Flow Surface Probes for Vector Field Visualization. - Cláudio T. Silva; Lichan Hong; Arie E. Kaufman (Scientific Visualization, 1994)

VolVis: A Diversified Volume Visualization System. - Ricardo S. Avila; Taosong He; Lichan Hong; Arie E. Kaufman; Hanspeter Pfister; Cláudio T. Silva; Lisa M. Sobierajski; Sidney W. Wang (IEEE Visualization, 1994)

Voxel Based Object Simplification. - Taosong He; Lichan Hong; Arie E. Kaufman; Amitabh Varshney; Sidney W. Wang (IEEE Visualization, 1995)

Interactive Visualization of Mixed Scalar and Vector Fields. - Lichan Hong; Xiaoyang Mao; Arie E. Kaufman (IEEE Visualization, 1995)

Splatting of Curvilinear Volumes. - Xiaoyang Mao; Lichan Hong; Arie E. Kaufman (IEEE Visualization, 1995)

Generation of Transfer Functions with Stochastic Search Techniques. - Taosong He; Lichan Hong; Arie E. Kaufman; Hanspeter Pfister (IEEE Visualization, 1996)

Controlled Topology Simplification. - Taosong He; Lichan Hong; Amitabh Varshney; Sidney W. Wang (IEEE Trans. Vis. Comput. Graph., 1996)

Notes on Computational-space-based Ray-casting for Curvilinear Volumes. - Lichan Hong; Arie E. Kaufman (Scientific Visualization, 1997)

Virtual voyage: interactive navigation in the human colon. - Lichan Hong; Shigeru Muraki; Arie E. Kaufman; Dirk Bartz; Taosong He (SIGGRAPH, 1997)

Interactive volume rendering for virtual colonoscopy. - Suya You; Lichan Hong; Ming Wan; Kittiboon Junyaprasert; Arie E. Kaufman; Shigeru Muraki; Yong Zhou 001; Mark Wax; Zhengrong Liang (IEEE Visualization, 1997)

Multi-Granularity Noise for Curvilinear Grid LIC. - Xiaoyang Mao; Lichan Hong; Arie E. Kaufman; Noboru Fujita; Makoto Kikukawa; Atsumi Imamiya (Graphics Interface, 1998)

Accelerated ray-casting for curvilinear volumes. - Lichan Hong; Arie E. Kaufman (IEEE Visualization, 1998)

Fast Projection-Based Ray-Casting Algorithm for Rendering Curvilinear Volumes. - Lichan Hong; Arie E. Kaufman (IEEE Trans. Vis. Comput. Graph., 1999)

Reliable Path for Virtual Endoscopy: Ensuring Complete Examination of Human Organs. - Taosong He; Lichan Hong; Dongqing Chen; Zhengrong Liang (IEEE Trans. Vis. Comput. Graph., 2001)

Automatic Centerline Extraction for Virtual Colonoscopy. - Ming Wan; Zhengrong Liang; Qi Ke; Lichan Hong; Ingmar Bitter; Arie E. Kaufman (IEEE Trans. Medical Imaging, 2002)

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)

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)

Turning Pages of 3D Electronic Books. - Lichan Hong; Stuart K. Card; Jindong Chen (3DUI, 2006)

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

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

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)

Remembrance of things tagged: how tagging effort affects tag production and human memory. - Raluca Budiu; Peter Pirolli; Lichan Hong (CHI, 2009)

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

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)

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)

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

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)

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)

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

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

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)

Wide & Deep Learning for Recommender Systems. - Heng-Tze Cheng; Levent Koc 001; Jeremiah Harmsen; Tal Shaked; Tushar Chandra; Hrishi Aradhye; Glen Anderson; Greg Corrado; Wei Chai; Mustafa Ispir; Rohan Anil; Zakaria Haque; et al. (DLRS@RecSys, 2016)

TensorFlow Estimators: Managing Simplicity vs. Flexibility in High-Level Machine Learning Frameworks. - Heng-Tze Cheng; Zakaria Haque; Lichan Hong; Mustafa Ispir; Clemens Mewald; Illia Polosukhin; Georgios Roumpos; D. Sculley; Jamie Smith; David Soergel; Yuan Tang; Philipp Tucker; et al. (KDD, 2017)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)