Jeffrey Li

According to our database, Jeffrey Li authored at least 18 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Language Models Improve When Pretraining Data Matches Target Tasks.

David Mizrahi, Anders Boesen Lindbo Larsen, Jesse Allardice, Suzie Petryk, Yuri Gorokhov, Jeffrey Li, Alex Fang, Josh Gardner, Tom Gunter, Afshin Dehghan

CoRR, July, 2025

OpenThoughts: Data Recipes for Reasoning Models.

Etash Kumar Guha, Ryan Marten, Sedrick Keh, Negin Raoof, Georgios Smyrnis, Hritik Bansal, Marianna Nezhurina, Jean Mercat, Trung Vu, Zayne Sprague, Ashima Suvarna, Benjamin Feuer, Liangyu Chen, Zaid Khan, Eric Frankel, Sachin Grover, Caroline Choi, Niklas Muennighoff, Shiye Su, Wanjia Zhao, John Yang, Shreyas Pimpalgaonkar, Kartik Sharma, Charlie Cheng-Jie Ji, Yichuan Deng, Sarah M. Pratt, Vivek Ramanujan, Jon Saad-Falcon, Jeffrey Li, Achal Dave, Alon Albalak, Kushal Arora, Blake Wulfe, Chinmay Hegde, Greg Durrett, Sewoong Oh, Mohit Bansal, Saadia Gabriel, Aditya Grover, Kai-Wei Chang, Vaishaal Shankar, Aaron Gokaslan, Mike A. Merrill, Tatsunori Hashimoto, Yejin Choi, Jenia Jitsev, Reinhard Heckel, Maheswaran Sathiamoorthy, Alexandros G. Dimakis, Ludwig Schmidt

CoRR, June, 2025

Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks.

Tianyi Zhang, Linrong Cai, Jeffrey Li, Nicholas Roberts, Neel Guha, Jinoh Lee, Frederic Sala

CoRR, January, 2025

Language models scale reliably with over-training and on downstream tasks.

Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Luca Soldaini, Jenia Jitsev, Alex Dimakis, Gabriel Ilharco, Pang Wei Koh, Shuran Song, Thomas Kollar, et al.

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Identifying Effective Praise in Tutoring: Large Language Models with Transparent Explanations.

Eason Chen, Jeffrey Li, Scarlett Huang, Xinyi Tang, Jionghao Lin, Paulo Carvalho, Kenneth R. Koedinger

Proceedings of the Artificial Intelligence in Education - 26th International Conference, 2025

TiC-LM: A Web-Scale Benchmark for Time-Continual LLM Pretraining.

Jeffrey Li, Mohammadreza Armandpour, Iman Mirzadeh, Sachin Mehta, Vaishaal Shankar, Raviteja Vemulapalli, Samy Bengio, Oncel Tuzel, Mehrdad Farajtabar, Hadi Pouransari, Fartash Faghri

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

CODA: an open-source platform for federated analysis and machine learning on distributed healthcare data.

Louis Mullie, Jonathan Afilalo, Patrick M. Archambault, Rima Bouchakri, Kip Brown, David L. Buckeridge, Yiorgos Alexandros Cavayas, Alexis F. Turgeon, Denis Martineau, François Lamontagne, Martine Lebrasseur, Renald Lemieux, Jeffrey Li, Michaël Sauthier, Pascal St-Onge, An Tang, William Witteman, Michael Chassé

J. Am. Medical Informatics Assoc., February, 2024

SDS - See it, Do it, Sorted: Quadruped Skill Synthesis from Single Video Demonstration.

Jeffrey Li, Maria Stamatopoulou, Dimitrios Kanoulas

CoRR, 2024

Language models scale reliably with over-training and on downstream tasks.

Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Jenia Jitsev, Alexandros G. Dimakis, Gabriel Ilharco, Shuran Song, Thomas Kollar, Yair Carmon, Achal Dave, Reinhard Heckel, Niklas Muennighoff, Ludwig Schmidt

CoRR, 2024

Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks.

Tianyi Zhang, Linrong Cai, Jeffrey Li, Nicholas Roberts, Neel Guha, Frederic Sala

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

DataComp-LM: In search of the next generation of training sets for language models.

Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Scott Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alex Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Better Alignment with Instruction Back-and-Forth Translation.

Thao Nguyen, Jeffrey Li, Sewoong Oh, Ludwig Schmidt, Jason Weston, Luke Zettlemoyer, Xian Li

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023

Characterizing the Impacts of Semi-supervised Learning for Weak Supervision.

Jeffrey Li, Jieyu Zhang, Ludwig Schmidt, Alexander J. Ratner

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021

Interpretable Machine Learning: Moving from mythos to diagnostics.

Valerie Chen, Jeffrey Li, Joon Sik Kim, Gregory Plumb, Ameet Talwalkar

ACM Queue, 2021

Towards Connecting Use Cases and Methods in Interpretable Machine Learning.

Valerie Chen, Jeffrey Li, Joon Sik Kim, Gregory Plumb, Ameet Talwalkar

CoRR, 2021

A Learning Theoretic Perspective on Local Explainability.

Jeffrey Li, Vaishnavh Nagarajan, Gregory Plumb, Ameet Talwalkar

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Differentially Private Meta-Learning.

Jeffrey Li, Mikhail Khodak, Sebastian Caldas, Ameet Talwalkar

Proceedings of the 8th International Conference on Learning Representations, 2020

2017

An Advanced Private Social Activity Invitation Framework with Friendship Protection.

Weitian Tong, Lei Chen, Scott Buglass, Weinan Gao, Jeffrey Li

Wirel. Commun. Mob. Comput., 2017