Michelle S. Lam

34 papers A* 8Journal 19Unranked 7
YearRankTypeTitle / Venue / Authors
2026 A* conf
Just-In-Time Objectives: A General Approach for Specialized AI Interactions.
CHI
Michelle S. Lam, Omar Shaikh, Hallie Xu, Alice Guo, Diyi Yang, Jeffrey Heer, James A. Landay, Michael S. Bernstein
2025 A* conf
Aligning Language Models with Demonstrated Feedback.
ICLR
Omar Shaikh, Michelle S. Lam, Joey Hejna, Yijia Shao, Hyundong Justin Cho, Michael S. Bernstein, Diyi Yang
2025 J jnl
Attention to Non-Adopters.
CoRR
Kaitlyn Zhou, Kristina Gligoric, Myra Cheng, Michelle S. Lam, Vyoma Raman, Boluwatife Aminu, Caeley Woo, Michael Brockman, Hannah Cha, Dan Jurafsky
2025 J jnl
Designing LLM Chains by Adapting Techniques from Crowdsourcing Workflows.
ACM Trans. Comput. Hum. Interact.
Madeleine Grunde-McLaughlin, Michelle S. Lam, Ranjay Krishna, Daniel S. Weld, Jeffrey Heer
2025 — conf
Human-Centered Evaluation and Auditing of Language Models.
CHI Extended Abstracts
Yu Lu Liu, Wesley Hanwen Deng, Michelle S. Lam, Motahhare Eslami, Juho Kim, Q. Vera Liao, Wei Xu, Jekaterina Novikova, Ziang Xiao
2025 J jnl
Just-In-Time Objectives: A General Approach for Specialized AI Interactions.
CoRR
Michelle S. Lam, Omar Shaikh, Hallie Xu, Alice Guo, Diyi Yang, Jeffrey Heer, James A. Landay, Michael S. Bernstein
2025 A* conf
Policy Maps: Tools for Guiding the Unbounded Space of LLM Behaviors.
UIST
Michelle S. Lam, Fred Hohman, Dominik Moritz, Jeffrey P. Bigham, Kenneth Holstein, Mary Beth Kery
2025 — conf
Refractor: Steerable Live Clustering for Speaker-Audience Understanding.
UIST Adjunct
Poonam Sahoo, Michelle S. Lam, Michael S. Bernstein
2024 J jnl
AI Policy Projector: Grounding LLM Policy Design in Iterative Mapmaking.
CoRR
Michelle S. Lam, Fred Hohman, Dominik Moritz, Jeffrey P. Bigham, Kenneth Holstein, Mary Beth Kery
2024 A* conf
Clarify: Improving Model Robustness With Natural Language Corrections.
UIST
Yoonho Lee, Michelle S. Lam, Helena Vasconcelos, Michael S. Bernstein, Chelsea Finn
2024 J jnl
Clarify: Improving Model Robustness With Natural Language Corrections.
CoRR
Yoonho Lee, Michelle S. Lam, Helena Vasconcelos, Michael S. Bernstein, Chelsea Finn
2024 A* conf
Concept Induction: Analyzing Unstructured Text with High-Level Concepts Using LLooM.
CHI
Michelle S. Lam, Janice Teoh, James A. Landay, Jeffrey Heer, Michael S. Bernstein
2024 J jnl
Concept Induction: Analyzing Unstructured Text with High-Level Concepts Using LLooM.
CoRR
Michelle S. Lam, Janice Teoh, James A. Landay, Jeffrey Heer, Michael S. Bernstein
2024 J jnl
Embedding Democratic Values into Social Media AIs via Societal Objective Functions.
Proc. ACM Hum. Comput. Interact.
Chenyan Jia, Michelle S. Lam, Minh Chau Mai, Jeffrey T. Hancock, Michael S. Bernstein
2024 — conf
Granting Non-AI Experts Creative Control Over AI Systems.
UIST (Adjunct Volume)
Michelle S. Lam
2024 — conf
Human-Centered Evaluation and Auditing of Language Models.
CHI Extended Abstracts
Ziang Xiao, Wesley Hanwen Deng, Michelle S. Lam, Motahhare Eslami, Juho Kim, Mina Lee, Q. Vera Liao
2024 J jnl
Show, Don't Tell: Aligning Language Models with Demonstrated Feedback.
CoRR
Omar Shaikh, Michelle S. Lam, Joey Hejna, Yijia Shao, Michael S. Bernstein, Diyi Yang
2023 J jnl
Designing LLM Chains by Adapting Techniques from Crowdsourcing Workflows.
