Implementation and testing of an automated EST processing and similarity analysis system. - Elizabeth Shoop; Ed Huai-hsin Chi; John V. Carlis; Paul Bieganski; John Riedl; Neal Dalton; Thomas Newman; Ernest Retzel (HICSS (5), 1995)

Visualization of Biological Sequence Similarity Search Results. - Ed Huai-hsin Chi; Phillip Barry; Elizabeth Shoop; John V. Carlis; Ernest Retzel; John Riedl (IEEE Visualization, 1995)

Flexible Information Visualization of Multivariate Data from Biological Sequence Similarity Searches. - Ed Huai-hsin Chi; John Riedl; Elizabeth Shoop; John V. Carlis; Ernest Retzel; Phillip Barry (IEEE Visualization, 1996)

A spreadsheet approach to information visualization. - Ed Huai-hsin Chi; Phillip Barry; John Riedl; Joseph A. Konstan (INFOVIS, 1997)

Visualizing the Evolution of Web Ecologies. - Ed Huai-hsin Chi; James E. Pitkow; Jock D. Mackinlay; Peter Pirolli; Rich Gossweiler; Stuart K. Card (CHI, 1998)

An Operator Interaction Framework for Visualization Systems. - Ed Huai-hsin Chi; John Riedl (INFOVIS, 1998)

Principles for Information Visualization Spreadsheets. - Ed Huai-hsin Chi; John Riedl; Phillip Barry; Joseph A. Konstan (IEEE Computer Graphics and Applications, 1998)

Web Analysis Visualization Spreadsheet. - Ed Huai-hsin Chi (WOWS, 1999)

Sensemaking of Evolving Web Sites Using Visualization Spreadsheets. - Ed Huai-hsin Chi; Stuart K. Card (INFOVIS, 1999)

The scent of a site: a system for analyzing and predicting information scent, usage, and usability of a Web site. - Ed Huai-hsin Chi; Peter Pirolli; James E. Pitkow (CHI, 2000)

Enhancing a digital book with a reading recommender. - Allison Woodruff; Rich Gossweiler; James E. Pitkow; Ed Huai-hsin Chi; Stuart K. Card (CHI, 2000)

A Taxonomy of Visualization Techniques Using the Data State Reference Model. - Ed Huai-hsin Chi (INFOVIS, 2000)

Case Study: Resource Steering in a Visualization System. - Ed H. Chi; John Riedl (VisSym, 2000)

Novel visualization method for biological sequence similarity reports. - Ed H. Chi; John Riedl; Elizabeth Shoop; Phillip Barry (J. Electronic Imaging, 2000)

Using information scent to model user information needs and actions and the Web. - Ed Huai-hsin Chi; Peter Pirolli; Kim Chen; James E. Pitkow (CHI, 2001)

Expressiveness of the data flow and data state models in visualization systems. - Ed H. Chi (AVI, 2002)

Separating the swarm: categorization methods for user sessions on the web. - Jeffrey Heer; Ed Huai-hsin Chi (CHI, 2002)

LumberJack: Intelligent Discovery and Analysis of Web User Traffic Composition. - Ed Huai-hsin Chi; Adam Rosien; Jeffrey Heer (WEBKDD, 2002)

Improving Web Usability Through Visualization. - Ed Huai-hsin Chi (IEEE Internet Comput., 2002)

The bloodhound project: automating discovery of web usability issues using the InfoScent simulator. - Ed Huai-hsin Chi; Adam Rosien; Gesara Supattanasiri; Amanda Williams; Christiaan Royer; Celia Chow; Erica Robles; Brinda Dalal; Julie Chen; Steve B. Cousins (CHI, 2003)

ScentTrails: integrating browsing and searching on the Web. - Christopher Olston; Ed Huai-hsin Chi (Interactions, 2003)

3Book: a 3D electronic smart book. - Stuart K. Card; Lichan Hong; Jock D. Mackinlay; Ed Huai-hsin Chi (AVI, 2004)

3Book: a scalable 3D virtual book. - Stuart K. Card; Lichan Hong; Jock D. Mackinlay; Ed Huai-hsin Chi (CHI Extended Abstracts, 2004)

eBooks with indexes that reorganize conceptually. - Ed Huai-hsin Chi; Lichan Hong; Julie Heiser; Stuart K. Card (CHI Extended Abstracts, 2004)

"Killer App" of wearable computing: wireless force sensing body protectors for martial arts. - Ed Huai-hsin Chi; Jin Song; Greg Corbin (UIST, 2004)

Annotating 3D electronic books. - Lichan Hong; Ed Huai-hsin Chi; Stuart K. Card (CHI Extended Abstracts, 2005)

ScentHighlights: highlighting conceptually-related sentences during reading. - Ed Huai-hsin Chi; Lichan Hong; Michelle Gumbrecht; Stuart K. Card (IUI, 2005)

Introducing wearable force sensors in martial arts. - Ed H. Chi (IEEE Pervasive Comput., 2005)

Guest Editors' Introduction: Pervasive Computing in Sports Technologies. - Ed H. Chi; Gaetano Borriello; G. Hunt; Nigel Davies 001 (IEEE Pervasive Comput., 2005)

Entity quick click: rapid text copying based on automatic entity extraction. - Eric A. Bier; Edward W. Ishak; Ed Huai-hsin Chi (CHI Extended Abstracts, 2006)

Scentindex: Conceptually Reorganizing Subject Indexes for Reading. - Ed H. Chi; Lichan Hong; Julie Heiser; Stuart K. Card (IEEE VAST, 2006)

Entity Workspace: An Evidence File That Aids Memory, Inference, and Reading. - Eric A. Bier; Edward W. Ishak; Ed Huai-hsin Chi (ISI, 2006)

He says, she says: conflict and coordination in Wikipedia. - Aniket Kittur; Bongwon Suh; Bryan A. Pendleton; Ed H. Chi (CHI, 2007)

Visual Foraging of Highlighted Text: An Eye-Tracking Study. - Ed Huai-hsin Chi; Michelle Gumbrecht; Lichan Hong (HCI (3), 2007)

Aspects of Augmented Social Cognition: Social Information Foraging and Social Search. - Ed Huai-hsin Chi; Peter Pirolli; Shyong K. Lam (HCI (15), 2007)

Us vs. Them: Understanding Social Dynamics in Wikipedia with Revert Graph Visualizations. - Bongwon Suh; Ed H. Chi; Bryan A. Pendleton; Aniket Kittur (IEEE VAST, 2007)

ScentIndex and ScentHighlights: productive reading techniques for conceptually reorganizing subject indexes and highlighting passages. - Ed Huai-hsin Chi; Lichan Hong; Julie Heiser; Stuart K. Card; Michelle Gumbrecht (Inf. Vis., 2007)

Augmented Social Cognition. - Ed H. Chi; Peter Pirolli; Bongwon Suh; Aniket Kittur; Bryan A. Pendleton; Todd Mytkowicz (AAAI Spring Symposium: Social Information Processing, 2008)

SparTag.us: a low cost tagging system for foraging of web content. - Lichan Hong; Ed Huai-hsin Chi; Raluca Budiu; Peter Pirolli; Les Nelson (AVI, 2008)

