Reliable and Responsible Foundation Models: A Comprehensive Survey

Xinyu Yang, Junlin Han, Rishi Bommasani +49

Economic Evaluations of Language Models

Alexander Wan, Stephane Hatgis-Kessell, Tomás Aguirre +2

NeurIPS should lead scientific consensus on AI policy

Rishi Bommasani

Language model developers should report train-test overlap

Andy K Zhang, Kevin Klyman, Yifan Mai +4

Data Governance in the Age of Large-Scale Data-Driven Language Technology

Yacine Jernite, Huu Nguyen, Stella Biderman +18

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

BigScience Workshop, :, Teven Le Scao +391

STREAM (ChemBio): A Standard for Transparently Reporting Evaluations in AI Model Reports

Tegan McCaslin, Jide Alaga, Samira Nedungadi +5

A Safe Harbor for AI Evaluation and Red Teaming

Shayne Longpre, Sayash Kapoor, Kevin Klyman +20

Beyond Release: Access Considerations for Generative AI Systems

Irene Solaiman, Rishi Bommasani, Dan Hendrycks +4

The California Report on Frontier AI Policy

Rishi Bommasani, Scott R. Singer, Ruth E. Appel +20

Frontier AI Auditing: Toward Rigorous Third-Party Assessment of Safety and Security Practices at Leading AI Companies

Miles Brundage, Noemi Dreksler, Aidan Homewood +45

Toward an Evaluation Science for Generative AI Systems

Laura Weidinger, Inioluwa Deborah Raji, Hanna Wallach +7

The Societal Impact of Foundation Models: Advancing Evidence-based AI Policy

Rishi Bommasani

Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation

Sayash Kapoor, Benedikt Stroebl, Peter Kirgis +28

Evaluation for Change

Rishi Bommasani

International AI Safety Report 2026

Yoshua Bengio, Stephen Clare, Carina Prunkl +89

Legal Alignment for Safe and Ethical AI

Noam Kolt, Nicholas Caputo, Jack Boeglin +14

Ecosystem Graphs: The Social Footprint of Foundation Models

Rishi Bommasani, Dilara Soylu, Thomas I. Liao +2

Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization?

Rishi Bommasani, Kathleen A. Creel, Ananya Kumar +2

Effective Mitigations for Systemic Risks from General-Purpose AI

Risto Uuk, Annemieke Brouwer, Tim Schreier +3

Algorithmic Monocultures in Hiring

Rishi Bommasani, Sarah H. Bana, Kathleen A. Creel +2

In-House Evaluation Is Not Enough: Towards Robust Third-Party Flaw Disclosure for General-Purpose AI

Shayne Longpre, Kevin Klyman, Ruth E. Appel +31

International AI Safety Report

Yoshua Bengio, Sören Mindermann, Daniel Privitera +93

Evaluating Human-Language Model Interaction

Mina Lee, Megha Srivastava, Amelia Hardy +15

The 2025 Foundation Model Transparency Index

Alexander Wan, Kevin Klyman, Sayash Kapoor +5

The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources

Shayne Longpre, Stella Biderman, Alon Albalak +20

The Jagged Global Economy: Frontier AI Unevenly Exposes National Economies

Arul Murugan, Tomás Aguirre, Abhishek Nagaraj +1

AISPA: User-Centric System Prompt Auditing for Large Language Model Applications

Xiangning Lin, Shenzhe Zhu, Shu Yang +23

The paper presents AISPA, a user‑centric framework for auditing the system prompts that guide large language model behavior in commercial AI products, and reports findings from ana…

Trustworthy Social Bias Measurement

Rishi Bommasani, Percy Liang

Advancing Science- and Evidence-based AI Policy

Rishi Bommasani, Sanjeev Arora, Jennifer Chayes +17

Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs

Deepak Narayanan, Keshav Santhanam, Peter Henderson +3

Open-World Evaluations for Measuring Frontier AI Capabilities

Sayash Kapoor, Peter Kirgis, Andrew Schwartz +15

The Limits of AI Data Transparency Policy: Three Disclosure Fallacies

Judy Hanwen Shen, Ken Liu, Angelina Wang +7

Generalized Optimal Linear Orders

Rishi Bommasani

Disclosure and Evaluation as Fairness Interventions for General-Purpose AI

Vyoma Raman, Judy Hanwen Shen, Andy K. Zhang +4

International Scientific Report on the Safety of Advanced AI (Interim Report)

Yoshua Bengio, Sören Mindermann, Daniel Privitera +41

On the Societal Impact of Open Foundation Models

Sayash Kapoor, Rishi Bommasani, Kevin Klyman +22

The 2024 Foundation Model Transparency Index

Rishi Bommasani, Kevin Klyman, Sayash Kapoor +4

The Reality of AI and Biorisk

Aidan Peppin, Anka Reuel, Stephen Casper +10

FLARE-AI: Flaw Reporting for AI

Shayne Longpre, Elaine Zhu, Carson Ezell +15

On the Opportunities and Risks of Foundation Models

Rishi Bommasani, Drew A. Hudson, Ehsan Adeli +111

Can AI agents conduct open-ended AI research? Early evidence from two case studies

Peter Kirgis, Sayash Kapoor, Andrew Schwartz +21

The paper evaluates whether current AI agents can independently conduct open‑ended AI research by having them attempt to solve the central questions of two unpublished NeurIPS subm…

Do AI Companies Make Good on Voluntary Commitments to the White House?

Jennifer Wang, Kayla Huang, Kevin Klyman +1

Foundation Model Transparency Reports

Rishi Bommasani, Kevin Klyman, Shayne Longpre +5

The Foundation Model Transparency Index

Rishi Bommasani, Kevin Klyman, Shayne Longpre +5

Holistic Evaluation of Language Models

Percy Liang, Rishi Bommasani, Tony Lee +47

Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes

Connor Toups, Rishi Bommasani, Kathleen A. Creel +3

Emergent Abilities of Large Language Models

Jason Wei, Yi Tay, Rishi Bommasani +13