PlateClick: Bootstrapping Food Preferences Through an Adaptive Visual Interface. - Longqi Yang 001; Yin Cui; Fan Zhang 022; John P. Pollak; Serge J. Belongie; Deborah Estrin (CIKM, 2015)

Beyond Classification: Latent User Interests Profiling from Visual Contents Analysis. - Longqi Yang 001; Cheng-Kang Hsieh; Deborah Estrin (ICDM Workshops, 2015)

GroupLink: Group Event Recommendations Using Personal Digital Traces. - Honghao Wei; Cheng-Kang Hsieh; Longqi Yang 001; Deborah Estrin (CSCW Companion, 2016)

Your activities of daily living (YADL): an image-based survey technique for patients with arthritis. - Longqi Yang 001; Diana Freed; Alex Wu; Judy Wu; John P. Pollak; Deborah Estrin (PervasiveHealth, 2016)

Immersive Recommendation: News and Event Recommendations Using Personal Digital Traces. - Cheng-Kang Hsieh; Longqi Yang 001; Honghao Wei; Mor Naaman; Deborah Estrin (WWW, 2016)

Yum-me: Personalized Healthy Meal Recommender System. - Longqi Yang 001; Cheng-Kang Hsieh; Hongjian Yang; Nicola Dell; Serge J. Belongie; Deborah Estrin (CoRR, 2016)

Leveraging Multi-Modal Sensing for Mobile Health: A Case Review in Chronic Pain. - Min S. Hane Aung; Faisal Alquaddoomi; Cheng-Kang Hsieh; Mashfiqui Rabbi; Longqi Yang 001; John P. Pollak; Deborah Estrin; Tanzeem Choudhury (IEEE J. Sel. Top. Signal Process., 2016)

Collaborative Metric Learning. - Cheng-Kang Hsieh; Longqi Yang 001; Yin Cui; Tsung-Yi Lin; Serge J. Belongie; Deborah Estrin (WWW, 2017)

Personalizing Software and Web Services by Integrating Unstructured Application Usage Traces. - Longqi Yang 001; Chen Fang; Hailin Jin; Matthew D. Hoffman; Deborah Estrin (WWW (Companion Volume), 2017)

Yum-Me: A Personalized Nutrient-Based Meal Recommender System. - Longqi Yang 001; Cheng-Kang Hsieh; Hongjian Yang; John P. Pollak; Nicola Dell; Serge J. Belongie; Curtis L. Cole; Deborah Estrin (ACM Trans. Inf. Syst., 2017)

Exploring recommendations under user-controlled data filtering. - Hongyi Wen; Longqi Yang 001; Michael Sobolev; Deborah Estrin (RecSys, 2018)

Modularizing deep neural network-inspired recommendation algorithms. - Longqi Yang 001; Eugene Bagdasaryan; Hongyi Wen (RecSys, 2018)

Unbiased offline recommender evaluation for missing-not-at-random implicit feedback. - Longqi Yang 001; Yin Cui; Yuan Xuan; Chenyang Wang; Serge J. Belongie; Deborah Estrin (RecSys, 2018)

Understanding user interactions with podcast recommendations delivered via voice. - Longqi Yang 001; Michael Sobolev; Christina Tsangouri; Deborah Estrin (RecSys, 2018)

OpenRec: A Modular Framework for Extensible and Adaptable Recommendation Algorithms. - Longqi Yang 001; Eugene Bagdasaryan; Joshua Gruenstein; Cheng-Kang Hsieh; Deborah Estrin (WSDM, 2018)

Characterizing User Skills from Application Usage Traces with Hierarchical Attention Recurrent Networks. - Longqi Yang 001; Chen Fang; Hailin Jin; Matthew D. Hoffman; Deborah Estrin (ACM Trans. Intell. Syst. Technol., 2018)

Leveraging post-click feedback for content recommendations. - Hongyi Wen; Longqi Yang 001; Deborah Estrin (RecSys, 2019)

More Than Just Words: Modeling Non-Textual Characteristics of Podcasts. - Longqi Yang 001; Yu Wang; Drew Dunne; Michael Sobolev; Mor Naaman; Deborah Estrin (WSDM, 2019)

