv abs/1911.01916]

74. Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong and Ed H. Chi. Deep Hash Embedding for Large-Vocab Categorical Feature Representations. arXiv:2010.10784. (2020)

75. Kellie Webster, Xuezhi Wang, Ian Tenney, Alex Beutel, Emily Pitler, Ellie Pavlick, Jilin Chen, Ed Chi, Slav Petrov. Measuring and reducing gendered correlations in pre-trained models.  arXiv preprint arXiv:2010.06032. 2020.

76. Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed H. Chi. CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation. EMNLP, 2020.  [Google]

77. Yuyan Wang, Zhe Zhao, Bo Dai, Christopher Fifty, Dong Lin, Lichan Hong, Ed H. Chi. Small Towers Make Big Differences. arXiv:2008.05808. 2020.

78. Yao Qin, Xuezhi Wang, Alex Beutel, Ed Chi. Improving uncertainty estimates through the relationship with adversarial robustness. 2020. arXiv:2006.16375.

79. Carole-Jean Wu, Robin Burke, Ed Chi, Joseph Konstan, Julian McAuley, Yves Raimond, Hao Zhang. Developing a Recommendation Benchmark for MLPerf Training and Inference. arxiv.org/abs/2003.07336, 2020. (mentioned in MLPerf Press Release.) 

80. Konstantina Christakopoulou, Madeleine Traverse, Trevor Potter, Emma Marriott, Daniel Li, Chris Haulk, Ed H. Chi, Minmin Chen. Deconfounding User Satisfaction Estimation from Response Rate Bias. Proceedings of the 14th ACM Conference on Recommender Systems (2020). [ACM]

81. Sungryull Sohn, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed Chi, Craig Boutilier. BRPO: Batch Residual Policy Optimization. Proceedings of the Twenty-ninth International Joint Conference on Artificial Intelligence (IJCAI-20), Yokohama, Japan (2020), pp. 2824-2830.

82. Kumar, A., Du, C., Kuzmin, D., Chi, E.H., Chio, E., Cheng, H.T., Anderson, J.R., Zhang, L., Jindal, N., Cao, P. and Agarwal, R. Zero-Shot Transfer Learning for Query-Item Cold Start in Search Retrieval and Recommendations. CIKM 2020.

83. Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix Yu, Ting Chen, Aditya Menon, Lichan Hong, Ed H Chi, Steve Tjoa, Evan Ettinger. Self-supervised Learning for Deep Models in Recommendations.  BayLearn 2020. arXiv:2007.12865.

84. Hussam Abu-Libdeh, Deniz Altinbuken, Alex Beutel, Ed H. Chi, Lyric Doshi, Tim Kraska, Xiaozhou, Li, Andy Ly, Christopher Olston. Learned Indexes for a Google-scale Disk-based Database. ML for Systems workshop at NeurIPS, 2020. [Google]

85. Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi. Fairness without Demographics through Adversarially Reweighted Learning. NeurIPS, 2020.  [Appendix and Code]

86. Ashudeep Singh, Yoni Halpern, Nithum Thain, Konstantina Christakopoulou, Ed H. Chi, Jilin Chen, Alex Beutel. Building Healthy Recommendation Sequences for Everyone: A Safe Reinforcement Learning Approach. In FAccTRec Workshop at ACM RecSyS, Sept. 2020.

87. Emily Denton, Hansa Srinivasan, Dylan Baker, Jilin Chen, Alex Beutel, Tulsee Doshi, Ed H. Chi. Learning to Diversify from Human Judgments: Research Directions and Open Challenges. Fair and Responsible AI Workshop at CHI, 2020

88. Sirui Yao, Yoni Halpern, Nithum Thain, Xuezhi Wang, Kang Lee, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel. Measuring Recommender System Effects with Simulated Users. FATES at WWW, 2020. [Video] [arxiv]

89. Jiaqi Ma, Zhe Zhao, Xinyang Yi, Ji Yang, Minmin Chen, Jiaxi Tang, Lichan Hong, Ed H. Chi. Off-policy Learning in Two-stage Recommender Systems. WWW 2020. (with oral presentation). [GDrive] [ACM]

90. Jyun-Yu Jiang, Tao Wu, Georgios Roumpos, Heng-Tze Cheng, Xinyang Yi, Ed H. Chi, Harish Ganapathy, Nitin Jindal, Pei Cao, and Wei Wang. 2020. End-to-End Deep Attentive Personalized Item Retrieval for Online Content-sharing Platforms. In Proceedings of The Web Conference 2020 (WWW ’20). ACM, New York, NY, USA, 2870–2877. DOI:https://doi.org/10.1145/3366423.3380051

91. Ji Yang, Xinyang Yi, Derek Zhiyuan Cheng, Lichan Hong, Yang Li, Simon Xiaoming Wang, Taibai Xu, and Ed H. Chi. 2020. Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations. In Companion Proceedings of the Web Conference 2020 (WWW ’20). ACM, New York, NY, USA, 441–447. [DOI]

92. Wang-Cheng Kang, Derek Zhiyuan Cheng, Ting Chen, Xinyang Yi, Dong Lin, Lichan Hong, and Ed H. Chi. 2020. Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems. In Companion Proceedings of the Web Conference 2020 (WWW ’20). ACM, New York, NY, USA, 562–566. [DOI]

93. Tang, Jiaxi, Rakesh Shivanna, Zhe Zhao, Dong Lin, Anima Singh, Ed H. Chi and Sagar Jain. Understanding and Improving Knowledge Distillation. 2020 [ArXiv abs/2002.03532]

94. Sohn, Sungryull, Yinlam Chow, Jayden Ooi, Ofir Nachum, Honglak Lee, Ed H. Chi and Craig Boutilier. BRPO: Batch Residual Policy Optimization. 2020. [ArXiv abs/2002.05522]

95. Irwan Bello, Sayali Kulkarni, Sagar Jain, Craig Boutilier, Ed Chi, Elad Eban, Xiyang Luo, Alan Mackey, Ofer Meshi. Seq2Slate: Re-ranking and Slate Optimization with RNNs. ICML 2019. [ArXiv]

96. Liu, Ge, Renji Wu, Heng-Tze Cheng, Jun-bo Wang, Jayden Ooi, Lihong Li, Ang Li, Wai Lok Sibon Li, Craig Boutilier and Ed H. Chi. Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing. In Proc. of NeurIPS 2019 Workshop on Deep RL.  2019. [ArXiv abs/2002.05229]

