Eric Frankel
Hello! I'm a second year Ph.D. student at the University of Washington, where I am co-advised by Sewoong Oh and Lillian Ratliff.
I am fortunate to be supported by the NSF Graduate Research Fellowship.
I am currently on leave and a Member of Technical Staff at Treeline AI.
Previously, I graduated from Stanford University with a B.S. with Honors in Mathematics and a M.S. in Statistics, advised by Emmanuel Candès.
I was also affiliated with the Stanford AI Lab and worked with Chelsea Finn and Ehsan Adeli.
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ericsf [at] cs [dot] washington [dot] edu
2025
Two papers accepted to ICML 20252024
Workshop paper at NeurIPS 2024 Statistical Frontiers in LLMs and Foundation ModelsOpenThoughts: Data Recipes for Reasoning Models
Etash Guha*, Ryan Marten*, ..., Eric Frankel, ..., et al.
International Conference on Learning Representations (ICLR) 2026 (Oral)
PDF
S4S: Solving for a Diffusion Model Solver
Eric Frankel, Sitan Chen, Jerry Li, Pang Wei Koh, Lillian J. Ratliff, Sewoong Oh
International Conference on Machine Learning (ICML) 2025
PDF
Finite-Time Convergence Rates in Stochastic Stackelberg Games with Smooth Algorithmic Agents
Eric Frankel, Kshitij Kulkarni, Dmitriy Drusvyatskiy, Sewoong Oh, Lillian J. Ratliff
International Conference on Machine Learning (ICML) 2025
PDF •
Code
Conformal Reasoning: Uncertainty Estimation in Interactive Environments
Eric Frankel, Shuyue Stella Li, Lillian J. Ratliff, Yulia Tsvetkov, Sewoong Oh, Pang Wei Koh
NeurIPS 2024 Workshop on Statistical Frontiers in LLMs and Foundation Models
PDF
JRDB: A Dataset and Benchmark of Egocentric Robot Visual Perception of Humans in Built Environments
Roberto Martín-Martín, Mihir Patel, Hamid Rezatofighi, Abhijeet Shenoi, Eric Frankel, JunYoung Gwak, Amir Sadeghian, Silvio Savarese
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) 2023
PDF •
Webpage
2026
Frontiers of Flows for Generative AI, CMU — "S4S: Solving for a Diffusion Model Solver"2026
Reviewer for COLM 20262023
Course Assistant, CS 230: Deep Learning, Stanford University2023
Course Assistant, CS 224N: NLP with Deep Learning, Stanford University2022
Course Assistant, CS 330: Deep Multi-Task and Meta Learning, Stanford University