RecBoard: A Web-based Platform for Recommendation System Research and Development. - Mohit Chawla; Kriti Singh; Longqi Yang 001; Deborah Estrin (WWW, 2019)

How Intention Informed Recommendations Modulate Choices: A Field Study of Spoken Word Content. - Longqi Yang 001; Michael Sobolev; Yu Wang; Jenny Chen; Drew Dunne; Christina Tsangouri; Nicola Dell; Mor Naaman; Deborah Estrin (WWW, 2019)

Creative Procedural-Knowledge Extraction From Web Design Tutorials. - Longqi Yang 001; Chen Fang; Hailin Jin; Walter Chang; Deborah Estrin (CoRR, 2019)

User-centric Recommendation Systems. - Longqi Yang 001 (2019)

How Work From Home Affects Collaboration: A Large-Scale Study of Information Workers in a Natural Experiment During COVID-19. - Longqi Yang 001; Sonia Jaffe; David Holtz; Siddharth Suri; Shilpi Sinha; Jeffrey Weston; Connor Joyce; Neha Shah; Kevin Sherman; Chia-Jung Lee; Brent J. Hecht; Jaime Teevan (CoRR, 2020)

Large Scale Analysis of Multitasking Behavior During Remote Meetings. - Hancheng Cao; Chia-Jung Lee; Shamsi T. Iqbal; Mary Czerwinski; Priscilla N. Y. Wong; Sean Rintel; Brent J. Hecht; Jaime Teevan; Longqi Yang 001 (CHI, 2021)

Learning to Represent Human Motives for Goal-directed Web Browsing. - Jyun-Yu Jiang; Chia-Jung Lee; Longqi Yang 001; Bahareh Sarrafzadeh; Brent J. Hecht; Jaime Teevan (RecSys, 2021)

Local Factor Models for Large-Scale Inductive Recommendation. - Longqi Yang 001; Tobias Schnabel; Paul N. Bennett; Susan T. Dumais (RecSys, 2021)

Learning Causal Effects on Hypergraphs. - Jing Ma 002; Mengting Wan; Longqi Yang 001; Jundong Li; Brent J. Hecht; Jaime Teevan (KDD, 2022)

RecWork: Workshop on Recommender Systems for the Future of Work. - Joseph A. Konstan; Ajith Muralidharan; Ankan Saha; Shilad Sen; Mengting Wan; Longqi Yang 001 (RecSys, 2022)

Learning Fair Node Representations with Graph Counterfactual Fairness. - Jing Ma 002; Ruocheng Guo; Mengting Wan; Longqi Yang 001; Aidong Zhang; Jundong Li (WSDM, 2022)

Lightweight Compositional Embeddings for Incremental Streaming Recommendation. - Mengyue Hang; Tobias Schnabel; Longqi Yang 001; Jennifer Neville (CoRR, 2022)

Situating Recommender Systems in Practice: Towards Inductive Learning and Incremental Updates. - Tobias Schnabel; Mengting Wan; Longqi Yang 001 (CoRR, 2022)

Learning Causal Effects on Hypergraphs (Extended Abstract). - Jing Ma 002; Mengting Wan; Longqi Yang 001; Jundong Li; Brent J. Hecht; Jaime Teevan (IJCAI, 2023)

Workplace Recommendation with Temporal Network Objectives. - Kiran Tomlinson; Jennifer Neville; Longqi Yang 001; Mengting Wan; Cao Lu (KDD, 2023)

Large-Scale Analysis of New Employee Network Dynamics. - Yulin Yu; Longqi Yang 001; Siân Lindley; Mengting Wan (WWW, 2023)

Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies. - Chirag Shah 001; Ryen W. White; Reid Andersen; Georg Buscher; Scott Counts; Sarkar Snigdha Sarathi Das; Ali Montazer; Sathish Manivannan; Jennifer Neville; Xiaochuan Ni 001; Nagu Rangan; Tara Safavi; et al. (CoRR, 2023)