97. Prost, Flavien, Hai Qian, Qiuwen Chen, Ed H. Chi, Jilin Chen and Alex Beutel. Toward a better trade-off between performance and fairness with kernel-based distribution matching. ML with Guarantees workshop at NeurIPS, 2019. [ArXiv abs/1910.11779]

98. Candice Schumann, Xuezhi Wang, Alex Beutel, Jilin Chen, Hai Qian, Ed H. Chi. Transfer of Machine Learning Fairness across Domains. AI for Social Good workshop at NeurIPS, 2019.  [ArXiv]

99. Xinyang Yi, Ji Yang, Lichan Hong, Derek Zhiyuan Cheng, Lukasz Heldt, Aditee Kumthekar, Zhe Zhao, Li Wei, and Ed Chi. 2019. Sampling-bias-corrected neural modeling for large corpus item recommendations. In Proc. of the 13th ACM Conference on Recommender Systems (RecSys '19). ACM, New York, NY, USA, 269-277. DOI: https://doi.org/10.1145/3298689.3346996 [Google]

100. Zhe Zhao, Lichan Hong, Li Wei, Jilin Chen, Aniruddh Nath, Shawn Andrews, Aditee Kumthekar, Maheswaran Sathiamoorthy, Xinyang Yi, and Ed Chi. 2019. Recommending what video to watch next: a multitask ranking system. In Proc. of the 13th ACM Conference on Recommender Systems (RecSys '19). ACM, New York, NY, USA, 43-51. DOI: https://doi.org/10.1145/3298689.3346997 [Google]

101. Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow.  Fairness in Recommendation Ranking through Pairwise Comparisons. KDD 2019. [arxiv]

102. Francois Belletti, Minmin Chen, Ed H. Chi. Quantifying Long Range Dependence in Language and User Behavior to improve RNNs. KDD 2019. [arxiv]

103. Jiaxi Tang, Francois Belletti, Sagar Jain, Minmin Chen, Alex Beutel, Can Xu, Ed H. Chi. Towards Neural Mixture Recommender for Long Range Dependent User Sequences. WWW 2019. [arxiv]

104. Bo Chang, Minmin Chen, Eldad Haber, Ed H. Chi. AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks. ICLR 2019.  [openreview]

105. Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John Anderson. Efficient Training on Very Large Corpora via Gramian Estimation. ICLR 2019. [arxiv]

106. Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi. Top-K Off-Policy Correction for a REINFORCE Recommender System. ACM International Conference on Web Search and Data Mining, (WSDM), 2019. [arxiv] [ACM]

107. Jiaqi Ma, Zhe Zhao, Jilin Chen, Ang Li, Lichan Hong, Ed H. Chi. SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-task Learning. AAAI Conference on Artificial Intelligence (AAAI), Honolulu, Hawaii, 2019. [pdf]

108. Sahaj Garg, Vincent Perot, Nicole Limtiaco, Ankur Taly, Ed H. Chi, Alex Beutel. Counterfactual fairness in text classification. AIES 2019. [arxiv]

109. Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Allison Woodruff, Christine Luu, Pierre Kreitmann, Jonathon Bischof and Ed H. Chi. Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements. AIES 2019.  [arxiv]

110. Tim Kraska, Mohammad Alizadeh, Alex Beutel, Ed H. Chi, Jialin Ding, Ani Kristo, Guillaume Leclerc, Samuel Madden, Hongzi Mao, Vikram Nathan. SageDB: A Learned Database System. CIDR, 2019. [pdf]

111. Stephen Macke, Alex Beutel, Tim Kraska, Maheswaran Sathiamoorthy, Derek Zhiyuan Cheng, Ed H. Chi. Lifting the Curse of Multidimensional Data with Learned Existence Indexes. ML for Systems workshop at NeurIPS, 2018. [pdf]

112. Qian Zhao, Jilin Chen, Minmin Chen, Sagar Jain, Alex Beutel, Francois Belletti, and Ed H. Chi. 2018. Categorical-attributes-based item classification for recommender systems. In Proceedings of the 12th ACM Conference on Recommender Systems (RecSys '18). ACM, New York, NY, USA, 320-328. DOI: https://doi.org/10.1145/3240323.3240367 [ACMDL]

113. Jiaqi Ma, Zhe Zhao,  Xinyang Yi, Jilin Chen, Lichan Hong, Ed H. Chi.  Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts. In Proc. of KDD 2018. [pdf]

114. Konstantina Christakopoulou, Alex Beutel, Rui Li, Sagar Jain, Ed H. Chi.  Q&R: A Two-Stage Approach toward Interactive Recommendation. In Proc. of KDD 2018. [pdf]

115. Mark Wilhelm, Ajith Ramanathan, Alexander Bonomo, Sagar Jain, Ed H. Chi, and Jennifer Gillenwater. 2018. Practical Diversified Recommendations on YouTube with Determinantal Point Processes. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM '18). ACM, New York, NY, USA, 2165-2173. DOI: https://doi.org/10.1145/3269206.3272018 [ACMDL}

116. Francois Belletti, Alex Beutel, Sagar Jain, Ed H. Chi. Factorized Recurrent Neural Architectures for Longer Range Dependence.  AISTATS, 2018.

117. Tim Kraska, Alex Beutel, Ed H. Chi, Jeff Dean, Neoklis Polyzotis.  The Case for Learned Index Structures.  SIGMOD, June 2018.  (first published online Dec. 2017.)  [arxiv]

118. Alex Beutel, Paul Covington, Sagar Jain, Can Xu, Jia Li, Vince Gatto, Ed H. Chi.  Latent Cross: Making Use of Context in Recurrent Recommender Systems.  WSDM 2018.

119. Alex Beutel, Jilin Chen, Zhe Zhao, Ed H. Chi.  Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations.  KDD FATML Workshop, 2017.  

120. Alex Beutel, Ed H. Chi, Zhiyuan Cheng, Hubert Pham, John Anderson.  Beyond Globally Optimal: Focused Learning for Improved Recommendations.  WWW, 2017.  [Google]

121. Rong Yang, Sarvjeet Singh, Pei Cao, Ed H. Chi, Bo Fu.  Video Watch Time and Comment Sentiment: Experiences from YouTube. 2016 Fourth IEEE Workshop on Hot Topics in Web Systems and Technologies (HotWeb), 26-28.  2016. IEEE

122. Andrew Warr, Ed H. Chi, Helen Harris, Alexander Kuscher, Jenn Chen, Robert Flack, Nicholas Jitkoff.  Window Shopping: A Study of Desktop Window Switching. CHI '16 Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 2016.

