HELM Lite: Lightweight and Broad Capabilities Evaluation Percy Liang, Yifan Mai, Josselin Somerville, Farzaan Kaiyom, Tony Lee, Rishi Bommasani
[Blog]
Considerations for Governing Open Foundation Models Rishi Bommasani, Sayash Kapoor, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Daniel Zhang, Marietje Schaake, Daniel E. Ho, Arvind Narayanan, Percy Liang
[Policy Brief]
Towards Compromise: A Concrete Two-tier Proposal for Foundation Models in the EU AI Act Rishi Bommasani, Tatsunori Hashimoto, Daniel E. Ho, Marietje Schaake, Percy Liang
[Policy Brief]
Drawing Lines: Tiers for Foundation Models Rishi Bommasani
[Policy Brief]
AI Regulation Has Its Own Alignment Problem: The Technical and Institutional Feasibility of Disclosure, Registration, Licensing, and Auditing Neel Guha*, Christie M. Lawrence*, Lindsey A. Gailmard, Kit T. Rodolfa, Faiz Surani, Rishi Bommasani, Inioluwa Deborah Raji, Mariano-Florentino Cuéllar, Colleen Honigsberg, Percy Liang, Daniel E. Ho
George Washington Law Review 2024 [Paper][Policy Brief]
By the Numbers: Tracking The AI Executive Order Caroline Meinhardt, Christie M. Lawrence, Lindsey A. Gailmard, Daniel Zhang, Rishi Bommasani, Rohini Kosoglu, Peter Henderson, Russell Wald, Daniel E. Ho
[Blog][Tracker]
Decoding the White House AI Executive Order’s Achievements Rishi Bommasani, Christie M. Lawrence, Lindsey A. Gailmard, Caroline Meinhardt, Daniel Zhang, Peter Henderson, Russell Wald, Daniel E. Ho
[Blog]
What the Executive Order means for Openness in AI Arvind Narayanan, Sayash Kapoor, Rishi Bommasani
[Blog]
Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes Connor Toups*, Rishi Bommasani*, Kathleen A. Creel, Sarah Bana, Dan Jurafsky, Percy Liang
NeurIPS 2023 [Paper][Code] [HAI]
Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani, Tony Lee, Percy Liang
NeurIPS 2023 [Paper]
Do Foundation Model Providers Comply with the Draft EU AI Act? Rishi Bommasani, Kevin Klyman, Daniel Zhang, Marietje Schaake, Percy Liang
[Policy Brief]
Stanford-Princeton Response to the US NTIA Request for Comment on AI Accountability Rishi Bommasani, Sayash Kapoor, Daniel Zhang, Arvind Narayanan, Percy Liang
[Policy Brief]
Ecosystem Graphs: The Social Footprint of Foundation Models Rishi Bommasani, Dilara Soylu, Thomas I. Liao, Kathleen A. Creel, Percy Liang
[Paper][Website][Blog][Code] [HAI]
AI Spring? Four Takeaways from Major Releases in Foundation Models Rishi Bommasani
[Blog]
Improving Transparency in AI Language Models: A Holistic Evaluation Rishi Bommasani, Daniel Zhang, Tony Lee, Percy Liang
[Policy Brief]
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang
NeurIPS 2022 [Paper][Code]
Data Governance in the Age of Large-Scale Data-Driven Language Technology Yacine Jernite, Huu Nguyen, full list of authors, Rishi Bommasani, Margaret Mitchell
FAccT 2022 [Paper]
The Time Is Now to Develop Community Norms for the Release of Foundation Models Percy Liang, Rishi Bommasani, Kathleen A. Creel, Rob Reich
[Blog] [HAI][Protocol]
Mistral — A Journey towards Reproducible Language Model Training Siddharth Karamcheti*, Laurel Orr*, Jason Bolton, Tianyi Zhang, Karan Goel, Avanika Narayan, Rishi Bommasani, Deepak Narayanan, Tatsunori Hashimoto, Dan Jurafsky, Christopher D. Manning, Christopher Potts, Christopher Ré, Percy Liang
[Blog][Code]
Generalized Optimal Linear Orders Rishi Bommasani
Committee: Claire Cardie (Chair), Robert Kleinberg
M.S. Thesis, Cornell University [arXiv] [Thesis][Slides]