Activity-based serendipitous recommendations with the Magitti mobile leisure guide. - Victoria Bellotti; James Bo Begole; Ed Huai-hsin Chi; Nicolas Ducheneaut; Ji Fang; Ellen Isaacs; Tracy Holloway King; Mark W. Newman; Kurt Partridge; Bob Price; Paul Rasmussen; Michael Roberts; et al. (CHI, 2008)

Crowdsourcing user studies with Mechanical Turk. - Aniket Kittur; Ed H. Chi; Bongwon Suh (CHI, 2008)

Lifting the veil: improving accountability and social transparency in Wikipedia with wikidashboard. - Bongwon Suh; Ed H. Chi; Aniket Kittur; Bryan A. Pendleton (CHI, 2008)

Towards a model of understanding social search. - Brynn M. Evans; Ed H. Chi (SSM, 2008)

The social (open) workspace. - David A. Evans 001; Susan Feldman; Ed H. Chi; Natasa Milic-Frayling; Igor Perisic (CIKM, 2008)

Can you ever trust a wiki?: impacting perceived trustworthiness in wikipedia. - Aniket Kittur; Bongwon Suh; Ed H. Chi (CSCW, 2008)

Understanding the Efficiency of Social Tagging Systems using Information Theory. - Ed H. Chi; Todd Mytkowicz (ICWSM, 2008)

The Social Web: Research and Opportunities. - Ed H. Chi (Computer, 2008)

Annotate once, appear anywhere: collective foraging for snippets of interest using paragraph fingerprinting. - Lichan Hong; Ed H. Chi (CHI, 2009)

Signpost from the masses: learning effects in an exploratory social tag search browser. - Yvonne Kammerer; Rowan Nairn; Peter Pirolli; Ed Huai-hsin Chi (CHI, 2009)

What's in Wikipedia?: mapping topics and conflict using socially annotated category structure. - Aniket Kittur; Ed H. Chi; Bongwon Suh (CHI, 2009)

With a little help from my friends: examining the impact of social annotations in sensemaking tasks. - Les Nelson; Christoph Held; Peter Pirolli; Lichan Hong; Diane J. Schiano; Ed H. Chi (CHI, 2009)

A Position Paper on 'Living Laboratories': Rethinking Ecological Designs and Experimentation in Human-Computer Interaction. - Ed H. Chi (HCI (1), 2009)

Activity Awareness and Social Sensemaking 2.0: Design of a Task Force Workspace. - Gregorio Convertino; Lichan Hong; Les Nelson; Peter Pirolli; Ed H. Chi (HCI (16), 2009)

Impact on Performance and Process by a Social Annotation System: A Social Reading Experiment. - Les Nelson; Gregorio Convertino; Peter Pirolli; Lichan Hong; Ed H. Chi (HCI (16), 2009)

Augmented social cognition: using social web technology to enhance the ability of groups to remember, think, and reason. - Ed H. Chi (SIGMOD Conference, 2009)

Collaborative Filtering Is Not Enough? Experiments with a Mixed-Model Recommender for Leisure Activities. - Nicolas Ducheneaut; Kurt Partridge; Qingfeng Huang; Bob Price; Michael Roberts; Ed H. Chi; Victoria Bellotti; Bo Begole (UMAP, 2009)

The singularity is not near: slowing growth of Wikipedia. - Bongwon Suh; Gregorio Convertino; Ed H. Chi; Peter Pirolli (Int. Sym. Wikis, 2009)

Information Seeking Can Be Social. - Ed H. Chi (Computer, 2009)

Designing a cross-channel information management tool for workers in enterprise task forces. - Gregorio Convertino; Sanjay Kairam; Lichan Hong; Bongwon Suh; Ed H. Chi (AVI, 2010)

Short and tweet: experiments on recommending content from information streams. - Jilin Chen; Rowan Nairn; Les Nelson; Michael S. Bernstein; Ed H. Chi (CHI, 2010)

FeedWinnower: layering structures over collections of information streams. - Lichan Hong; Gregorio Convertino; Bongwon Suh; Ed H. Chi; Sanjay Kairam (CHI, 2010)

Clorg: collective intelligence in organizations. - Gregorio Convertino; Antonietta Grasso; Giorgio De Michelis; David R. Millen; Ed H. Chi (GROUP, 2010)

A Comparison of Generated Wikipedia Profiles Using Social Labeling and Automatic Keyword Extraction. - Terrell Russell; Bongwon Suh; Ed H. Chi (ICWSM, 2010)

Keynote: Model-Driven Research in Human-Computer Interaction. - Ed H. Chi (MuC, 2010)

Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network. - Bongwon Suh; Lichan Hong; Peter Pirolli; Ed H. Chi (SocialCom/PASSAT, 2010)

Eddi: interactive topic-based browsing of social status streams. - Michael S. Bernstein; Bongwon Suh; Lichan Hong; Jilin Chen; Sanjay Kairam; Ed H. Chi (UIST, 2010)

Model-Driven Research in Human-Centric Computing. - Ed H. Chi (VL/HCC, 2010)

Expanding CS education; improving software development. - Ed H. Chi; Ruben Ortega (Commun. ACM, 2010)

The chaos of the internet as an external brain; and more. - Greg Linden; Ed H. Chi; Mark Guzdial (Commun. ACM, 2010)

Advancing the Design of Technology-Mediated Social Participation Systems. - Ed H. Chi; Sean Munson; Gerhard Fischer; Sarah Vieweg; Cynthia Parr (Computer, 2010)

An elaborated model of social search. - Brynn M. Evans; Ed H. Chi (Inf. Process. Manag., 2010)

Mail2Wiki: low-cost sharing and early curation from email to wikis. - Benjamin V. Hanrahan; Guillaume Bouchard; Gregorio Convertino; Thiébaud Weksteen; Nicholas Kong; Cédric Archambeau; Ed H. Chi (C&T, 2011)

The trouble with social computing systems research. - Michael S. Bernstein; Mark S. Ackerman; Ed H. Chi; Robert C. Miller (CHI Extended Abstracts, 2011)

Crowdsourcing and human computation: systems, studies and platforms. - Michael S. Bernstein; Ed H. Chi; Lydia B. Chilton; Björn Hartmann; Aniket Kittur; Robert C. Miller (CHI Extended Abstracts, 2011)

Speak little and well: recommending conversations in online social streams. - Jilin Chen; Rowan Nairn; Ed Huai-hsin Chi (CHI, 2011)

Transferability of research findings: context-dependent or model-driven. - Ed H. Chi; Mary Czerwinski; David R. Millen; Dave W. Randall 001; Gunnar Stevens; Volker Wulf; John Zimmerman (CHI Extended Abstracts, 2011)

Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles. - Brent J. Hecht; Lichan Hong; Bongwon Suh; Ed H. Chi (CHI, 2011)

VisualWikiCurator: a corporate Wiki plugin. - Nicholas Kong; Gregorio Convertino; Benjamin V. Hanrahan; Ed H. Chi (CHI Extended Abstracts, 2011)

From slacktivism to activism: participatory culture in the age of social media. - Dana Rotman; Sarah Vieweg; Sarita Yardi; Ed Huai-hsin Chi; Jenny Preece; Ben Shneiderman; Peter Pirolli; Tom Glaisyer (CHI Extended Abstracts, 2011)