123. Shuo Chang, Peng Dai, Lichan Hong, Cheng Sheng, Tianjiao Zhang, Ed H. Chi.   AppGrouper: Knowledge-based Interactive Clustering Tool for App Search Results. IUI '16 Proceedings of the 21st International Conference on Intelligent User Interfaces, 2016

124. Zhe Zhao, Zhiyuan Cheng, Lichan Hong, Ed H. Chi. Improving User Topic Interest Profiles by Behavior Factorization. In Proc. of the 24th International Conference on World Wide Web (WWW '15). Geneva, Switzerland, 1406-1416. 2015. [ACM] [WWW]

125. Shuo Chang, Peng Dai, Jilin Chen, Ed H. Chi.  Got Many Labels?: Deriving Topic Labels from Multiple Sources for Social Media Posts using Crowdsourcing and Ensemble Learning. In Proc. of the 24th International Conference on World Wide Web (WWW '15 Companion). Geneva, Switzerland, 397-406. 2015. DOI=http://dx.doi.org/10.1145/2740908.2745401  [ACM] [WWW]

126. Michael J. Brzozowski, Phil Adams, Ed H. Chi. Google+ Communities as Plazas and Topic Boards. In Proc. of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). ACM, New York, NY, USA, 3779-3788. 2015. DOI=http://dx.doi.org/10.1145/2702123.2702600 [ACM] [Google]

127. Peng Dai, Jeffrey M. Rzeszotarski, Praveen Paritosh, Ed H. Chi.  And Now for Something Completely Different: Improving Crowdsourcing Workflows with Micro-Diversions. In Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing (CSCW '15). ACM, New York, NY, USA, 628-638. 2015. DOI=http://dx.doi.org/10.1145/2675133.2675260 [ACM]

128. Chenhao Tan, Ed H. Chi, David Huffaker, Gueorgi Kossinets, Alexander J. Smola. Instant Foodie: Predicting Expert Ratings From Grassroots. In Proc. of ACM Conference of Information and Knowledge Management (CIKM 2013), Oct. 27--Nov. 1, 2013, San Francisco, USA. [ACM] [Google]

129. Jennifer Fernquist, Ed H. Chi. Perception and Understanding of Social Annotations in Web Search. In Proc. of WWW2013. pp. 403--412. Rio de Janeiro, Brazil. May, 2013. WWW2013 [pdf]

130. Chinmay Kulkarni, Ed H. Chi. All the news that's fit to read: a study of social annotations for news reading. In Proc. of the SIGCHI Conference on Human Factors in Computing Systems (ACM CHI2013). pp. 2407--2416. Paris, France. May, 2013. [ACM] [pdf]

131. Andrew Warr, Ed H. Chi. Swipe vs. scroll: web page switching on mobile browsers. In Proc. of the SIGCHI Conference on Human Factors in Computing Systems (ACM CHI2013). pp. 2171--2174. Paris, France. May, 2013. RepliCHI Award. [ACM] [GDrive]

132. Sanjay Kairam, Michael J. Brzozowski, David Huffaker, Ed H. Chi. Talking in Circles: Selective Sharing in Google+. In Proc. CHI2012. May 5, 2012. Austin, TX, USA. [Google]

133. Aditi Muralidharan, Zoltan Gyongyi, Ed H. Chi. Social Annotations in Web Search. In Proc. CHI2012. May 5, 2012. Austin, TX, USA. [ACM] [Google]

134. Sharoda A. Paul, Lichan Hong, Ed H. Chi. Who is authoritative? Understanding reputation mechanisms in Quora. In Proc. of Collective Intelligence 2012. April, 2012. Cambridge, MA, USA. [arxiv]

135. Nelson, L.; Convertino, G.; Nairn, R.; Chi, E. H. Studying the Adoption of Mail2Tag: an Enterprise2.0 Tool for Sharing. In Proc. of the European Conference on Computer-Supported Cooperative Work 2011, 24-28 September.

136. S. Paul, L. Hong, and E. Chi. Is Twitter a Good Place for Asking Questions? A Characterization Study. In Proc. of 2011 International AAAI Conference on Weblogs and Social Media (ICWSM'11). [AAAI]

137. Lichan Hong, Gregorio. Convertino, and Ed H. Chi. Language Matters in Twitter: A Large Scale Study. In Proc. of 2011 International AAAI Conference on Weblogs and Social Media (ICWSM'11). [AAAI]

138. Hanrahan, B.; Bouchard G.; Convertino, G.; Weksteen T.; Kong, N.; Archanbeau C.; Chi, E. H. Mail2Wiki: low-cost sharing and early curation from email to wikis. In Proc. of the 5th International Conference on Communities & Technologies (C&T 2011); 2011 June, Brisbane, Australia.

139. Jilin Chen, Rowan Nairn, Ed H. Chi. Speak Little and Well: Recommending Conversations in Online Social Streams. In Proc. of CHI2011. Vancouver, Canada. [pdf]

140. Brent Hecht, Lichan Hong, Bongwon Suh, Ed H. Chi. Tweets from Justin Bieber's Heart: the Dynamics of the "Location" Field in User Profiles. In Proc. of CHI2011. Vancouver, Canada. [ACM] [pdf]

141. Nelson, L.; Nairn, R.; Chi, E. H.; Convertino, G. Mail2Tag: augmenting email for sharing with implicit tag-based categorization. In Proc. of 2011 International Conference on Collaboration Technologies and Systems (CTS), 2011. pp. 23-30. May 23-27; Philadelphia, PA. (Outstanding Paper Runner Up Award)  [pdf]

142. Kong, N.; Hanrahan, B.; Weksteen, T.; Convertino, G.; Chi, E. H. VisualWikiCurator: Human and machine intelligence for organizing wiki content. In Proc. of Intelligent User Interfaces (IUI) 2011. Feb., 2011. Palo Alto, CA. [pdf]

143. Nicholas Kong, Gregorio Convertino, Benjamin Hanrahan, Ed Chi. VisualWikiCurator: a corporate Wiki plugin. CHI EA '11 CHI '11 Extended Abstracts on Human Factors in Computing Systems, 2011. [ACM]

144. Michael S. Bernstein, Bongwon Suh, Lichan Hong, Jilin Chen, Sanjay Kairam, Ed H. Chi. Eddi: Interactive Topic-based Browsing of Social Status Streams. In Proc. of ACM User Interface Software and Technology (UIST) conference, Oct. 2010. New York, NY. [pdf] [Slides]