PEARL: Personalizing Large Language Model Writing Assistants with Generation-Calibrated Retrievers. - Sheshera Mysore; Zhuoran Lu; Mengting Wan; Longqi Yang 001; Steve Menezes; Tina Baghaee; Emmanuel Barajas Gonzalez; Jennifer Neville; Tara Safavi (CoRR, 2023)

Causal Effect Estimation under Interference on Hypergraphs. - Jing Ma 002; Mengting Wan; Longqi Yang 001; Jundong Li; Brent J. Hecht; Jaime Teevan (AI Matters, 2023)

Targeted Training for Multi-organization Recommendation. - Kiran Tomlinson; Mengting Wan; Cao Lu; Brent J. Hecht; Jaime Teevan; Longqi Yang 001 (Trans. Recomm. Syst., 2023)

S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs. - Sarkar Snigdha Sarathi Das; Chirag Shah 001; Mengting Wan; Jennifer Neville; Longqi Yang 001; Reid Andersen; Georg Buscher; Tara Safavi (ACL (Findings), 2024)

Interpretable User Satisfaction Estimation for Conversational Systems with Large Language Models. - Ying-Chun Lin; Jennifer Neville; Jack W. Stokes; Longqi Yang 001; Tara Safavi; Mengting Wan; Scott Counts; Siddharth Suri; Reid Andersen; Xiaofeng Xu; Deepak Gupta; Sujay Kumar Jauhar; et al. (ACL (1), 2024)

TnT-LLM: Text Mining at Scale with Large Language Models. - Mengting Wan; Tara Safavi; Sujay Kumar Jauhar; Yujin Kim; Scott Counts; Jennifer Neville; Siddharth Suri; Chirag Shah 001; Ryen W. White; Longqi Yang 001; Reid Andersen; Georg Buscher; et al. (KDD, 2024)

The Use of Generative Search Engines for Knowledge Work and Complex Tasks. - Siddharth Suri; Scott Counts; Leijie Wang; Chacha Chen; Mengting Wan; Tara Safavi; Jennifer Neville; Chirag Shah 001; Ryen W. White; Reid Andersen; Georg Buscher; Sathish Manivannan; et al. (CoRR, 2024)

Corporate Communication Companion (CCC): An LLM-empowered Writing Assistant for Workplace Social Media. - Zhuoran Lu; Sheshera Mysore; Tara Safavi; Jennifer Neville; Longqi Yang 001; Mengting Wan (CoRR, 2024)

WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback. - Taiwei Shi; Zhuoer Wang; Longqi Yang 001; Ying-Chun Lin; Zexue He; Mengting Wan; Pei Zhou; Sujay Kumar Jauhar; Xiaofeng Xu; Xia Song; Jennifer Neville (CoRR, 2024)

GenTool: Enhancing Tool Generalization in Language Models through Zero-to-One and Weak-to-Strong Simulation. - Jie He 004; Jennifer Neville; Mengting Wan; Longqi Yang 001; Hui Liu; Xiaofeng Xu; Xia Song; Jeff Z. Pan; Pei Zhou (ACL (Findings), 2025)

Leveraging Large Language Models for Collective Decision-Making. - Marios Papachristou; Longqi Yang 001; Chin-Chia Hsu 001 (Proc. ACM Hum. Comput. Interact., 2025)

Group Preference Alignment: Customized LLM Response Generation from In-Situ Conversations. - Ishani Mondal; Jack W. Stokes; Sujay Kumar Jauhar; Longqi Yang 001; Mengting Wan; Xiaofeng Xu; Xia Song; Jennifer Neville (CoRR, 2025)

Teaching Language Models To Gather Information Proactively. - Tenghao Huang; Sihao Chen; Muhao Chen 001; Jonathan May; Longqi Yang 001; Mengting Wan; Pei Zhou (CoRR, 2025)

Using Large Language Models to Generate, Validate, and Apply User Intent Taxonomies. - Chirag Shah 001; Ryen White; Reid Andersen; Georg Buscher; Scott Counts; Sarkar Snigdha Sarathi Das; Ali Montazer; Sathish Manivannan; Jennifer Neville; Nagu Rangan; Tara Safavi; Siddharth Suri; et al. (ACM Trans. Web, 2025)