RepliCHI - CHI should be replicating and validating results more: discuss. - Max L. Wilson 001; Wendy E. Mackay; Ed H. Chi; Michael S. Bernstein; Daniel M. Russell; Harold W. Thimbleby (CHI Extended Abstracts, 2011)

Mail2Tag: Augmenting email for sharing with implicit tag-based categorization. - Les Nelson; Rowan Nairn; Ed H. Chi; Gregorio Convertino (CTS, 2011)

Studying the Adoption of Mail2Tag: an Enterprise2.0 Tool for Sharing. - Les Nelson; Gregorio Convertino; Ed H. Chi; Rowan Nairn (ECSCW, 2011)

Language Matters In Twitter: A Large Scale Study. - Lichan Hong; Gregorio Convertino; Ed H. Chi (ICWSM, 2011)

Is Twitter a Good Place for Asking Questions? A Characterization Study. - Sharoda A. Paul; Lichan Hong; Ed H. Chi (ICWSM, 2011)

Mail2Wiki: posting and curating Wiki content from email. - Benjamin V. Hanrahan; Thiébaud Weksteen; Nicholas Kong; Gregorio Convertino; Guillaume Bouchard; Cédric Archambeau; Ed H. Chi (IUI, 2011)

VisualWikiCurator: human and machine intelligencefor organizing wiki content. - Nicholas Kong; Benjamin V. Hanrahan; Thiébaud Weksteen; Gregorio Convertino; Ed H. Chi (IUI, 2011)

Apples to oranges?: comparing across studies of open collaboration/peer production. - Judd Antin; Ed H. Chi; James Howison; Sharoda A. Paul; Aaron D. Shaw; Jude Yew (Int. Sym. Wikis, 2011)

Reviewing peer review. - Jeannette M. Wing; Ed H. Chi (Commun. ACM, 2011)

Talking in circles: selective sharing in google+. - Sanjay Kairam; Mike Brzozowski; David A. Huffaker; Ed Huai-hsin Chi (CHI, 2012)

Social annotations in web search. - Aditi S. Muralidharan; Zoltán Gyöngyi; Ed H. Chi (CHI, 2012)

RepliCHI SIG: from a panel to a new submission venue for replication. - Max L. Wilson 001; Wendy E. Mackay; Ed Huai-hsin Chi; Michael S. Bernstein; Jeffrey Nichols 001 (CHI Extended Abstracts, 2012)

2nd Workshop on context-awareness in retrieval and recommendation: (CaRR 2012). - Ernesto William De Luca; Matthias Böhmer 001; Alan Said; Ed H. Chi (IUI, 2012)

Who knows?: searching for expertise on the social web: technical perspective. - Ed H. Chi (Commun. ACM, 2012)

Online privacy; replicating research results. - Daniel Reed; Ed H. Chi (Commun. ACM, 2012)

Who is Authoritative? Understanding Reputation Mechanisms in Quora - Sharoda A. Paul; Lichan Hong; Ed H. Chi (CoRR, 2012)

Leveraging Online Populations for Crowdsourcing [Guest editors' introduction]. - Ed H. Chi; Michael S. Bernstein (IEEE Internet Comput., 2012)

Re-testing the Perception of Social Annotations in Web Search. - Jennifer Fernquist; Ed H. Chi (RepliCHI, 2013)

All the news that's fit to read: a study of social annotations for news reading. - Chinmay Kulkarni 001; Ed H. Chi (CHI, 2013)

Swipe vs. scroll: web page switching on mobile browsers. - Andrew Warr; Ed H. Chi (CHI, 2013)

RepliCHI: the workshop. - Max L. Wilson 001; Paul Resnick; David Coyle; Ed H. Chi (CHI Extended Abstracts, 2013)

Instant foodie: predicting expert ratings from grassroots. - Chenhao Tan; Ed H. Chi; David A. Huffaker; Gueorgi Kossinets; Alexander J. Smola (CIKM, 2013)

The Science of Social Interactions on the Web. - Ed H. Chi (CW, 2013)

Inserting Micro-Breaks into Crowdsourcing Workflows. - Jeffrey M. Rzeszotarski; Ed H. Chi; Praveen K. Paritosh; Peng Dai 001 (HCOMP (Works in Progress / Demos), 2013)

The false dichotomy between accessibility and usability. - Ed H. Chi (W4A, 2013)

Perception and understanding of social annotations in web search. - Jennifer Fernquist; Ed H. Chi (WWW, 2013)

Already up? using mobile phones to track & share sleep behavior. - Alireza Sahami Shirazi; James Clawson; Yashar Hassanpour; Mohammad J. Tourian; Albrecht Schmidt 001; Ed H. Chi; Marko Borazio; Kristof Van Laerhoven (Int. J. Hum. Comput. Stud., 2013)

Crowdsourcing in HCI Research. - Serge Egelman; Ed H. Chi; Steven Dow (Ways of Knowing in HCI, 2014)

Looking Back: Retrospective Study Methods for HCI. - Daniel M. Russell; Ed H. Chi (Ways of Knowing in HCI, 2014)

Location and Language Use in Social Media. - Ed H. Chi (LTCSS@ACL, 2014)

RepliCHI: the workshop II. - Max L. Wilson 001; Ed H. Chi; Stuart Reeves; David Coyle (CHI Extended Abstracts, 2014)

Google+ Communities as Plazas and Topic Boards. - Michael J. Brzozowski; Phil Adams; Ed H. Chi (CHI, 2015)

Design for Searching & Finding. - Daniel M. Russell; Jaime Teevan; Meredith Ringel Morris; Marti A. Hearst; Ed H. Chi (CHI Extended Abstracts, 2015)

And Now for Something Completely Different: Improving Crowdsourcing Workflows with Micro-Diversions. - Peng Dai 001; Jeffrey M. Rzeszotarski; Praveen K. Paritosh; Ed H. Chi (CSCW, 2015)

Blurring of the Boundary Between Interactive Search and Recommendation. - Ed H. Chi (IUI, 2015)

Got Many Labels?: Deriving Topic Labels from Multiple Sources for Social Media Posts using Crowdsourcing and Ensemble Learning. - Shuo Chang; Peng Dai 001; Jilin Chen; Ed Huai-hsin Chi (WWW (Companion Volume), 2015)

Improving User Topic Interest Profiles by Behavior Factorization. - Zhe Zhao 001; Zhiyuan Cheng 002; Lichan Hong; Ed Huai-hsin Chi (WWW, 2015)

1st International Workshop on Multilingual Web Access (MWA 2015). - Ben Steichen; Nicola Ferro 001; David Lewis 001; Ed H. Chi (SIGIR Forum, 2015)

Window Shopping: A Study of Desktop Window Switching. - Andrew Warr; Ed H. Chi; Helen Harris; Alexander Kuscher; Jenn Chen; Robert Flack; Nicholas Jitkoff (CHI, 2016)

Video Watch Time and Comment Sentiment: Experiences from YouTube. - Rong Yang; Sarvjeet Singh; Pei Cao; Ed H. Chi; Bo Fu (HotWeb, 2016)

AppGrouper: Knowledge-based Interactive Clustering Tool for App Search Results. - Shuo Chang; Peng Dai 001; Lichan Hong; Cheng Sheng 002; Tianjiao Zhang; Ed H. Chi (IUI, 2016)