145. Bongwon Suh, Lichan Hong, Peter Pirolli, and Ed H. Chi. Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network. In Proc. of IEEE SocialCom 2010, Aug 20-22, 2010. Minneapolis, MN. [pdf]

146. Terrell Russell, Bongwon Suh, Ed H. Chi. A Comparison of Generated Wikipedia Profiles Using Social Labeling and Automatic Keyword Extraction. In Proc. of 4th Int'l AAAI Conference on Weblogs and Social Media (ICWSM 2010). May 23, 2010. Washington, DC.  [AAAI]

147. Convertino, G.; Kairam, S.; Hong, L.; Suh, B.; Chi, E. H. Designing a Cross-Channel Information Management Tool for Workers in Enterprise Task Forces.In Proc. of Advanced Visual Interfaces 2010 (AVI2010). May 26, 2010. [pdf]

148. Ed H. Chi, Todd Mytkowicz. Understanding the Efficiency of Social Tagging Systems using Information Theory. In Proc. of the Second International Conference on Weblogs and Social Media (ICWSM2008). Seattle, WA. [pdf]

149. Lichan Hong, Gregorio. Convertino, Bongwon Suh, Ed H. Chi, Sanjay Kairam. FeedWinnower: layering structures over collections of information streams. In Proceedings of the 28th International Conference on Human Factors in Computing Systems (CHI2010). April, 2010. Atlanta, GA. [pdf]

150. Jilin Chen, Rowan Nairn, Les Nelson, Michael Bernstein, Ed H. Chi. Short and Tweet: Experiments on Recommending Content from Information Streams. In Proceedings of the 28th International Conference on Human Factors in Computing Systems (CHI2010). April, 2010. Atlanta, GA. [slides]

151. Ed H. Chi.  Augmented social cognition: using social web technology to enhance the ability of groups to remember, think, and reason. In Proceedings of the 35th SIGMOD international Conference on Management of Data (Providence, Rhode Island, USA, June 29 - July 02, 2009). SIGMOD '09. ACM, New York, NY, 973-984.  (Invited Paper) [ACM]

152. Bongwon Suh, Gregorio Convertino, Ed H. Chi, Peter Pirolli. The Singularity is Not Near: Slowing Growth of Wikipedia. In Proc. of WikiSym 2009. Oct, 2009. Florida, USA. (34% acceptace rate)

153. Ed H. Chi. A position paper on 'Living Laboratories': rethinking ecological designs and experimentation in human-computer interaction. HCI International 2009; 2009 July 19-24; San Diego, CA. [Springer] [Slides]

154. Les Nelson, Gregorio Convertino, Peter Pirolli, Lichan Hong, Ed H. Chi. Impact on Performance and Process by a Social Annotation System: A Social Reading Experiment. HCI International 2009; 2009 July 19-24; San Diego, CA. [Springer]

155. Convertino, G. ; Hong, L. ; Nelson, L. ; Pirolli, P. L. ; Chi, E. H. Activity awareness & social sensemaking 2.0: design of a task force workspace. HCI International 2009 - Thematic Area: Augmented Cognition; 2009 July 19-24; San Diego, CA. [Springer]

156. Nicolas Ducheneaut, Qingfeng Huang, Kurt Partridge, Bob Price, Mike Roberts, Ed H. Chi, Victoria Bellotti, Bo Begole. Collaborative Filtering is not Enough? Experiments with a Mixed-Model Recommender for Leisure Activities. In Proc. of International Conference on User Modeling, Adaptation, and Personalization (UMAP 2009). pp. 295--306. Trento, Italy. June 2009.  [Springer]

157. Kammerer, Y., Nairn, R., Pirolli, P., and Chi, E. H. 2009. Signpost from the masses: learning effects in an exploratory social tag search browser. In Proceedings of the 27th International Conference on Human Factors in Computing Systems (Boston, MA, USA, April 04 - 09, 2009). CHI '09. ACM, New York, NY, 625-634.  [ACM] [Slides] [DemoVideo] (24% acceptance rate)

158. Kittur, A., Chi, E. H., and Suh, B. 2009. What's in Wikipedia?: Mapping Topics and Conflict using Socially Annotated Category Structure. In Proceedings of the 27th International Conference on Human Factors in Computing Systems (Boston, MA, USA, April 04 - 09, 2009). CHI '09. ACM, New York, NY, 1509-1512. [ACM] (24% acceptance rate)

159. Nelson, L., Held, C., Pirolli, P., Hong, L., Schiano, D., and Chi, E. H. 2009. With a little help from my friends: examining the impact of social annotations in sensemaking tasks. In Proceedings of the 27th International Conference on Human Factors in Computing Systems (Boston, MA, USA, April 04 - 09, 2009). CHI '09. ACM, New York, NY, 1795-1798. [ACM] (24% acceptance rate)

160. Hong, L. and Chi, E. H. 2009. Annotate once, appear anywhere: collective foraging for snippets of interest using paragraph fingerprinting. In Proceedings of the 27th International Conference on Human Factors in Computing Systems (Boston, MA, USA, April 04 - 09, 2009). CHI '09. ACM, New York, NY, 1791-1794. [ACM] (24% acceptance rate)

161. Brynn Evans, Ed H. Chi. Towards a Model of Understanding Social Search. In Proc. of Computer-Supported Cooperative Work (CSCW), pp. 485-494. ACM Press, 2008. San Diego, CA. [ACM]

162. Aniket Kittur, Bongwon Suh, Ed H. Chi. Can You Ever Trust a Wiki? Impacting Perceived Trustworthiness in Wikipedia. In Proc. of Computer-Supported Cooperative Work (CSCW), pp. 477-480. ACM Press, 2008. San Diego, CA. Best Note Award. [ACM]

163. Ed H. Chi, Todd Mytkowicz. Understanding the Efficiency of Social Tagging Systems using Information Theory. In Proc. of ACM Conference on Hypertext 2008. pp. 81--88. ACM Press, 2008. Pittsburgh, PA. [pdf]

164. Brynn Evans, Ed H. Chi. Towards a Model of Understanding Social Search. In Proc. of the JCDL Workshop on Collaborative Information Retrieval. 2008. Pittsburgh, PA.