CoRR
Madeleine Grunde-McLaughlin, Michelle S. Lam, Ranjay Krishna, Daniel S. Weld, Jeffrey Heer
2023 J jnl
Embedding Democratic Values into Social Media AIs via Societal Objective Functions.
CoRR
Chenyan Jia, Michelle S. Lam, Minh Chau Mai, Jeff T. Hancock, Michael S. Bernstein
2023 A* conf
Model Sketching: Centering Concepts in Early-Stage Machine Learning Model Design.
CHI
Michelle S. Lam, Zixian Ma, Anne Li, Izequiel Freitas, Dakuo Wang, James A. Landay, Michael S. Bernstein
2023 J jnl
Model Sketching: Centering Concepts in Early-Stage Machine Learning Model Design.
CoRR
Michelle S. Lam, Zixian Ma, Anne Li, Izequiel Freitas, Dakuo Wang, James A. Landay, Michael S. Bernstein
2023 J jnl
Sociotechnical Audits: Broadening the Algorithm Auditing Lens to Investigate Targeted Advertising.
CoRR
Michelle S. Lam, Ayush Pandit, Colin H. Kalicki, Rachit Gupta, Poonam Sahoo, Danaë Metaxa
2023 J jnl
Sociotechnical Audits: Broadening the Algorithm Auditing Lens to Investigate Targeted Advertising.
Proc. ACM Hum. Comput. Interact.
Michelle S. Lam, Ayush Pandit, Colin H. Kalicki, Rachit Gupta, Poonam Sahoo, Danaë Metaxa
2023 — conf
Supporting User Engagement in Testing, Auditing, and Contesting AI.
CSCW Companion
Wesley Hanwen Deng, Michelle S. Lam, Ángel Alexander Cabrera, Danaë Metaxa, Motahhare Eslami, Kenneth Holstein
2022 J jnl
End-User Audits: A System Empowering Communities to Lead Large-Scale Investigations of Harmful Algorithmic Behavior.
Proc. ACM Hum. Comput. Interact.
Michelle S. Lam, Mitchell L. Gordon, Danaë Metaxa, Jeffrey T. Hancock, James A. Landay, Michael S. Bernstein
2022 A* conf
Jury Learning: Integrating Dissenting Voices into Machine Learning Models.
CHI
Mitchell L. Gordon, Michelle S. Lam, Joon Sung Park, Kayur Patel, Jeffrey T. Hancock, Tatsunori Hashimoto, Michael S. Bernstein
2022 J jnl
Jury Learning: Integrating Dissenting Voices into Machine Learning Models.
CoRR
Mitchell L. Gordon, Michelle S. Lam, Joon Sung Park, Kayur Patel, Jeffrey T. Hancock, Tatsunori Hashimoto, Michael S. Bernstein
2021 J jnl
Fairness On The Ground: Applying Algorithmic Fairness Approaches to Production Systems.
CoRR
Chloé Bakalar, Renata Barreto, Stevie Bergman, Miranda Bogen, Bobbie Chern, Sam Corbett-Davies, Melissa Hall, Isabel Kloumann, Michelle S. Lam, Joaquin Quiñonero Candela, Manish Raghavan, Joshua Simons, Jonathan Tannen, Edmund Tong, Kate Vredenburgh, Jiejing Zhao
2019 — conf
Eevee: Transforming Images by Bridging High-level Goals and Low-level Edit Operations.
CHI Extended Abstracts
Michelle S. Lam, Grace B. Young, Catherine Y. Xu, Ranjay Krishna, Michael S. Bernstein
2018 J jnl
Amanuensis: The Programmer's Apprentice.
CoRR
Thomas Dean, Maurice Chiang, Marcus Gomez, Nate Gruver, Yousef Hindy, Michelle S. Lam, Peter Lu, Sophia Sanchez, Rohun Saxena, Michael Smith, Lucy Wang, Catherine Wong
2018 — conf
Power Networks: A Novel Neural Architecture to Predict Power Relations.
LaTeCH@COLING
Michelle S. Lam, Catherina Xu, Vinodkumar Prabhakaran
2018 J jnl
Power Networks: A Novel Neural Architecture to Predict Power Relations.
CoRR
Michelle S. Lam, Catherina Xu, Angela Kong, Vinodkumar Prabhakaran
2016 A* conf
Atelier: Repurposing Expert Crowdsourcing Tasks as Micro-internships.
CHI
Ryo Suzuki, Niloufar Salehi, Michelle S. Lam, Juan C. Marroquin, Michael S. Bernstein
2016 J jnl
Atelier: Repurposing Expert Crowdsourcing Tasks as Micro-internships.
CoRR
Ryo Suzuki, Niloufar Salehi, Michelle S. Lam, Juan C. Marroquin, Michael S. Bernstein