Eric Zelikman

According to our database, Eric Zelikman authored at least 24 papers between 2018 and 2024.

Collaborative distances:

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

2024

Certified Deductive Reasoning with Language Models.

Gabriel Poesia, Kanishk Gandhi, Eric Zelikman, Noah D. Goodman

Trans. Mach. Learn. Res., 2024

Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference Labels.

Jan-Philipp Fränken, Eric Zelikman, Rafael Rafailov, Kanishk Gandhi, Tobias Gerstenberg, Noah D. Goodman

CoRR, 2024

Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking.

Eric Zelikman, Georges Harik, Yijia Shao, Varuna Jayasiri, Nick Haber, Noah D. Goodman

CoRR, 2024

Hypothesis Search: Inductive Reasoning with Language Models.

Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber, Noah D. Goodman

Proceedings of the Twelfth International Conference on Learning Representations, 2024

ContextRef: Evaluating Referenceless Metrics for Image Description Generation.

Elisa Kreiss, Eric Zelikman, Christopher Potts, Nick Haber

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Holistic Evaluation of Language Models.

Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda

Trans. Mach. Learn. Res., 2023

Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation.

Eric Zelikman, Eliana Lorch, Lester Mackey, Adam Tauman Kalai

CoRR, 2023

SkyGPT: Probabilistic Short-term Solar Forecasting Using Synthetic Sky Videos from Physics-constrained VideoGPT.

Yuhao Nie, Eric Zelikman, Andea Scott, Quentin Paletta, Adam Brandt

CoRR, 2023

Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized Language Model Finetuning Using Shared Randomness.

Eric Zelikman, Qian Huang, Percy Liang, Nick Haber, Noah D. Goodman

CoRR, 2023

Certified Reasoning with Language Models.

Gabriel Poesia, Kanishk Gandhi, Eric Zelikman, Noah D. Goodman

CoRR, 2023

Lexinvariant Language Models.

Qian Huang, Eric Zelikman, Sarah Li Chen, Yuhuai Wu, Gregory Valiant, Percy Liang

CoRR, 2023

Parsel🦆: Algorithmic Reasoning with Language Models by Composing Decompositions.

Eric Zelikman, Qian Huang, Gabriel Poesia, Noah D. Goodman, Nick Haber

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

Lexinvariant Language Models.

Qian Huang, Eric Zelikman, Sarah Chen, Yuhuai Wu, Gregory Valiant, Percy Liang

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

Generating and Evaluating Tests for K-12 Students with Language Model Simulations: A Case Study on Sentence Reading Efficiency.

Eric Zelikman, Wanjing Anya Ma, Jasmine E. Tran, Diyi Yang, Jason D. Yeatman, Nick Haber

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

Parsel: A Unified Natural Language Framework for Algorithmic Reasoning.

Eric Zelikman, Qian Huang, Gabriel Poesia, Noah D. Goodman, Nick Haber

CoRR, 2022

STaR: Bootstrapping Reasoning With Reasoning.

Eric Zelikman, Yuhuai Wu, Noah D. Goodman

CoRR, 2022

STaR: Bootstrapping Reasoning With Reasoning.

Eric Zelikman, Yuhuai Wu, Jesse Mu, Noah D. Goodman

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Context Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metrics.

Elisa Kreiss, Cynthia L. Bennett, Shayan Hooshmand, Eric Zelikman, Meredith Ringel Morris, Christopher Potts

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology.

Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Gunnar E. Carlsson, Stefano Ermon

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

2020

Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models.

Eric Zelikman, Sharon Zhou, Jeremy Irvin, Cooper Raterink, Hao Sheng, Jack Kelly, Ram Rajagopal, Andrew Y. Ng, David Gagne

CoRR, 2020

Evaluating the Disentanglement of Deep Generative Models through Manifold Topology.

Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Stefano Ermon

CoRR, 2020

Improving Regression Uncertainty Estimates with an Empirical Prior.

Eric Zelikman, Christopher Healy

CoRR, 2020

Learning as Reinforcement: Applying Principles of Neuroscience for More General Reinforcement Learning Agents.

Eric Zelikman, William Yin, Kenneth Wang

CoRR, 2020

2018

Context is Everything: Finding Meaning Statistically in Semantic Spaces.

Eric Zelikman

CoRR, 2018