165. Lichan Hong, Ed H. Chi, Raluca Budiu, Peter Pirolli, and Les Nelson. SparTag.us: Low Cost Tagging System for Foraging of Web Content. In Proceedings of the Advanced Visual Interface (AVI2008), pp. 65-72. ACM Press, 2008. [Video]

166. Aniket Kittur, Ed H. Chi, Bongwon Suh. Crowdsourcing User Studies With Mechanical Turk. In Proc. of the ACM Conference on Human-factors in Computing Systems (CHI2008), pp.453-456. ACM Press, 2008. Florence, Italy. (18% acceptance rate) [ACM] [ ACM PDF] [GDrive PDF]

167. Bongwon Suh, Ed H. Chi, Aniket Kittur, Bryan A. Pendleton. Lifting the Veil: Improving Accountability and Social Transparency in Wikipedia with WikiDashboard. In Proceedings of the ACM Conference on Human-factors in Computing Systems (CHI2008), pp. 1037-1040. ACM Press, 2008. Florence, Italy.(18% acceptance rate)

168. Victoria Bellotti, Bo Begole, Ed H. Chi, Nicolas Ducheneaut, Ji Fang, Ellen Isaacs, Tracy King, Mark W. Newman, Kurt Partridge, Bob Price, Paul Rasmussen, Michael Roberts, Diane J. Schiano, Alan Walendowski. Activity-Based Serendipitous Recommendations with the Magitti Mobile Leisure Guide. In Proceedings of the ACM Conference on Human-factors in Computing Systems (CHI2008), pp. 1157-1166. ACM Press, 2008. Florence, Italy. ACM UMN

169. Ed H. Chi, Peter Pirolli, Bongwon Suh, Aniket Kittur, Bryan Pendleton, Todd Mytkowicz. Augmented Social Cognition. In Proceedings of AAAI Spring Symposium on Social Information Processing. AAAI Press, March 26 2008. Stanford Lecture

170. Bongwon Suh, Ed H. Chi, Bryan A. Pendleton, Aniket Kittur. Us vs. Them: Understanding Social Dynamics in Wikipedia with Revert Graph Visualizations.In Proc. of the IEEE 2007 Visual Analytics Science and Technology (VAST2007) Symposium, pp. 163--170. Oct. 2007. Sacramento, CA. IEEE CS Press.

171. Ed H. Chi, Michelle Gumbrecht, Lichan Hong. Visual Foraging of Highlighted Text: An Eye-tracking Study. In Proc. of HCI International Conference (HCII 2007), LNCS 4552, pp. 589--598, July 2007. Beijing, China.

172. Ed H. Chi. Peter Pirolli, Shyong K. Lam. Aspects of Augmented Social Cognition: Social Information Foraging and Social Search. In Proc. of HCI International Conference (HCII 2007), Online Communities and Social Computing. LNCS 4564, pp. 60--69, July 2007. Beijing, China.

173. Aniket Kittur, Ed H. Chi, Bryan A. Pendleton, Bongwon Suh, Todd Mytkowicz. Power of the Few vs. Wisdom of the Crowd: Wikipedia and the Rise of the Bourgeoisie. Presented at alt.CHI at ACM SIGCHI Conference 2007. April, 2007. San Jose, CA. alt.CHI

174. Aniket Kittur, Bongwon Suh, Bryan A. Pendleton, Ed H. Chi. He Says, She Says: Conflict and Coordination in Wikipedia. In Proc. of ACM Conference on Human Factors in Computing Systems (CHI2007), pp. 453--462, April 2007. ACM Press. San Jose, CA. Talk Slides

175. Ed H. Chi, Lichan Hong, Julie Heiser, Stuart K. Card. ScentIndex: Conceptually Reorganizing Subject Indexes for Reading. In Proc. of the IEEE 2006 Visual Analytics Science and Technology (VAST2006) Symposium, pp. 159--166. Oct. 2006. Baltimore, MD. IEEE CS Press. Slides

176. Eric Bier, Eddie Ishak, Ed Chi. Entity Workspace: an evidence file that aids memory, inference, and reading. In Proc. of IEEE International Conference on Intelligence and Security Informatics (ISI) 2006, pp. 466--472. May 23, 2006. San Diego, CA. Springer Link

177. Eric Bier, Eddie Ishak, Ed Chi. Entity quick click: rapid text copying based on automatic entity extraction. In Proc. of CHI 2006 Extended Abstracts on Human Factors in Computing Systems, pp. 562-567. April, 2006. ACM Press.

178. Peter Pirolli, Wai-tat Fu, Ed H. Chi, Ayman Farahat. Information scent and web navigation: Theory, models, and automated usability evaluation. In Proceedings of Human Computer Interaction International 2005. July 22-27, 2005. Las Vegas, Nevada. PARC Link

179. Lichan Hong, Ed H. Chi, Stuart K. Card. Annotating 3D Electronic Books. In Proc. of the Human Factors in Computing Systems Conference (CHI2005) Conference Companion, pp. 1463--1466. ACM Press, 2005. Portland, Oregon.

180. Ed H. Chi, Lichan Hong, Michelle Gumbrecht, Stuart K. Card. ScentHighlights: highlighting conceptually-related sentences during reading. In Proc. of the 10th International Conference on Intelligent User Interfaces, pp. 272--274. ACM Press, January 2005. San Diego, CA. UMN

181. Ed H. Chi, Jin Song, Greg Corbin.“Killer App” of Wearable Computing: Wireless Force  Sensing Body Protectors for Martial Arts. In Proc. of 17th Annual ACM Symposium on User Interface Software and Technology, pp. 277--285. ACM Press, October, 2004. Santa Fe, NM. Video Demo UIST demo GDrive

182. Stuart K. Card, Lichan Hong, Jock D. Mackinlay, Ed H. Chi. 3Book: A 3D Electronic Smart Book. In Proceedings of the Advanced Visual Interface (AVI2004), pp. 303-307. ACM Press, 2004. Gallipoli, Italy. Video UMN

183. Ed H. Chi, Lichan Hong, Julie Heiser, Stuart K. Card. eBooks with Indexes that Reorganize Conceptually. In Proc. of the Human Factors in Computing Systems Conference (CHI2004) Conference Companion, pp. 1223--1226. ACM Press, 2004. Vienna, Austria. UMN

184. Stuart K. Card, Lichan Hong, Jock D. Mackinlay, and Ed H. Chi. 3Book: A Scalable 3D Virtual Book. In Proceedings of the Human Factors in Computing Systems Conference (CHI2004) Conference Companion, pp. 1095--1098. ACM Press, 2004. Vienna, Austria. Video