Beyond Globally Optimal: Focused Learning for Improved Recommendations. - Alex Beutel; Ed Huai-hsin Chi; Zhiyuan Cheng 002; Hubert Pham; John R. Anderson (WWW, 2017)

Technical perspective: Humans and computers working together on hard tasks. - Ed H. Chi (Commun. ACM, 2017)

Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations. - Alex Beutel; Jilin Chen; Zhe Zhao 001; Ed H. Chi (CoRR, 2017)

Factorized Recurrent Neural Architectures for Longer Range Dependence. - Francois Belletti; Alex Beutel; Sagar Jain; Ed Huai-hsin Chi (AISTATS, 2018)

Practical Diversified Recommendations on YouTube with Determinantal Point Processes. - Mark Wilhelm; Ajith Ramanathan; Alexander Bonomo; Sagar Jain; Ed H. Chi; Jennifer Gillenwater (CIKM, 2018)

Q&R: A Two-Stage Approach toward Interactive Recommendation. - Konstantina Christakopoulou; Alex Beutel; Rui Li 049; Sagar Jain; Ed H. Chi (KDD, 2018)

Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts. - Jiaqi Ma 001; Zhe Zhao 001; Xinyang Yi; Jilin Chen; Lichan Hong; Ed H. Chi (KDD, 2018)

Categorical-attributes-based item classification for recommender systems. - Qian Zhao; Jilin Chen; Minmin Chen; Sagar Jain; Alex Beutel; Francois Belletti; Ed H. Chi (RecSys, 2018)

The Case for Learned Index Structures. - Tim Kraska; Alex Beutel; Ed H. Chi; Jeffrey Dean; Neoklis Polyzotis (SIGMOD Conference, 2018)

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

Seq2Slate: Re-ranking and Slate Optimization with RNNs. - Irwan Bello; Sayali Kulkarni; Sagar Jain; Craig Boutilier; Ed Huai-hsin Chi; Elad Eban; Xiyang Luo; Alan Mackey; Ofer Meshi (CoRR, 2018)

Evaluation and Refinement of Clustered Search Results with the Crowd. - Amy X. Zhang; Jilin Chen; Wei Chai; Jinjun Xu; Lichan Hong; Ed H. Chi (ACM Trans. Interact. Intell. Syst., 2018)

SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning. - Jiaqi Ma 001; Zhe Zhao 001; Jilin Chen; Ang Li; Lichan Hong; Ed H. Chi (AAAI, 2019)

Putting Fairness Principles into Practice: Challenges, Metrics, and Improvements. - Alex Beutel; Jilin Chen; Tulsee Doshi; Hai Qian; Allison Woodruff; Christine Luu; Pierre Kreitmann; Jonathan Bischof; Ed H. Chi (AIES, 2019)

Counterfactual Fairness in Text Classification through Robustness. - Sahaj Garg; Vincent Perot; Nicole Limtiaco; Ankur Taly; Ed H. Chi; Alex Beutel (AIES, 2019)

SageDB: A Learned Database System. - Tim Kraska; Mohammad Alizadeh; Alex Beutel; Ed H. Chi; Ani Kristo; Guillaume Leclerc; Samuel Madden 001; Hongzi Mao; Vikram Nathan (CIDR, 2019)

AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks. - Bo Chang 002; Minmin Chen; Eldad Haber; Ed H. Chi (ICLR (Poster), 2019)

Efficient Training on Very Large Corpora via Gramian Estimation. - Walid Krichene; Nicolas Mayoraz; Steffen Rendle; Li Zhang 001; Xinyang Yi; Lichan Hong; Ed H. Chi; John R. Anderson (ICLR (Poster), 2019)

Quantifying Long Range Dependence in Language and User Behavior to improve RNNs. - Francois Belletti; Minmin Chen; Ed H. Chi (KDD, 2019)

Fairness in Recommendation Ranking through Pairwise Comparisons. - Alex Beutel; Jilin Chen; Tulsee Doshi; Hai Qian; Li Wei; Yi Wu; Lukasz Heldt; Zhe Zhao 001; Lichan Hong; Ed H. Chi; Cristos Goodrow (KDD, 2019)

Sampling-bias-corrected neural modeling for large corpus item recommendations. - Xinyang Yi; Ji Yang; Lichan Hong; Derek Zhiyuan Cheng; Lukasz Heldt; Aditee Kumthekar; Zhe Zhao 001; Li Wei; Ed H. Chi (RecSys, 2019)

Recommending what video to watch next: a multitask ranking system. - Zhe Zhao 001; Lichan Hong; Li Wei; Jilin Chen; Aniruddh Nath; Shawn Andrews; Aditee Kumthekar; Maheswaran Sathiamoorthy; Xinyang Yi; Ed H. Chi (RecSys, 2019)

Top-K Off-Policy Correction for a REINFORCE Recommender System. - Minmin Chen; Alex Beutel; Paul Covington; Sagar Jain; Francois Belletti; Ed H. Chi (WSDM, 2019)

Towards Neural Mixture Recommender for Long Range Dependent User Sequences. - Jiaxi Tang; Francois Belletti; Sagar Jain; Minmin Chen; Alex Beutel; Can Xu; Ed H. Chi (WWW, 2019)

Dynamical Isometry and a Mean Field Theory of LSTMs and GRUs. - Dar Gilboa; Bo Chang 002; Minmin Chen; Greg Yang; Samuel S. Schoenholz; Ed H. Chi; Jeffrey Pennington (CoRR, 2019)

Transfer of Machine Learning Fairness across Domains. - Candice Schumann; Xuezhi Wang 002; Alex Beutel; Jilin Chen; Hai Qian; Ed H. Chi (CoRR, 2019)

Toward a better trade-off between performance and fairness with kernel-based distribution matching. - Flavien Prost; Hai Qian; Qiuwen Chen; Ed H. Chi; Jilin Chen; Alex Beutel (CoRR, 2019)

Practical Compositional Fairness: Understanding Fairness in Multi-Task ML Systems. - Xuezhi Wang 002; Nithum Thain; Anu Sinha; Ed H. Chi; Jilin Chen; Alex Beutel (CoRR, 2019)

Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval. - Tao Wu; Ellie Ka In Chio; Heng-Tze Cheng; Yu Du; Steffen Rendle; Dima Kuzmin; Ritesh Agarwal; Li Zhang 001; John R. Anderson; Sarvjeet Singh; Tushar Chandra; Ed H. Chi; et al. (CIKM, 2020)

CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation. - Tianlu Wang; Xuezhi Wang 002; Yao Qin 001; Ben Packer; Kang Li; Jilin Chen; Alex Beutel; Ed H. Chi (EMNLP (1), 2020)

BRPO: Batch Residual Policy Optimization. - Sungryull Sohn; Yinlam Chow; Jayden Ooi; Ofir Nachum; Honglak Lee; Ed H. Chi; Craig Boutilier (IJCAI, 2020)

Fairness without Demographics through Adversarially Reweighted Learning. - Preethi Lahoti; Alex Beutel; Jilin Chen; Kang Lee; Flavien Prost; Nithum Thain; Xuezhi Wang 002; Ed H. Chi (NeurIPS, 2020)

Deconfounding User Satisfaction Estimation from Response Rate Bias. - Konstantina Christakopoulou; Madeleine Traverse; Trevor Potter; Emma Marriott; Daniel Li; Chris Haulk; Ed H. Chi; Minmin Chen (RecSys, 2020)

