What You See Is What You Get? The Impact of Representation Criteria on Human Bias in Hiring. - Andi Peng; Besmira Nushi; Emre Kiciman; Kori Inkpen; Siddharth Suri; Ece Kamar (HCOMP, 2019)

Human-Machine Collaboration for Fast Land Cover Mapping. - Caleb Robinson; Anthony Ortiz; Kolya Malkin; Blake Elias; Andi Peng; Dan Morris 001; Bistra Dilkina; Nebojsa Jojic (AAAI, 2020)

The Perils of Objectivity: Towards a Normative Framework for Fair Judicial Decision-Making. - Andi Peng; Malina Simard-Halm (AIES, 2020)

Investigations of Performance and Bias in Human-AI Teamwork in Hiring. - Andi Peng; Besmira Nushi; Emre Kiciman; Kori Inkpen; Ece Kamar (AAAI, 2022)

Strengthening Subcommunities: Towards Sustainable Growth in AI Research. - Andi Peng; Jessica Zosa Forde; Yonadav Shavit; Jonathan Frankle (CoRR, 2022)

Aligning Robot Representations with Humans. - Andreea Bobu; Andi Peng (CoRR, 2022)

Diagnosis, Feedback, Adaptation: A Human-in-the-Loop Framework for Test-Time Policy Adaptation. - Andi Peng; Aviv Netanyahu; Mark K. Ho; Tianmin Shu; Andreea Bobu; Julie Shah; Pulkit Agrawal 001 (ICML, 2023)

Human-Guided Complexity-Controlled Abstractions. - Andi Peng; Mycal Tucker; Eoin M. Kenny; Noga Zaslavsky; Pulkit Agrawal 001; Julie A. Shah (NeurIPS, 2023)

Aligning Robot and Human Representations. - Andreea Bobu; Andi Peng; Pulkit Agrawal 001; Julie Shah; Anca D. Dragan (CoRR, 2023)

Getting aligned on representational alignment. - Ilia Sucholutsky; Lukas Muttenthaler; Adrian Weller; Andi Peng; Andreea Bobu; Been Kim; Bradley C. Love; Erin Grant; Jascha Achterberg; Joshua B. Tenenbaum; Katherine M. Collins; Katherine L. Hermann; et al. (CoRR, 2023)

Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. - Stephen Casper; Xander Davies; Claudia Shi; Thomas Krendl Gilbert; Jérémy Scheurer; Javier Rando; Rachel Freedman; Tomasz Korbak; David Lindner; Pedro Freire; Tony Tong Wang; Samuel Marks; et al. (Trans. Mach. Learn. Res., 2023)

Adaptive Language-Guided Abstraction from Contrastive Explanations. - Andi Peng; Belinda Z. Li; Ilia Sucholutsky; Nishanth Kumar; Julie Shah; Jacob Andreas; Andreea Bobu (CoRL, 2024)

Aligning Human and Robot Representations. - Andreea Bobu; Andi Peng; Pulkit Agrawal 001; Julie A. Shah; Anca D. Dragan (HRI, 2024)

Preference-Conditioned Language-Guided Abstraction. - Andi Peng; Andreea Bobu; Belinda Z. Li; Theodore R. Sumers; Ilia Sucholutsky; Nishanth Kumar; Thomas L. Griffiths 001; Julie A. Shah (HRI, 2024)

Learning with Language-Guided State Abstractions. - Andi Peng; Ilia Sucholutsky; Belinda Z. Li; Theodore R. Sumers; Thomas L. Griffiths 001; Jacob Andreas; Julie Shah (ICLR, 2024)

Pragmatic Feature Preferences: Learning Reward-Relevant Preferences from Human Input. - Andi Peng; Yuying Sun; Tianmin Shu; David Abel (ICML, 2024)

Constrained Human-AI Cooperation: An Inclusive Embodied Social Intelligence Challenge. - Weihua Du; Qiushi Lyu; Jiaming Shan; Zhenting Qi; Hongxin Zhang; Sunli Chen; Andi Peng; Tianmin Shu; Kwonjoon Lee; Behzad Dariush; Chuang Gan 001 (NeurIPS, 2024)

The Future of Open Human Feedback. - Shachar Don-Yehiya; Ben Burtenshaw; Ramón Fernandez Astudillo; Cailean Osborne; Mimansa Jaiswal; Tzu-Sheng Kuo; Wenting Zhao; Idan Shenfeld; Andi Peng; Mikhail Yurochkin; Atoosa Kasirzadeh; Yangsibo Huang; et al. (CoRR, 2024)

Learning How Hard to Think: Input-Adaptive Allocation of LM Computation. - Mehul Damani; Idan Shenfeld; Andi Peng; Andreea Bobu; Jacob Andreas (ICLR, 2025)