185. Ed H. Chi, Adam Rosien, Gesara Supattanasiri, Amanda Williams, Christiaan Royer, Celia Chow, Erica Robles, Brinda Dalal, Julie Chen, Steve Cousins. The Bloodhound Project: Automating Discovery of Web Usability Issues using the InfoScent(tm) Simulator. In Proc. of ACM CHI 2003 Conference on Human Factors in Computing Systems, pp. 505--512. ACM Press, April 2003. Fort Lauderdale, FL. (16% acceptance rate) UMN

186. Ed H. Chi, Adam S. Rosien, Jeffrey Heer. LumberJack: Intelligent Discovery and Analysis of Web User Traffic Composition. In Proc. ACM-SIGKDD Workshop on Web Mining for Usage Patterns and User Profiles (WebKDD 2002), pp. 1--16. Springer, July 2002. Edmonton, Canada. Springer Link

187. Ed H. Chi.  Expressiveness of the Data Flow and Data State Models in Visualization Systems. In Proc. of the Advanced Visual Interfaces Conference, pp. 375--378. ACM Press, May 2002. Trento, Italy.

188. Jeffrey Heer, Ed H. Chi. Separating the Swarm: Categorization Methods for User Access Sessions on the Web. In Proc. of ACM CHI 2002 Conference on Human Factors in Computing Systems, pp. 243--250. ACM Press, April 2002. Minneapolis, MN. (15% acceptance rate) UMN

189. Jeffrey Heer, Ed H. Chi. Mining the Structure of User Activity using Cluster Stability. In Proceedings of the Workshop on Web Analytics, Second SIAM Conference on Data Mining. April, 2002. Arlington, VA.

190. Ed H. Chi, Peter Pirolli, Kim Chen, James Pitkow. Using Information Scent to Model User Information Needs and Actions on the Web. In Proc. of ACM CHI 2001 Conference on Human Factors in Computing Systems, pp. 490--497. ACM Press, April 2001. Seattle, WA. (20% acceptance rate) UMN

191. Jeffrey Heer, Ed H. Chi. Identification of Web User Traffic Composition using Multi-Modal Clustering and Information Scent. In Proceedings of the Workshop on Web Mining, SIAM Conference on Data Mining, pp. 51--58. April 7th, 2001. Chicago, IL.

192. Ed H. Chi. A Taxonomy of Visualization Techniques using the Data State Reference Model. In Proceedings of the Symposium on Information Visualization (InfoVis '00), pp. 69--75. IEEE Press, 2000. Salt Lake City, Utah.

193. Ed H. Chi, Peter Pirolli, James Pitkow. The Scent of a Site: A System for Analyzing and Predicting Information Scent, Usage, and Usability of a Web Site. In Proc. of ACM CHI 2000 Conference on Human Factors in Computing Systems, pp. 161--168, 581, 582. ACM Press, 2000. Amsterdam, Netherlands. Figures (21% acceptance rate)

194. Allison Woodruff, Rich Gossweiler, James Pitkow, Ed H. Chi, Stuart K. Card. Enhancing a Digital Book with a Reading Recommender. In Proc. of ACM CHI 2000 Conference on Human Factors in Computing Systems, pp. 153--160, 580. ACM Press, 2000. Amsterdam, Netherlands. (21% acceptance rate) UMN

195. Ed H. Chi, John T. Riedl. Case Study: Resource Steering in a Visualization System. In Proceedings of the Joint Eurographics - IEEE TCVG Symposium on Visualization (VisSym '00), pp. 269--277. Springer-Verlag, May, 2000. Amsterdam, Netherlands.

196. Ed H. Chi, Stuart K. Card. Sensemaking of Evolving Web Sites using Visualization Spreadsheets. In Proceedings of the Symposium on Information Visualization (InfoVis '99), pp. 18--25, 142. IEEE Press, 1999. San Francisco, CA.  Figures

197. Ed H. Chi, John T. Riedl. An Operator Interaction Framework for Visualization Systems. In Proceedings of the Symposium on Information Visualization (InfoVis '98), pp. 63--70. IEEE Press, 1998. Research Triangle Park, North Carolina.  (Awarded 20-year Test of Time in 2018.)

198. Ed H. Chi, James Pitkow, Jock Mackinlay, Peter Pirolli, Rich Gossweiler, Stuart K. Card. Visualizing the Evolution of Web Ecologies. In Proc. of ACM CHI 98 Conference on Human Factors in Computing Systems, pp. 400--407, 644--645. ACM Press, 1998. Los Angeles, California. (23% acceptance rate)  Figures

199. Ed H. Chi, Phillip Barry, John Riedl, Joseph Konstan. A Spreadsheet Approach to Information Visualization. In Proc. of the Symposium on Information Visualization (InfoVis '97), pp. 17--24,116. IEEE CS, 1997. Phoenix, Arizona. Figures

200. Ed Huai-hsin Chi, Joseph Konstan, Phillip Barry, John Riedl. A Spreadsheet Approach to Information Visualization.  In Proc. of ACM Symposium on User Interface Software and Technology (UIST '97), pp. 79--80. ACM Press, 1997. Banff, Canada. (Reviewed Demonstration)

201. Ed H. Chi, John Riedl, Elizabeth Shoop, John V. Carlis, Ernest Retzel, and Phillip Barry. Flexible Information Visualization of Multivariate Data from Biological Sequence Similarity Searches. In Proc. of IEEE Visualization '96, pp. 133--140, 477. IEEE CS Press, 1996.

202. Ed H. Chi, Phillip Barry, Elizabeth Shoop, John Carlis, Ernest Retzel, and John Riedl. Visualization of Biological Sequence Similarity Search Results. In Proc. of IEEE Visualization '95, pp. 44--51. IEEE CS Press, 1995.  Slides

203. Elizabeth Shoop, Ed Chi, John Carlis, Paul Bieganski, John Riedl, Neal Dalton, Tom Newman, and Ernest Retzel. Implementation and Testing of an Automated EST Processing and Analysis System. In Lawrence Hunter and Bruce Shriver, editors. Proceedings of the 28th Annual Hawaii International Conference on System Sciences, pp. 52--61. Vol. 5. IEEE CS Press, January, 1995.

204. Kristi Swope, Paul Bieganski, Ed Chi, Elizabeth Shoop, O. Holt, John Carlis, John Riedl, Tom Newman, and Ernest Retzel. Does ELVIS (GA[AG]CT[ACGT]GT[ACGT]AT[ACT]TC[ACGT]TA[AG]) Live in Minnesota's Arabidopsis Databank? Weed's World: The International Electronic Arabidopsis Newsletter. 2(iii):11-18. December, 1995.