From Missing Data to Boltzmann Distributions and Time Dynamics: The Statistical Physics of Recommendation. - Ed H. Chi (WSDM, 2020)

End-to-End Deep Attentive Personalized Item Retrieval for Online Content-sharing Platforms. - Jyun-Yu Jiang; Tao Wu; Georgios Roumpos; Heng-Tze Cheng; Xinyang Yi; Ed H. Chi; Harish Ganapathy; Nitin Jindal; Pei Cao; Wei Wang 010 (WWW, 2020)

Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems. - Wang-Cheng Kang; Derek Zhiyuan Cheng; Ting Chen; Xinyang Yi; Dong Lin; Lichan Hong; Ed H. Chi (WWW (Companion Volume), 2020)

Off-policy Learning in Two-stage Recommender Systems. - Jiaqi Ma 001; Zhe Zhao 001; Xinyang Yi; Ji Yang; Minmin Chen; Jiaxi Tang; Lichan Hong; Ed H. Chi (WWW, 2020)

Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations. - Ji Yang; Xinyang Yi; Derek Zhiyuan Cheng; Lichan Hong; Yang Li 150; Simon Xiaoming Wang; Taibai Xu; Ed H. Chi (WWW (Companion Volume), 2020)

Understanding and Improving Knowledge Distillation. - Jiaxi Tang; Rakesh Shivanna; Zhe Zhao 001; Dong Lin; Anima Singh; Ed H. Chi; Sagar Jain (CoRR, 2020)

Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing. - Ge Liu; Rui Wu 020; Heng-Tze Cheng; Jing Wang; Jayden Ooi; Lihong Li 001; Ang Li; Wai Lok Sibon Li; Craig Boutilier; Ed H. Chi (CoRR, 2020)

Developing a Recommendation Benchmark for MLPerf Training and Inference. - Carole-Jean Wu; Robin Burke; Ed H. Chi; Joseph A. Konstan; Julian J. McAuley; Yves Raimond; Hao Zhang (CoRR, 2020)

Improving Uncertainty Estimates through the Relationship with Adversarial Robustness. - Yao Qin 001; Xuezhi Wang 002; Alex Beutel; Ed H. Chi (CoRR, 2020)

Self-supervised Learning for Deep Models in Recommendations. - Tiansheng Yao; Xinyang Yi; Derek Zhiyuan Cheng; Felix X. Yu; Aditya Krishna Menon; Lichan Hong; Ed H. Chi; Steve Tjoa; Jieqi Kang; Evan Ettinger (CoRR, 2020)

Small Towers Make Big Differences. - Yuyan Wang; Zhe Zhao 001; Bo Dai 001; Christopher Fifty; Dong Lin; Lichan Hong; Ed H. Chi (CoRR, 2020)

DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems. - Ruoxi Wang; Rakesh Shivanna; Derek Zhiyuan Cheng; Sagar Jain; Dong Lin; Lichan Hong; Ed H. Chi (CoRR, 2020)

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

Learned Indexes for a Google-scale Disk-based Database. - Hussam Abu-Libdeh; Deniz Altinbüken; Alex Beutel; Ed H. Chi; Lyric Doshi; Tim Kraska; Xiaozhou Li; Andy Ly; Christopher Olston (CoRR, 2020)

Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. - Flavien Prost; Pranjal Awasthi; Nick Blumm; Aditee Kumthekar; Trevor Potter; Li Wei; Xuezhi Wang 002; Ed H. Chi; Jilin Chen; Alex Beutel (AIES, 2021)

Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. - Jiaqi Ma 001; Xinyang Yi; Weijing Tang; Zhe Zhao 001; Lichan Hong; Ed H. Chi; Qiaozhu Mei (AISTATS, 2021)

Self-supervised Learning for Large-scale Item Recommendations. - Tiansheng Yao; Xinyang Yi; Derek Zhiyuan Cheng; Felix X. Yu; Ting Chen; Aditya Krishna Menon; Lichan Hong; Ed H. Chi; Steve Tjoa; Jieqi (Jay) Kang; Evan Ettinger (CIKM, 2021)

Can We Improve Model Robustness through Secondary Attribute Counterfactuals? - Ananth Balashankar; Xuezhi Wang 002; Ben Packer; Nithum Thain; Ed H. Chi; Alex Beutel (EMNLP (1), 2021)

Batch Reinforcement Learning Through Continuation Method. - Yijie Guo; Shengyu Feng; Nicolas Le Roux; Ed H. Chi; Honglak Lee; Minmin Chen (ICLR, 2021)

Learning to Embed Categorical Features without Embedding Tables for Recommendation. - Wang-Cheng Kang; Derek Zhiyuan Cheng; Tiansheng Yao; Xinyang Yi; Ting Chen; Lichan Hong; Ed H. Chi (KDD, 2021)

Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. - Yuyan Wang; Xuezhi Wang 002; Alex Beutel; Flavien Prost; Jilin Chen; Ed H. Chi (KDD, 2021)

DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. - Hussein Hazimeh 001; Zhe Zhao 001; Aakanksha Chowdhery; Maheswaran Sathiamoorthy; Yihua Chen; Rahul Mazumder; Lichan Hong; Ed H. Chi (NeurIPS, 2021)

Improving Calibration through the Relationship with Adversarial Robustness. - Yao Qin 001; Xuezhi Wang 002; Alex Beutel; Ed H. Chi (NeurIPS, 2021)

Values of User Exploration in Recommender Systems. - Minmin Chen; Yuyan Wang; Can Xu; Ya Le; Mohit Sharma 002; Lee Richardson; Su-Lin Wu; Ed H. Chi (RecSys, 2021)

Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems. - Xuezhi Wang 002; Nithum Thain; Anu Sinha; Flavien Prost; Ed H. Chi; Jilin Chen; Alex Beutel (WSDM, 2021)

User Response Models to Improve a REINFORCE Recommender System. - Minmin Chen; Bo Chang 002; Can Xu; Ed H. Chi (WSDM, 2021)

Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems. - Zhe Chen; Yuyan Wang; Dong Lin; Derek Zhiyuan Cheng; Lichan Hong; Ed H. Chi; Claire Cui (WSDM, 2021)

DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems. - Ruoxi Wang; Rakesh Shivanna; Derek Zhiyuan Cheng; Sagar Jain; Dong Lin; Lichan Hong; Ed H. Chi (WWW, 2021)

Towards Content Provider Aware Recommender Systems: A Simulation Study on the Interplay between User and Provider Utilities. - Ruohan Zhan; Konstantina Christakopoulou; Ya Le; Jayden Ooi; Martin Mladenov; Alex Beutel; Craig Boutilier; Ed H. Chi; Minmin Chen (WWW, 2021)

A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. - Yin Zhang 011; Derek Zhiyuan Cheng; Tiansheng Yao; Xinyang Yi; Lichan Hong; Ed H. Chi (WWW, 2021)

Measuring Recommender System Effects with Simulated Users. - Sirui Yao; Yoni Halpern; Nithum Thain; Xuezhi Wang 002; Kang Lee; Flavien Prost; Ed H. Chi; Jilin Chen; Alex Beutel (CoRR, 2021)

