Nathan Lambert

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 21

Top Topics

Reinforcement Learning

Eligibility Traces

Partially Observable Environments

Top Venues

Publications

Prasann Singhal, Nathan Lambert, Scott Niekum, Tanya Goyal, Greg Durrett
D2PO: Discriminator-Guided DPO with Response Evaluation Models. CoRR (2024)
Alon Albalak, Yanai Elazar, Sang Michael Xie, Shayne Longpre, Nathan Lambert, Xinyi Wang, Niklas Muennighoff, Bairu Hou, Liangming Pan, Haewon Jeong, Colin Raffel, Shiyu Chang, Tatsunori Hashimoto, William Yang Wang
A Survey on Data Selection for Language Models. CoRR (2024)
Dirk Groeneveld, Iz Beltagy, Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi
OLMo: Accelerating the Science of Language Models. CoRR (2024)
Nathan Lambert, Valentina Pyatkin, Jacob Morrison, LJ Miranda, Bill Yuchen Lin, Khyathi Raghavi Chandu, Nouha Dziri, Sachin Kumar, Tom Zick, Yejin Choi, Noah A. Smith, Hannaneh Hajishirzi
RewardBench: Evaluating Reward Models for Language Modeling. CoRR (2024)
Adrien Basdevant, Camille François, Victor Storchan, Kevin Bankston, Ayah Bdeir, Brian Behlendorf, Mérouane Debbah, Sayash Kapoor, Yann LeCun, Mark Surman, Helen King-Turvey, Nathan Lambert, Stefano Maffulli, Nik Marda, Govind Shivkumar, Justine Tunney
Towards a Framework for Openness in Foundation Models: Proceedings from the Columbia Convening on Openness in Artificial Intelligence. CoRR (2024)
Vincent Conitzer, Rachel Freedman, Jobst Heitzig, Wesley H. Holliday, Bob M. Jacobs, Nathan Lambert, Milan Mossé, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, Emanuel Tewolde, William S. Zwicker
Social Choice for AI Alignment: Dealing with Diverse Human Feedback. CoRR (2024)
Hamish Ivison, Yizhong Wang, Jiacheng Liu, Zeqiu Wu, Valentina Pyatkin, Nathan Lambert, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi
Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback. CoRR (2024)
Seungju Han, Kavel Rao, Allyson Ettinger, Liwei Jiang, Bill Yuchen Lin, Nathan Lambert, Yejin Choi, Nouha Dziri
WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs. CoRR (2024)
Luca Soldaini, Rodney Kinney, Akshita Bhagia, Dustin Schwenk, David Atkinson, Russell Authur, Ben Bogin, Khyathi Chandu, Jennifer Dumas, Yanai Elazar, Valentin Hofmann, Ananya Harsh Jha, Sachin Kumar, Li Lucy, Xinxi Lyu, Nathan Lambert, Ian Magnusson, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Abhilasha Ravichander, Kyle Richardson, Zejiang Shen, Emma Strubell, Nishant Subramani, Oyvind Tafjord, Pete Walsh, Luke Zettlemoyer, Noah A. Smith, Hannaneh Hajishirzi, Iz Beltagy, Dirk Groeneveld, Jesse Dodge, Kyle Lo
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. CoRR (2024)
Sarah Shoker, Andrew Reddie, Sarah Barrington, Ruby Booth, Miles Brundage, Husanjot Chahal, Michael Depp, Bill Drexel, Ritwik Gupta, Marina Favaro, Jake Hecla, Alan Hickey, Margarita Konaev, Kirthi Kumar, Nathan Lambert, Andrew Lohn, Cullen O'Keefe, Nazneen Rajani, Michael Sellitto, Robert Trager, Leah Walker, Alexa Wehsener, Jessica Young
Confidence-Building Measures for Artificial Intelligence: Workshop Proceedings. CoRR (2023)
Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, Nathan Sarrazin, Omar Sanseviero, Alexander M. Rush, Thomas Wolf
Zephyr: Direct Distillation of LM Alignment. CoRR (2023)
Thomas Krendl Gilbert, Nathan Lambert, Sarah Dean, Tom Zick, Aaron J. Snoswell, Soham Mehta
Reward Reports for Reinforcement Learning. AIES (2023)
Nathan Lambert, Thomas Krendl Gilbert, Tom Zick
Entangled Preferences: The History and Risks of Reinforcement Learning and Human Feedback. CoRR (2023)
Hamish Ivison, Yizhong Wang, Valentina Pyatkin, Nathan Lambert, Matthew Peters, Pradeep Dasigi, Joel Jang, David Wadden, Noah A. Smith, Iz Beltagy, Hannaneh Hajishirzi
Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2. CoRR (2023)
Thomas Krendl Gilbert, Sarah Dean, Tom Zick, Nathan Lambert
Choices, Risks, and Reward Reports: Charting Public Policy for Reinforcement Learning Systems. CoRR (2022)
Margaret Mitchell, Alexandra Sasha Luccioni, Nathan Lambert, Marissa Gerchick, Angelina McMillan-Major, Ezinwanne Ozoani, Nazneen Rajani, Tristan Thrush, Yacine Jernite, Douwe Kiela
Measuring Data. CoRR (2022)
Thomas Krendl Gilbert, Sarah Dean, Nathan Lambert, Tom Zick, Aaron J. Snoswell
Reward Reports for Reinforcement Learning. CoRR (2022)
Nathan Lambert, Markus Wulfmeier, William F. Whitney, Arunkumar Byravan, Michael Bloesch, Vibhavari Dasagi, Tim Hertweck, Martin A. Riedmiller
The Challenges of Exploration for Offline Reinforcement Learning. CoRR (2022)
Sarah Dean, Thomas Krendl Gilbert, Nathan Lambert, Tom Zick
Axes for Sociotechnical Inquiry in AI Research. CoRR (2021)
McKane Andrus, Sarah Dean, Thomas Krendl Gilbert, Nathan Lambert, Tom Zick
AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks. CoRR (2021)
McKane Andrus, Sarah Dean, Thomas Krendl Gilbert, Nathan Lambert, Tom Zick
AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks. ISTAS (2020)
Braden Simpson, Eirini Kalliamvakou, Nathan Lambert, Daniela E. Damian
Aduno: Real-time collaborative work design in a shared workspace. CHASE@ICSE (2013)