205. Kristi Swope, Tom Newman, Elizabeth Shoop, Paul Bieganski, Ed Chi, O.Holt, John Carlis, John Riedl, and Ernest Retzel. Everything you wanted to know about the University of Minnesota's analysis of Arabidopsis ESTs but were afraid to ask. Weed's World: The International Electronic Arabidopsis Newsletter. 2(ii):21-26. August, 1995.

Conference Abstracts, Posters, and Workshops (incomplete, and some lightly refereed)

1. Wilson, M. L. L., Resnick, P., Coyle, D., & Chi, E. H. (2013). RepliCHI: the workshop. CHI2013 Extended Abstracts on Human Factors in Computing Systems (pp. 3159--3162).

2. Paul, S.A., Hong, L., and Chi, E.H. (2011). What is a Question? Crowdsourcing Tweet Categorization. In Workshop on Crowdsourcing and Human Computation at the Conference on Human Factors in Computing Systems (CHI 2011).

3. Judd Antin, Ed H. Chi, James Howison, Sharoda Paul, Aaron Shaw, and Jude Yew. 2011. Apples to oranges? comparing across studies of open collaboration/peer production. In Proceedings of the 7th International Symposium on Wikis and Open Collaboration (WikiSym ’11). Association for Computing Machinery, New York, NY, USA, 227–228. DOI:https://doi.org/10.1145/2038558.2038610

4. Benjamin Hanrahan, Thiebaud Weksteen, Nicholas Kong, Gregorio Convertino, Guillaume Bouchard, Cedric Archambeau, Ed H. Chi. Mail2Wiki: Posting and Curating Wiki Content from Email. (Demo) In Proc. of Intelligent User Interfaces (IUI) 2011. Feb., 2011. Palo Alto, CA.

5. Convertino, G.; Grasso, A.; De Michelis, G.; Millen, D. R.; Chi, E. H. CIorg - collective intelligence in organizations: tools and studies. In Proc. of 16th ACM International Conference on Supporting Group Work (GROUP'10); 2010 November 7-10; Sanibel, FL. NY: ACM; 2010; 355-358.

6. Convertino, G.; Hanrahan, B.; Kong, N.; Weksteen, T.; Chi, E. H.; Bouchard, G.; Archambeau, C. Mail2Wiki: low-cost sharing and organization on wikis. Workshop on Collective Intelligence in Organizations: Tools and Studies at ACM GROUP'10; 2010 November 7; Sanibel Island FL.

7. Bernstein, M.; Kairam, S.; Suh, B.; Hong, L.; Chi, E. H. A torrent of tweets: managing information overload in online social streams. CHI 2010 Workshop on Microblogging.; 2010 April 11; Atlanta, GA.

8. Suh, B.; Hong, L.; Convertino, G.; Chi, E. H.; Bernstein, M. Sensemaking with tweeting: exploiting microblogging for knowledge workers. CHI 2010 Microblogging Workshop; 2010 April 11; Atlanta, GA.

9. Ed H. Chi, Rowan Nairn. Information Seeking with Social Signals: Anatomy of a Social Tag-based Exploratory Search Browser. In IUI2010 Workshop on Social Recommender Systems. Feb 2010, Hong Kong. Slides

10. Convertino, G.; Grasso, A.; DiMicco, J. M.; De Michelis, G.; Chi, E. H. Collective intelligence in organizations: toward a research agenda. ACM Conference on Computer-Supported Cooperative Work (CSCW 2010); 2010 February 6-10; Savannah, GA. NY: ACM; 2010; 613-614.

11. G. Convertino, T. Stricker, S. Kairam, A. Grasso, P. Pirolli, E. Chi, E. Bascaran. Learning Communities in a Large Enterprise. In TEL-CoPs'09: 3rd International Workshop on Building Technology Enhanced Learning solutions for Communities of Practice (at 4th European Conference on Technology Enhanced Learning).

12. Convertino, G., Pirolli, P., Chi, E., Vicario, T., Stricker, T.M. & Vastola, G.S. Cases of online learning communities in a large enterprise. CHI2009 Workshop on Social Mediating Technologies.

13. Nelson, L.; Pirolli, P. L.; Hong, L.; Chi, E. H.; Held, C. Examining the impact of social annotations in sensemaking tasks. CHI2009 Workshop on Sensemaking.

14. Ed H. Chi. A position paper on 'Living Laboratories': Rethinking Ecological Designs and Experimentation in Human-Computer Interaction. Presented at 2009 HCIC Workshop. Frasier, Colorado, Feb 2009. Talk Slides

15. Brynn Evans, Ed H. Chi. Towards a Model of Understanding Social Search. In CIKM workshop on Social Media Search. 2008. Napa, CA.

16. Begole, J.; Bellotti, V.; Chi, E. H.; Ducheneaut, N.; Newman, M.; Partridge, K. Mobile recommendations for leisure activities. International Workshop on Recommendation and Collaboration at IUI 2008; 2008 January 13; Canary Islands, Spain.

17. P. Pirolli and E. Chi, Lichan Hong. LATEST: A System for Active Learning about Emerging Science and Technology. Presented at 2008 HCIC Workshop. Frasier, Colorado, Jan 2008.

18. Ed H. Chi, Lawrence Lee. Web 2.0 in the Enterprise: Improving collaboration through research insights in coordination costs. KMWorld and Intranets 2007. Nov 7, 2007.

19. Peter Pirolli, Wai-tat Fu, Ed H. Chi, Ayman Farahat. Information Scent and Web Navigation: Theory, Models, and Automated Usability Evaluation. In Next Wave: NSA's Review of Emerging Technologies, vol. 15, no. 2, Spring 2006.

20. Ed H. Chi, Peter Pirolli. Social Information Foraging and Social Search. HCIC 2006, Fraser, CO. Feb, 2006.

21. Ed H. Chi. Acceptance of UbiComp Technology in Sports. UbiComp2005 conference workshop on Sports in Technology. Tokyo, Japan. Sep. 2005.

22. Ed H. Chi. Building Tools based on Sensemaking Models. CHI2005 Workshop on Sensemaking. Portland, OR. April 2005.

23. Ed H. Chi. Transient User Profiling. In Proceedings of the Workshop on User Profiling at CHI2004. 2004. Vienna, Austria.

24. Ed H. Chi. Killer App: Force Sensors in Martial Arts. HCIC 2004 Workshop, Fraser, CO. Feb, 2004.

25. Ed H. Chi. The information scent project: automating discovery of Web usability issues. CHI 2002 Workshop on Automatically Evaluating the Usability of Web Sites; 2002 April 20-25; Minneapolis; MN; USA.

