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Eric Zelikman
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2020 – today
- 2024
- [j2]Gabriel Poesia, Kanishk Gandhi, Eric Zelikman, Noah D. Goodman:
Certified Deductive Reasoning with Language Models. Trans. Mach. Learn. Res. 2024 (2024) - [c8]Elisa Kreiss, Eric Zelikman, Christopher Potts, Nick Haber:
ContextRef: Evaluating Referenceless Metrics for Image Description Generation. ICLR 2024 - [c7]Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber, Noah D. Goodman:
Hypothesis Search: Inductive Reasoning with Language Models. ICLR 2024 - [i19]Eric Zelikman, Georges Harik, Yijia Shao, Varuna Jayasiri, Nick Haber, Noah D. Goodman:
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking. CoRR abs/2403.09629 (2024) - [i18]Jan-Philipp Fränken, Eric Zelikman, Rafael Rafailov, Kanishk Gandhi, Tobias Gerstenberg, Noah D. Goodman:
Self-Supervised Alignment with Mutual Information: Learning to Follow Principles without Preference Labels. CoRR abs/2404.14313 (2024) - 2023
- [j1]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:
Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. 2023 (2023) - [c6]Eric Zelikman, Wanjing Anya Ma, Jasmine E. Tran, Diyi Yang, Jason D. Yeatman, Nick Haber:
Generating and Evaluating Tests for K-12 Students with Language Model Simulations: A Case Study on Sentence Reading Efficiency. EMNLP 2023: 2190-2205 - [c5]Qian Huang, Eric Zelikman, Sarah Chen, Yuhuai Wu, Gregory Valiant, Percy Liang:
Lexinvariant Language Models. NeurIPS 2023 - [c4]Eric Zelikman, Qian Huang, Gabriel Poesia, Noah D. Goodman, Nick Haber:
Parsel🦆: Algorithmic Reasoning with Language Models by Composing Decompositions. NeurIPS 2023 - [i17]Qian Huang, Eric Zelikman, Sarah Li Chen, Yuhuai Wu, Gregory Valiant, Percy Liang:
Lexinvariant Language Models. CoRR abs/2305.16349 (2023) - [i16]Gabriel Poesia, Kanishk Gandhi, Eric Zelikman, Noah D. Goodman:
Certified Reasoning with Language Models. CoRR abs/2306.04031 (2023) - [i15]Eric Zelikman, Qian Huang, Percy Liang, Nick Haber, Noah D. Goodman:
Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized Language Model Finetuning Using Shared Randomness. CoRR abs/2306.10015 (2023) - [i14]Yuhao Nie, Eric Zelikman, Andea Scott, Quentin Paletta, Adam Brandt:
SkyGPT: Probabilistic Short-term Solar Forecasting Using Synthetic Sky Videos from Physics-constrained VideoGPT. CoRR abs/2306.11682 (2023) - [i13]Ruocheng Wang, Eric Zelikman, Gabriel Poesia, Yewen Pu, Nick Haber, Noah D. Goodman:
Hypothesis Search: Inductive Reasoning with Language Models. CoRR abs/2309.05660 (2023) - [i12]Elisa Kreiss, Eric Zelikman, Christopher Potts, Nick Haber:
ContextRef: Evaluating Referenceless Metrics For Image Description Generation. CoRR abs/2309.11710 (2023) - [i11]Eric Zelikman, Eliana Lorch, Lester Mackey, Adam Tauman Kalai:
Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation. CoRR abs/2310.02304 (2023) - [i10]Eric Zelikman, Wanjing Anya Ma, Jasmine E. Tran, Diyi Yang, Jason D. Yeatman, Nick Haber:
Generating and Evaluating Tests for K-12 Students with Language Model Simulations: A Case Study on Sentence Reading Efficiency. CoRR abs/2310.06837 (2023) - 2022
- [c3]Elisa Kreiss, Cynthia L. Bennett, Shayan Hooshmand, Eric Zelikman, Meredith Ringel Morris, Christopher Potts:
Context Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metrics. EMNLP 2022: 4685-4697 - [c2]Eric Zelikman, Yuhuai Wu, Jesse Mu, Noah D. Goodman:
STaR: Bootstrapping Reasoning With Reasoning. NeurIPS 2022 - [i9]Eric Zelikman, Yuhuai Wu, Noah D. Goodman:
STaR: Bootstrapping Reasoning With Reasoning. CoRR abs/2203.14465 (2022) - [i8]Elisa Kreiss, Cynthia L. Bennett, Shayan Hooshmand, Eric Zelikman, Meredith Ringel Morris, Christopher Potts:
Context Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metrics. CoRR abs/2205.10646 (2022) - [i7]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:
Holistic Evaluation of Language Models. CoRR abs/2211.09110 (2022) - [i6]Eric Zelikman, Qian Huang, Gabriel Poesia, Noah D. Goodman, Nick Haber:
Parsel: A Unified Natural Language Framework for Algorithmic Reasoning. CoRR abs/2212.10561 (2022) - 2021
- [c1]Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Gunnar E. Carlsson, Stefano Ermon:
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology. ICLR 2021 - 2020
- [i5]Eric Zelikman, William Yin, Kenneth Wang:
Learning as Reinforcement: Applying Principles of Neuroscience for More General Reinforcement Learning Agents. CoRR abs/2004.09043 (2020) - [i4]Eric Zelikman, Christopher Healy:
Improving Regression Uncertainty Estimates with an Empirical Prior. CoRR abs/2005.12496 (2020) - [i3]Sharon Zhou, Eric Zelikman, Fred Lu, Andrew Y. Ng, Stefano Ermon:
Evaluating the Disentanglement of Deep Generative Models through Manifold Topology. CoRR abs/2006.03680 (2020) - [i2]Eric Zelikman, Sharon Zhou, Jeremy Irvin, Cooper Raterink, Hao Sheng, Jack Kelly, Ram Rajagopal, Andrew Y. Ng, David Gagne:
Short-Term Solar Irradiance Forecasting Using Calibrated Probabilistic Models. CoRR abs/2010.04715 (2020)
2010 – 2019
- 2018
- [i1]Eric Zelikman:
Context is Everything: Finding Meaning Statistically in Semantic Spaces. CoRR abs/1803.08493 (2018)
Coauthor Index
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last updated on 2024-08-10 00:32 CEST by the dblp team
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