HyperPrompt: Prompt-based Task-Conditioning of Transformers. - Yun He; Huaixiu Steven Zheng; Yi Tay; Jai Prakash Gupta 001; Yu Du; Vamsi Aribandi; Zhe Zhao 001; YaGuang Li; Zhao Chen; Donald Metzler; Heng-Tze Cheng; Ed H. Chi (ICML, 2022)

Surrogate for Long-Term User Experience in Recommender Systems. - Yuyan Wang; Mohit Sharma 002; Can Xu; Sriraj Badam; Qian Sun 005; Lee Richardson; Lisa Chung; Ed H. Chi; Minmin Chen (KDD, 2022)

Improving Multi-Task Generalization via Regularizing Spurious Correlation. - Ziniu Hu; Zhe Zhao 001; Xinyang Yi; Tiansheng Yao; Lichan Hong; Yizhou Sun; Ed H. Chi (NeurIPS, 2022)

Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. - Jason Wei; Xuezhi Wang 002; Dale Schuurmans; Maarten Bosma; Brian Ichter; Fei Xia 002; Ed H. Chi; Quoc V. Le; Denny Zhou (NeurIPS, 2022)

Off-Policy Actor-critic for Recommender Systems. - Minmin Chen; Can Xu; Vince Gatto; Devanshu Jain; Aviral Kumar; Ed H. Chi (RecSys, 2022)

Multi-Resolution Attention for Personalized Item Search. - Furkan Kocayusufoglu; Tao Wu; Anima Singh; Georgios Roumpos; Heng-Tze Cheng; Sagar Jain; Ed H. Chi; Ambuj K. Singh (WSDM, 2022)

Learning to Augment for Casual User Recommendation. - Jianling Wang; Ya Le; Bo Chang 002; Yuyan Wang; Ed H. Chi; Minmin Chen (WWW, 2022)

Can Small Heads Help? Understanding and Improving Multi-Task Generalization. - Yuyan Wang; Zhe Zhao 001; Bo Dai 001; Christopher Fifty; Dong Lin; Lichan Hong; Li Wei; Ed H. Chi (WWW, 2022)

Distributionally-robust Recommendations for Improving Worst-case User Experience. - Hongyi Wen; Xinyang Yi; Tiansheng Yao; Jiaxi Tang; Lichan Hong; Ed H. Chi (WWW, 2022)

LaMDA: Language Models for Dialog Applications. - 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; et al. (CoRR, 2022)

Recency Dropout for Recurrent Recommender Systems. - Bo Chang 002; Can Xu; Matthieu Lê; Jingchen Feng; Ya Le; Sriraj Badam; Ed H. Chi; Minmin Chen (CoRR, 2022)

Chain of Thought Prompting Elicits Reasoning in Large Language Models. - Jason Wei; Xuezhi Wang 002; Dale Schuurmans; Maarten Bosma; Ed H. Chi; Quoc Le 001; Denny Zhou (CoRR, 2022)

Algorithms for Efficiently Learning Low-Rank Neural Networks. - Kiran Vodrahalli; Rakesh Shivanna; Maheswaran Sathiamoorthy; Sagar Jain; Ed H. Chi (CoRR, 2022)

Self-Consistency Improves Chain of Thought Reasoning in Language Models. - Xuezhi Wang 002; Jason Wei; Dale Schuurmans; Quoc V. Le; Ed H. Chi; Denny Zhou (CoRR, 2022)

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. - Denny Zhou; Nathanael Schärli; Le Hou; Jason Wei; Nathan Scales; Xuezhi Wang 002; Dale Schuurmans; Olivier Bousquet; Quoc Le 001; Ed H. Chi (CoRR, 2022)

Rationale-Augmented Ensembles in Language Models. - Xuezhi Wang 002; Jason Wei; Dale Schuurmans; Quoc V. Le; Ed H. Chi; Denny Zhou (CoRR, 2022)

Reward Shaping for User Satisfaction in a REINFORCE Recommender. - 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; et al. (CoRR, 2022)

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

Scaling Instruction-Finetuned Language Models. - Hyung Won Chung; Le Hou; Shayne Longpre; Barret Zoph; Yi Tay; William Fedus; Eric Li; Xuezhi Wang 002; Mostafa Dehghani 001; Siddhartha Brahma; Albert Webson; Shixiang Shane Gu; et al. (CoRR, 2022)

Emergent Abilities of Large Language Models. - 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; et al. (Trans. Mach. Learn. Res., 2022)

Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. - Mirac Suzgun; Nathan Scales; Nathanael Schärli; Sebastian Gehrmann; Yi Tay; Hyung Won Chung; Aakanksha Chowdhery; Quoc V. Le; Ed H. Chi; Denny Zhou; Jason Wei (ACL (Findings), 2023)

Multitask Ranking System for Immersive Feed and No More Clicks: A Case Study of Short-Form Video Recommendation. - Qingyun Liu 003; Zhe Zhao 001; Liang Liu 017; Zhen Zhang; Junjie Shan; Yuening Li; Shuchao Bi; Lichan Hong; Ed H. Chi (CIKM, 2023)

Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation. - Ananth Balashankar; Xuezhi Wang 002; Yao Qin 001; Ben Packer; Nithum Thain; Ed H. Chi; Jilin Chen; Alex Beutel (EMNLP (Findings), 2023)

Self-Consistency Improves Chain of Thought Reasoning in Language Models. - Xuezhi Wang 002; Jason Wei; Dale Schuurmans; Quoc V. Le; Ed H. Chi; Sharan Narang; Aakanksha Chowdhery; Denny Zhou (ICLR, 2023)

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. - Denny Zhou; Nathanael Schärli; Le Hou; Jason Wei; Nathan Scales; Xuezhi Wang 002; Dale Schuurmans; Claire Cui; Olivier Bousquet; Quoc V. Le; Ed H. Chi (ICLR, 2023)

Large Language Models Can Be Easily Distracted by Irrelevant Context. - Freda Shi; Xinyun Chen; Kanishka Misra; Nathan Scales; David Dohan; Ed H. Chi; Nathanael Schärli; Denny Zhou (ICML, 2023)

Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). - Yin Zhang 011; Ruoxi Wang; Derek Zhiyuan Cheng; Tiansheng Yao; Xinyang Yi; Lichan Hong; James Caverlee; Ed H. Chi (KDD, 2023)

Foundations and Applications in Large-scale AI Models: Pre-training, Fine-tuning, and Prompt-based Learning. - Derek Zhiyuan Cheng; Dhaval Patel 002; Linsey Pang; Sameep Mehta; Kexin Xie; Ed H. Chi; Wei Liu 007; Nitesh V. Chawla; James Bailey 001 (KDD, 2023)

Improving Training Stability for Multitask Ranking Models in Recommender Systems. - Jiaxi Tang; Yoel Drori; Daryl Chang; Maheswaran Sathiamoorthy; Justin Gilmer; Li Wei; Xinyang Yi; Lichan Hong; Ed H. Chi (KDD, 2023)

Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. - Jianling Wang; Haokai Lu; Sai Zhang; Bart N. Locanthi; Haoting Wang; Dylan Greaves; Benjamin Lipshitz; Sriraj Badam; Ed H. Chi; Cristos J. Goodrow; Su-Lin Wu; Lexi Baugher; et al. (KDD, 2023)

Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. - Benjamin Coleman; Wang-Cheng Kang; Matthew Fahrbach; Ruoxi Wang; Lichan Hong; Ed H. Chi; Derek Zhiyuan Cheng (NeurIPS, 2023)

Recommender Systems with Generative Retrieval. - Shashank Rajput; Nikhil Mehta 002; Anima Singh; Raghunandan Hulikal Keshavan; Trung Vu 002; Lukasz Heldt; Lichan Hong; Yi Tay; Vinh Q. Tran 002; Jonah Samost; Maciej Kula; Ed H. Chi; et al. (NeurIPS, 2023)

Efficient Data Representation Learning in Google-scale Systems. - Derek Zhiyuan Cheng; Ruoxi Wang; Wang-Cheng Kang; Benjamin Coleman; Yin Zhang 011; Jianmo Ni; Jonathan Valverde; Lichan Hong; Ed H. Chi (RecSys, 2023)

Online Matching: A Real-time Bandit System for Large-scale Recommendations. - Xinyang Yi; Shao-Chuan Wang; Ruining He; Hariharan Chandrasekaran; Charles Wu; Lukasz Heldt; Lichan Hong; Minmin Chen; Ed H. Chi (RecSys, 2023)

What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. - Yao Qin 001; Xuezhi Wang 002; Balaji Lakshminarayanan; Ed H. Chi; Alex Beutel (SaTML, 2023)

HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. - Kaize Ding; Albert Jiongqian Liang; Bryan Perozzi; Ting Chen; Ruoxi Wang; Lichan Hong; Ed H. Chi; Huan Liu 001; Derek Zhiyuan Cheng (SIGIR, 2023)

Latent User Intent Modeling for Sequential Recommenders. - Bo Chang 002; Alexandros Karatzoglou; Yuyan Wang; Can Xu; Ed H. Chi; Minmin Chen (WWW (Companion Volume), 2023)

Investigating Action-Space Generalization in Reinforcement Learning for Recommendation Systems. - Abhishek Naik; Bo Chang 002; Alexandros Karatzoglou; Martin Mladenov; Ed H. Chi; Minmin Chen (WWW (Companion Volume), 2023)

Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. - Wang-Cheng Kang; Jianmo Ni; Nikhil Mehta 002; Maheswaran Sathiamoorthy; Lichan Hong; Ed H. Chi; Derek Zhiyuan Cheng (CoRR, 2023)

Value of Exploration: Measurements, Findings and Algorithms. - Yi Su 008; Xiangyu Wang; Elaine Ya Le; Liang Liu 017; Yuening Li; Haokai Lu; Benjamin Lipshitz; Sriraj Badam; Lukasz Heldt; Shuchao Bi; Ed H. Chi; Cristos Goodrow; et al. (CoRR, 2023)

Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals. - Ananth Balashankar; Xuezhi Wang 002; Yao Qin 001; Ben Packer; Nithum Thain; Jilin Chen; Ed H. Chi; Alex Beutel (CoRR, 2023)

Large Language Models for User Interest Journeys. - Konstantina Christakopoulou; Alberto Lalama; Cj Adams; Iris Qu; Yifat Amir; Samer Chucri; Pierce Vollucci; Fabio Soldo; Dina Bseiso; Sarah Scodel; Lucas Dixon; Ed H. Chi; et al. (CoRR, 2023)

Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations. - Pan Li; Yuyan Wang; Ed H. Chi; Minmin Chen (CoRR, 2023)

Hierarchical Reinforcement Learning for Modeling User Novelty-Seeking Intent in Recommender Systems. - Pan Li; Yuyan Wang; Ed H. Chi; Minmin Chen (CoRR, 2023)

Better Generalization with Semantic IDs: A case study in Ranking for Recommendations. - Anima Singh; Trung Vu 002; Raghunandan H. Keshavan; Nikhil Mehta 002; Xinyang Yi; Lichan Hong; Lukasz Heldt; Li Wei; Ed H. Chi; Maheswaran Sathiamoorthy (CoRR, 2023)

Density Weighting for Multi-Interest Personalized Recommendation. - Nikhil Mehta 002; Anima Singh; Xinyang Yi; Sagar Jain; Lichan Hong; Ed H. Chi (CoRR, 2023)

Talking Models: Distill Pre-trained Knowledge to Downstream Models via Interactive Communication. - Zhe Zhao 001; Qingyun Liu 003; Huan Gui; Bang An; Lichan Hong; Ed H. Chi (CoRR, 2023)

Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems. - Huan Gui; Ruoxi Wang; Ke Yin; Long Jin; Maciej Kula; Taibai Xu; Lichan Hong; Ed H. Chi (CoRR, 2023)

Leveraging LLM Reasoning Enhances Personalized Recommender Systems. - Alicia Tsai; Adam Kraft; Long Jin; Chenwei Cai; Anahita Hosseini; Taibai Xu; Zemin Zhang; Lichan Hong; Ed Huai-hsin Chi; Xinyang Yi (ACL (Findings), 2024)

Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses. - Xiao Ma 010; Swaroop Mishra; Ariel Liu; Sophie Ying Su; Jilin Chen; Chinmay Kulkarni 001; Heng-Tze Cheng; Quoc V. Le; Ed H. Chi (CHI Extended Abstracts, 2024)

Large Language Models as Analogical Reasoners. - Michihiro Yasunaga; Xinyun Chen; Yujia Li; Panupong Pasupat; Jure Leskovec; Percy Liang; Ed H. Chi; Denny Zhou (ICLR, 2024)

Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models. - Huaixiu Steven Zheng; Swaroop Mishra; Xinyun Chen; Heng-Tze Cheng; Ed H. Chi; Quoc V. Le; Denny Zhou (ICLR, 2024)

LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views. - Yuji Roh; Qingyun Liu 003; Huan Gui; Zhe Yuan; Yujin Tang; Steven Euijong Whang; Liang Liu 017; Shuchao Bi; Lichan Hong; Ed H. Chi; Zhe Zhao 001 (ICML, 2024)

Multi-Task Neural Linear Bandit for Exploration in Recommender Systems. - Yi Su 008; Haokai Lu; Yuening Li; Liang Liu 017; Shuchao Bi; Ed H. Chi; Minmin Chen (KDD, 2024)

Aligning Large Language Models with Recommendation Knowledge. - Yuwei Cao; Nikhil Mehta 002; Xinyang Yi; Raghunandan Hulikal Keshavan; Lukasz Heldt; Lichan Hong; Ed H. Chi; Maheswaran Sathiamoorthy (NAACL-HLT (Findings), 2024)

SELF-DISCOVER: Large Language Models Self-Compose Reasoning Structures. - Pei Zhou; Jay Pujara; Xiang Ren 001; Xinyun Chen; Heng-Tze Cheng; Quoc V. Le; Ed H. Chi; Denny Zhou; Swaroop Mishra; Huaixiu Steven Zheng (NeurIPS, 2024)

Self-Auxiliary Distillation for Sample Efficient Learning in Google-Scale Recommenders. - Yin Zhang 011; Ruoxi Wang; Xiang Li; Tiansheng Yao; Andrew Evdokimov; Jonathan Valverde; Yuan Gao; Jerry Zhang; Evan Ettinger; Ed H. Chi; Derek Zhiyuan Cheng (RecSys, 2024)

