Arvind Narayanan

Full Professor, Princeton University

Joined

June 2019

Names

Arvind Narayanan

Emails

****@princeton.edu (Confirmed)

****@cs.princeton.edu (Confirmed)

Personal Links

Career & Education History

Full Professor

Princeton University (princeton.edu)

2022 – Present

Associate Professor

Princeton University (princeton.edu)

2018 – 2022

Assistant Professor

Princeton University (princeton.edu)

2012 – 2018

Visitor

Microsoft (microsoft.com)

2017 – 2017

Advisors, Relations & Conflicts

PhD Advisor

Vitaly Shmatikov

Present

Expertise

ethics of computing

Present

fairness in machine learning

Present

societal impacts of AI

Present

Publications

Localized Cultural Knowledge is Conserved and Controllable in Large Language Models
Veniamin Veselovsky, Berke Argın, Benedikt Stroebl, Chris Wendler, Robert West, James Evans, Thomas L. Griffiths, Arvind Narayanan
- ICLR 2026 Conference Withdrawn Submission
- Readers: Everyone
The Limits of Inference Scaling Through Resampling
Benedikt Stroebl, Sayash Kapoor, Arvind Narayanan
- ICLR 2026 Poster
- Readers: Everyone
Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent Evaluation
Sayash Kapoor, Benedikt Stroebl, Peter Kirgis, Nitya Nadgir, Zachary S Siegel, Boyi Wei, Tianci Xue, Ziru Chen, Felix Chen, Saiteja Utpala, Franck Ndzomga, Dheeraj Oruganty, Sophie Luskin, Kangheng Liu, Botao Yu, Amit Arora, Dongyoon Hahm, Harsh Trivedi, Huan Sun, Juyong Lee et al. (11 additional authors not shown)
- ICLR 2026 Poster
- Readers: Everyone
In-House Evaluation Is Not Enough: Towards Robust Third-Party Flaw Disclosure for General-Purpose AI
Shayne Longpre, Kevin Klyman, Ruth E. Appel, Sayash Kapoor, Rishi Bommasani, Michelle Sahar, Sean McGregor, Avijit Ghosh, Borhane Blili-Hamelin, Nathan Butters, Alondra Nelson, Dr. Amit Elazari, Andrew Sellars, Casey John Ellis, Dane Sherrets, Dawn Song, Harley Geiger, Ilona Cohen, Lauren McIlvenny, Madhulika Srikumar et al. (14 additional authors not shown)
- ICML 2025 Workshop TAIG Poster
- Readers: Everyone
Establishing Best Practices in Building Rigorous Agentic Benchmarks
Yuxuan Zhu, Tengjun Jin, Yada Pruksachatkun, Andy K Zhang, Shu Liu, Sasha Cui, Sayash Kapoor, Shayne Longpre, Kevin Meng, Rebecca Weiss, Fazl Barez, Rahul Gupta, Jwala Dhamala, Jacob Merizian, Mario Giulianelli, Harry Coppock, Cozmin Ududec, Antony Kellermann, Jasjeet S Sekhon, Jacob Steinhardt et al. (6 additional authors not shown)
- NeurIPS 2025 Datasets and Benchmarks Track poster
- Readers: Everyone
Hindsight Merging: Diverse Data Generation with Language Models
Veniamin Veselovsky, Benedikt Stroebl, Gianluca Bencomo, Dilip Arumugam, Lisa Schut, Arvind Narayanan, Thomas L. Griffiths
- UAI 2025 Poster
- Readers: Everyone
Inference Scaling fLaws: The Limits of LLM Resampling with Imperfect Verifiers
Benedikt Stroebl, Sayash Kapoor, Arvind Narayanan
- Preprint (arxiv)
- Readers: Everyone
Position: In-House Evaluation Is Not Enough. Towards Robust Third-Party Evaluation and Flaw Disclosure for General-Purpose AI
Shayne Longpre, Kevin Klyman, Ruth Elisabeth Appel, Sayash Kapoor, Rishi Bommasani, Michelle Sahar, Sean McGregor, Avijit Ghosh, Borhane Blili-Hamelin, Nathan Butters, Alondra Nelson, Dr. Amit Elazari, Andrew Sellars, Casey John Ellis, Dane Sherrets, Dawn Song, Harley Geiger, Ilona Cohen, Lauren McIlvenny, Madhulika Srikumar et al. (14 additional authors not shown)
- ICML 2025 Position Paper Track spotlightposter
- Readers: Everyone
AI Agents That Matter
Sayash Kapoor, Benedikt Stroebl, Zachary S Siegel, Nitya Nadgir, Arvind Narayanan
- Accepted by TMLR
- Readers: Everyone
CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark
Zachary S Siegel, Sayash Kapoor, Nitya Nadgir, Benedikt Stroebl, Arvind Narayanan
- Accepted by TMLR
- Readers: Everyone

View all 14 publications

Co-Authors

View all 127 co-authors