26. Ed H. Chi. Scent of the Web. Institute for Mathematics and its Applications Workshop on Digital Library and Information Access, Feburary 28, 2001.

27. Colin Ware, Ed H. Chi, Rich Gossweiler. Visual Perception for Data Visualization. Tutorial at CHI 2000. In Proc. of the Human Factor in Computing Systems Conference (CHI 2000) Extended Abstract. April, 2000, Amsterdam, Netherlands.

28. Ed H. Chi. Webology and Information Scent. Internet Archive Colloquium. March 8, 2000.

29. Ed H. Chi. Web Analysis Visualization Spreadsheet. ACM Digital Library Workshop on Organizing Web Space (WOWS '99). pp. 24--31. August, 1999.

30. Ed H. Chi. Web Analysis Visualization Spreadsheet. Workshop on Organizing Web Site Information, CHI 1999.

31. Ed H. Chi. Spreadsheet for Information Visualizatoin. Basic Research Symposium, CHI 1998.

32. Ernest F. Retzel, Kristi L. Swope, Elizabeth Shoop, Olaf Holt, John V. Carlis, Ed Chi, Paul Bieganski, John Riedl and Tom Newman. [1996]. EST Informatics. Plant Genome IV. San Diego.

33. Kristi L. Swope, Paul Bieganski, Elizabeth Shoop, Olaf Holt, John V. Carlis, Ed Chi, Phillip Barry, John Riedl, Tom Newman and Ernest F. Retzel. [1996]. Plant Molecular Informatics Tools at the University of Minnesota. Plant Genome IV. San Diego.

34. T. Newman, E.F. Retzel, E. Shoop, E. Chi and C. Somerville [1995]. Arabidopsis thaliana Expressed Sequence Tags: Generation, Analysis and Dissemination. Plant Genome III: International Conference on the Status of Plant Genome Research. San Diego, CA.

35. E. F. Retzel, E. Shoop, J. V. Carlis, K. Swope, E. Chi, P. Barry, P. Bieganski, O. Holt, J. Riedl and T. Newman [1995]. The Arabidopsis cDNA Sequencing Project: Blind Analysis of Anonymous ESTs. Plant Genome III: International Conference on the Status of Plant Genome Research. San Diego, CA.

36. T. Newman, E. Shoop, K. L. Swope, E. Chi, P. Bieganski, O. Holt and E. F. Retzel [1995]. The Arabidopsis cDNA Sequencing Project: An update on Clones, Libraries, and Informational Output. Sixth International Meeting on Arabidopsis Research, Madison, WI.

37. E. F. Retzel, K. L. Swope, E. Shoop, O. Holt, J. V. Carlis, E. Chi, P. Barry, P. Bieganski, A. Lundberg, J. Riedl. and T. Newman. [1995] The Arabidopsis cDNA Sequencing Project: Biological Information Processing, Management and Retrieval. Sixth International Meeting on Arabidopsis Research, Madison, WI.

38. Swope, K.L., E. Shoop, P. Bieganski, N. Agarwal, J.V. Carlis, J. Riedl, O. Holt, E.H. Chi, T.C. Newman and E. F. Retzel. [1996]. "Determining the function of genes by EST analysis: Do high quality sequences provide the most information?" Eighth International Genome Sequencing and Analysis Conference. Hilton Head, SC, October, 1996. Abstract C-28. In: Microbial & Comparative Genomics. 1(3):255

39. Shoop, E., J.V. Carlis, E. H. Chi,. N. Agarwal, P. Bieganski, J. Riedl, K. Swope, E. F. Retzel [1996]. "An Automated Processing System and Database System for EST Similarity Analysis." Intelligent Systems in Molecular Biology Conference, St. Louis, Missouri, June, 1996.

40. Elizabeth Shoop, Paul Bieganski, Ed Chi, Olaf Holt, Troy Hanson, John Carlis, John Riedl, Kristi Swope, Ernest Retzel, Thomas Newman. Issues Related to Access and Manipulation of a Molecular Sequence Similarity Database. Workshop on New Paradigms in Information Visualization and Manipulation, in Conjunction with the ACM Conference on Information and Knowledge Management (CIKM'95).

Technical Reports

1. Ed H. Chi. The Future of Software: Visualization+Computation Tools. Future of Software Special Issue (opinion piece), Fawcette Technical Publishing.

2. Nisha Agarwal, Elizabeth Shoop, Ed Chi, and John Riedl. Sensitivity Analysis of the FASTA and BLASTX Sequence Homology Algorithms. Number TR96-042. University of Minnesota, Computer Science Department, Minneapolis, MN, June, 1996.

3. Ed Huai-hsin Chi, John Riedl, John V. Carlis, and Ernest Retzel. Computational Steering with Resource Management for Multivariate Data from Biological Sequence Similarity Searches.

4. Ed Huai-hsin Chi, Elizabeth Shoop, John V. Carlis Phillip Barry, Ernest Retzel, and John Riedl. A Novel Representation and Visualization Method for Biological Sequence Similarity Reports.

5. Ed Huai-hsin Chi, Elizabeth Shoop, John Carlis, Ernest Retzel, and John Riedl. Efficiency of Shared-Memory Multiprocessors for a Genetic Sequence Similarity Search Algorithm. Number TR97-05. Univeresity of Minnesota, Computer Science Department, Minneapolis, MN, Janurary, 1997. gzipped PostScript

6. Ed Huai-hsin Chi. Visualization of Biological Sequence Similarity Algorithm Reports. In Twelfth Midwest Chinese American Science and Technology Conference. St Louis, MI. June, 1995. Received Outstanding Paper Award.

7. E. F. Retzel, K. L. Swope, E. Shoop, O. Holt, J. V. Carlis, E. Chi, P. Barry, P. Bieganski, A. Lundberg, J. Riedl and T. Newman. Exploring the EST Data Mines. In The Plant Molecular Reporter. 1995.

8. Tamara Munzner, Paul Burchard, Ed H. Chi. Visualization through the World Wide Web with Geomview, Cyberview, W3Kit, and WebOOGL. The Second International WWW Conference '94: Mosaic and the Web. Chicago, USA, October 1994.

9. Ed H. Chi. Info for a Free Unix Operating System. Technolog, University of Minnesota, 1994.

10. Ed H. Chi. A tutorial on Computational Molecular Biology.