Bridging the Gap: Unpacking the Hidden Challenges in Knowledge Distillation for Online Ranking Systems. - Nikhil Khani; Li Wei; Aniruddh Nath; Shawn Andrews; Shuo Yang; Yang Liu 136; Pendo Abbo; Maciej Kula; Jarrod Kahn; Zhe Zhao 001; Lichan Hong; Ed H. Chi (RecSys, 2024)

Short-form Video Needs Long-term Interests: An Industrial Solution for Serving Large User Sequence Models. - Yuening Li; Diego Uribe; Chuan He; Jiaxi Tang; Qingyun Liu 003; Junjie Shan; Ben Most; Kaushik Kalyan; Shuchao Bi; Xinyang Yi; Lichan Hong; Ed H. Chi; et al. (RecSys, 2024)

Improving Data Efficiency for Recommenders and LLMs. - Noveen Sachdeva; Benjamin Coleman; Wang-Cheng Kang; Jianmo Ni; James Caverlee; Lichan Hong; Ed H. Chi; Derek Zhiyuan Cheng (RecSys, 2024)

Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations. - Anima Singh; Trung Vu 002; Nikhil Mehta 002; Raghunandan H. Keshavan; Maheswaran Sathiamoorthy; Yilin Zheng; Lichan Hong; Lukasz Heldt; Li Wei; Devansh Tandon; Ed H. Chi; Xinyang Yi (RecSys, 2024)

LLMs for User Interest Exploration in Large-scale Recommendation Systems. - Jianling Wang; Haokai Lu; Yifan Liu; He Ma; Yueqi Wang; Yang Gu; Shuzhou Zhang; Ningren Han; Shuchao Bi; Lexi Baugher; Ed H. Chi; Minmin Chen (RecSys, 2024)

Co-optimize Content Generation and Consumption in a Large Scale Video Recommendation System. - Zhen Zhang; Qingyun Liu 003; Yuening Li; Sourabh Bansod; Mingyan Gao; Yaping Zhang; Zhe Zhao 001; Lichan Hong; Ed H. Chi; Shuchao Bi; Liang Liu 017 (RecSys, 2024)

Long-Term Value of Exploration: Measurements, Findings and Algorithms. - Yi Su 008; Xiangyu Wang; Elaine Ya Le; Liang Liu 017; Yuening Li; Haokai Lu; Benjamin Lipshitz; Sriraj Badam; Lukasz Heldt; Shuchao Bi; Ed H. Chi; Cristos Goodrow; et al. (WSDM, 2024)

Cluster Anchor Regularization to Alleviate Popularity Bias in Recommender Systems. - Bo Chang 002; Changping Meng; He Ma; Shuo Chang; Yang Gu; Yajun Peng; Jingchen Feng; Yaping Zhang; Shuchao Bi; Ed H. Chi; Minmin Chen (WWW (Companion Volume), 2024)

Large Language Models as Data Augmenters for Cold-Start Item Recommendation. - Jianling Wang; Haokai Lu; James Caverlee; Ed H. Chi; Minmin Chen (WWW (Companion Volume), 2024)

How to Train Data-Efficient LLMs. - Noveen Sachdeva; Benjamin Coleman; Wang-Cheng Kang; Jianmo Ni; Lichan Hong; Ed H. Chi; James Caverlee; Julian J. McAuley; Derek Zhiyuan Cheng (CoRR, 2024)

Wisdom of Committee: Distilling from Foundation Model to Specialized Application Model. - Zichang Liu; Qingyun Liu 003; Yuening Li; Liang Liu 017; Anshumali Shrivastava; Shuchao Bi; Lichan Hong; Ed H. Chi; Zhe Zhao 001 (CoRR, 2024)

Diversifying by Intent in Recommender Systems. - Yuyan Wang; Cheenar Banerjee; Samer Chucri; Fabio Soldo; Sriraj Badam; Ed H. Chi; Minmin Chen (CoRR, 2024)

LLMs for User Interest Exploration: A Hybrid Approach. - Jianling Wang; Haokai Lu; Yifan Liu; He Ma; Yueqi Wang; Yang Gu; Shuzhou Zhang; Ningren Han; Shuchao Bi; Lexi Baugher; Ed H. Chi; Minmin Chen (CoRR, 2024)

NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. - Huaixiu Steven Zheng; Swaroop Mishra; Hugh Zhang; Xinyun Chen; Minmin Chen; Azade Nova; Le Hou; Heng-Tze Cheng; Quoc V. Le; Ed H. Chi; Denny Zhou (CoRR, 2024)

Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries. - Kiran Vodrahalli; Santiago Ontanon; Nilesh Tripuraneni; Kelvin Xu; Sanil Jain; Rakesh Shivanna; Jeffrey Hui; Nishanth Dikkala; Mehran Kazemi; Bahare Fatemi; Rohan Anil; Ethan Dyer; et al. (CoRR, 2024)

EVOLvE: Evaluating and Optimizing LLMs For Exploration. - Allen Nie; Yi Su 008; Bo Chang 002; Jonathan N. Lee; Ed H. Chi; Quoc V. Le; Minmin Chen (CoRR, 2024)

STAR: A Simple Training-free Approach for Recommendations using Large Language Models. - Dong-Ho Lee; Adam Kraft; Long Jin; Nikhil Mehta 002; Taibai Xu; Lichan Hong; Ed H. Chi; Xinyang Yi (CoRR, 2024)

Scaling Instruction-Finetuned Language Models. - Hyung Won Chung; Le Hou; Shayne Longpre; Barret Zoph; Yi Tay; William Fedus; Yunxuan Li; Xuezhi Wang 002; Mostafa Dehghani 001; Siddhartha Brahma; Albert Webson; Shixiang Shane Gu; et al. (J. Mach. Learn. Res., 2024)

Beyond Item Dissimilarities: Diversifying by Intent in Recommender Systems. - Yuyan Wang; Cheenar Banerjee; Samer Chucri; Fabio Soldo; Sriraj Badam; Ed H. Chi; Minmin Chen (KDD (1), 2025)

ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation. - Yupeng Hou; Jianmo Ni; Zhankui He; Noveen Sachdeva; Wang-Cheng Kang; Ed H. Chi; Julian J. McAuley; Derek Zhiyuan Cheng (CoRR, 2025)

User Feedback Alignment for LLM-powered Exploration in Large-scale Recommendation Systems. - Jianling Wang; Yifan Liu; Yinghao Sun; Xuejian Ma; Yueqi Wang; He Ma; Zhengyang Su; Minmin Chen; Mingyan Gao; Onkar Dalal; Ed H. Chi; Lichan Hong; et al. (CoRR, 2025)

Serendipitous Recommendation with Multimodal LLM. - Haoting Wang; Jianling Wang; Hao Li; Fangjun Yi; Mengyu Fu; Youwei Zhang; Yifan Liu; Liang Liu 017; Minmin Chen; Ed H. Chi; Lichan Hong; Haokai Lu (CoRR, 2025)

ReMem: Mutual Information-Aware Fine-tuning of Pretrained Vision Transformers for Effective Knowledge Distillation. - Chengyu Dong; Huan Gui; Noveen Sachdeva; Long Jin; Ke Yin; Jingbo Shang; Lichan Hong; Ed H. Chi; Zhe Zhao 001 (CoRR, 2025)