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ORCIDSean Welleck
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2020 – today
- 2024
[c34]Seungone Kim, Juyoung Suk, Shayne Longpre, Bill Yuchen Lin, Jamin Shin, Sean Welleck, Graham Neubig, Moontae Lee, Kyungjae Lee, Minjoon Seo:
Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models. EMNLP 2024: 4334-4353- [c33]Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, Marco Dos Santos, Stephen Marcus McAleer, Albert Q. Jiang, Jia Deng, Stella Biderman, Sean Welleck:
Llemma: An Open Language Model for Mathematics. ICLR 2024 - [i42]Zhiqing Sun, Longhui Yu, Yikang Shen, Weiyang Liu, Yiming Yang, Sean Welleck, Chuang Gan:
Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision. CoRR abs/2403.09472 (2024) - [i41]Seungone Kim, Juyoung Suk, Shayne Longpre, Bill Yuchen Lin, Jamin Shin, Sean Welleck, Graham Neubig, Moontae Lee, Kyungjae Lee, Minjoon Seo:
Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models. CoRR abs/2405.01535 (2024) - [i40]Seungone Kim, Juyoung Suk, Ji Yong Cho, Shayne Longpre, Chaeeun Kim, Dongkeun Yoon, Guijin Son, Yejin Choi, Sheikh Shafayat, Jinheon Baek, Sue Hyun Park, Hyeonbin Hwang, Jinkyung Jo, Hyowon Cho, Haebin Shin, Seongyun Lee, Hanseok Oh, Noah Lee, Namgyu Ho, Se June Joo, Miyoung Ko, Yoonjoo Lee, Hyungjoo Chae, Jamin Shin, Joel Jang, Seonghyeon Ye, Bill Yuchen Lin, Sean Welleck, Graham Neubig, Moontae Lee, Kyungjae Lee, Minjoon Seo:
The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models. CoRR abs/2406.05761 (2024) - [i39]Evan Lohn, Sean Welleck:
miniCodeProps: a Minimal Benchmark for Proving Code Properties. CoRR abs/2406.11915 (2024) - [i38]Sean Welleck, Amanda Bertsch, Matthew Finlayson, Hailey Schoelkopf, Alex Xie, Graham Neubig, Ilia Kulikov, Zaïd Harchaoui:
From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models. CoRR abs/2406.16838 (2024) - [i37]Haohan Lin, Zhiqing Sun, Yiming Yang, Sean Welleck:
Lean-STaR: Learning to Interleave Thinking and Proving. CoRR abs/2407.10040 (2024) - [i36]Yangzhen Wu, Zhiqing Sun, Shanda Li, Sean Welleck, Yiming Yang:
An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models. CoRR abs/2408.00724 (2024) - [i35]Jiewen Hu, Thomas Zhu, Sean Welleck:
miniCTX: Neural Theorem Proving with (Long-)Contexts. CoRR abs/2408.03350 (2024) - [i34]Riyaz Ahuja, Jeremy Avigad, Prasad Tetali, Sean Welleck:
ImProver: Agent-Based Automated Proof Optimization. CoRR abs/2410.04753 (2024) - 2023
- [j1]Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
MAUVE Scores for Generative Models: Theory and Practice. J. Mach. Learn. Res. 24: 356:1-356:92 (2023) - [c32]Pan Lu, Liang Qiu, Wenhao Yu, Sean Welleck, Kai-Wei Chang:
A Survey of Deep Learning for Mathematical Reasoning. ACL (1) 2023: 14605-14631 - [c31]Ximing Lu, Faeze Brahman, Peter West, Jaehun Jung, Khyathi Raghavi Chandu, Abhilasha Ravichander, Prithviraj Ammanabrolu, Liwei Jiang, Sahana Ramnath, Nouha Dziri, Jillian Fisher, Bill Y. Lin, Skyler Hallinan, Lianhui Qin, Xiang Ren, Sean Welleck, Yejin Choi:
Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. EMNLP 2023: 6863-6883 - [c30]Skyler Hallinan, Faeze Brahman, Ximing Lu, Jaehun Jung, Sean Welleck, Yejin Choi:
STEER: Unified Style Transfer with Expert Reinforcement. EMNLP (Findings) 2023: 7546-7562 - [c29]Albert Qiaochu Jiang, Sean Welleck, Jin Peng Zhou, Timothée Lacroix, Jiacheng Liu, Wenda Li, Mateja Jamnik, Guillaume Lample, Yuhuai Wu:
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs. ICLR 2023 - [c28]Sean Welleck, Ximing Lu, Peter West, Faeze Brahman, Tianxiao Shen, Daniel Khashabi, Yejin Choi:
Generating Sequences by Learning to Self-Correct. ICLR 2023 - [c27]Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Sean Welleck, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Xiang Ren, Allyson Ettinger, Zaïd Harchaoui, Yejin Choi:
Faith and Fate: Limits of Transformers on Compositionality. NeurIPS 2023 - [c26]Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark:
Self-Refine: Iterative Refinement with Self-Feedback. NeurIPS 2023 - [i33]Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Sean Welleck, Bodhisattwa Prasad Majumder, Shashank Gupta, Amir Yazdanbakhsh, Peter Clark:
Self-Refine: Iterative Refinement with Self-Feedback. CoRR abs/2303.17651 (2023) - [i32]Ximing Lu, Faeze Brahman, Peter West, Jaehun Jung, Khyathi Raghavi Chandu, Abhilasha Ravichander, Lianhui Qin, Prithviraj Ammanabrolu, Liwei Jiang, Sahana Ramnath, Nouha Dziri, Jillian Fisher, Bill Yuchen Lin, Skyler Hallinan, Xiang Ren, Sean Welleck, Yejin Choi:
Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning. CoRR abs/2305.15065 (2023) - [i31]Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Lorraine Li, Liwei Jiang, Bill Yuchen Lin, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena D. Hwang, Soumya Sanyal, Sean Welleck, Xiang Ren, Allyson Ettinger, Zaïd Harchaoui, Yejin Choi:
Faith and Fate: Limits of Transformers on Compositionality. CoRR abs/2305.18654 (2023) - [i30]Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, Marco Dos Santos, Stephen McAleer, Albert Q. Jiang, Jia Deng, Stella Biderman, Sean Welleck:
Llemma: An Open Language Model For Mathematics. CoRR abs/2310.10631 (2023) - [i29]Sean Welleck, Rahul Saha:
LLMSTEP: LLM proofstep suggestions in Lean. CoRR abs/2310.18457 (2023) - [i28]Skyler Hallinan, Faeze Brahman, Ximing Lu, Jaehun Jung, Sean Welleck, Yejin Choi:
STEER: Unified Style Transfer with Expert Reinforcement. CoRR abs/2311.07167 (2023) - 2022
- [c25]Sean Welleck, Peter West, Jize Cao, Yejin Choi:
Symbolic Brittleness in Sequence Models: On Systematic Generalization in Symbolic Mathematics. AAAI 2022: 8629-8637 - [c24]Jiacheng Liu, Alisa Liu, Ximing Lu, Sean Welleck, Peter West, Ronan Le Bras, Yejin Choi, Hannaneh Hajishirzi:
Generated Knowledge Prompting for Commonsense Reasoning. ACL (1) 2022: 3154-3169 - [c23]Jaehun Jung, Lianhui Qin, Sean Welleck, Faeze Brahman, Chandra Bhagavatula, Ronan Le Bras, Yejin Choi:
Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations. EMNLP 2022: 1266-1279 - [c22]Swaroop Mishra, Matthew Finlayson, Pan Lu, Leonard Tang, Sean Welleck, Chitta Baral, Tanmay Rajpurohit, Oyvind Tafjord, Ashish Sabharwal, Peter Clark, Ashwin Kalyan:
LILA: A Unified Benchmark for Mathematical Reasoning. EMNLP 2022: 5807-5832 - [c21]Jiacheng Liu, Skyler Hallinan, Ximing Lu, Pengfei He, Sean Welleck, Hannaneh Hajishirzi, Yejin Choi:
Rainier: Reinforced Knowledge Introspector for Commonsense Question Answering. EMNLP 2022: 8938-8958 - [c20]Ximing Lu, Sean Welleck, Peter West, Liwei Jiang, Jungo Kasai, Daniel Khashabi, Ronan Le Bras, Lianhui Qin, Youngjae Yu, Rowan Zellers, Noah A. Smith, Yejin Choi:
NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics. NAACL-HLT 2022: 780-799 - [c19]Daniel Khashabi, Xinxi Lyu, Sewon Min, Lianhui Qin, Kyle Richardson, Sean Welleck, Hannaneh Hajishirzi, Tushar Khot, Ashish Sabharwal, Sameer Singh, Yejin Choi:
Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts. NAACL-HLT 2022: 3631-3643 - [c18]Peter West, Chandra Bhagavatula, Jack Hessel, Jena D. Hwang, Liwei Jiang, Ronan Le Bras, Ximing Lu, Sean Welleck, Yejin Choi:
Symbolic Knowledge Distillation: from General Language Models to Commonsense Models. NAACL-HLT 2022: 4602-4625 - [c17]Ximing Lu, Sean Welleck, Jack Hessel, Liwei Jiang, Lianhui Qin, Peter West, Prithviraj Ammanabrolu, Yejin Choi:
QUARK: Controllable Text Generation with Reinforced Unlearning. NeurIPS 2022 - [c16]Lianhui Qin, Sean Welleck, Daniel Khashabi, Yejin Choi:
COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics. NeurIPS 2022 - [c15]Sean Welleck, Jiacheng Liu, Ximing Lu, Hannaneh Hajishirzi, Yejin Choi:
NaturalProver: Grounded Mathematical Proof Generation with Language Models. NeurIPS 2022 - [i27]Lianhui Qin, Sean Welleck, Daniel Khashabi, Yejin Choi:
COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics. CoRR abs/2202.11705 (2022) - [i26]Jaehun Jung, Lianhui Qin, Sean Welleck, Faeze Brahman, Chandra Bhagavatula, Ronan Le Bras, Yejin Choi:
Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations. CoRR abs/2205.11822 (2022) - [i25]Sean Welleck, Jiacheng Liu, Ximing Lu, Hannaneh Hajishirzi, Yejin Choi:
NaturalProver: Grounded Mathematical Proof Generation with Language Models. CoRR abs/2205.12910 (2022) - [i24]Ximing Lu, Sean Welleck, Liwei Jiang, Jack Hessel, Lianhui Qin, Peter West, Prithviraj Ammanabrolu, Yejin Choi:
Quark: Controllable Text Generation with Reinforced Unlearning. CoRR abs/2205.13636 (2022) - [i23]Jiacheng Liu, Skyler Hallinan, Ximing Lu, Pengfei He, Sean Welleck, Hannaneh Hajishirzi, Yejin Choi:
Rainier: Reinforced Knowledge Introspector for Commonsense Question Answering. CoRR abs/2210.03078 (2022) - [i22]Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, Wenda Li, Jiacheng Liu, Mateja Jamnik, Timothée Lacroix, Yuhuai Wu, Guillaume Lample:
Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs. CoRR abs/2210.12283 (2022) - [i21]Swaroop Mishra, Matthew Finlayson, Pan Lu, Leonard Tang, Sean Welleck, Chitta Baral, Tanmay Rajpurohit, Oyvind Tafjord, Ashish Sabharwal, Peter Clark, Ashwin Kalyan:
Lila: A Unified Benchmark for Mathematical Reasoning. CoRR abs/2210.17517 (2022) - [i20]Sean Welleck, Ximing Lu, Peter West, Faeze Brahman, Tianxiao Shen, Daniel Khashabi, Yejin Choi:
Generating Sequences by Learning to Self-Correct. CoRR abs/2211.00053 (2022) - [i19]Pan Lu, Liang Qiu, Wenhao Yu, Sean Welleck, Kai-Wei Chang:
A Survey of Deep Learning for Mathematical Reasoning. CoRR abs/2212.10535 (2022) - [i18]Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
MAUVE Scores for Generative Models: Theory and Practice. CoRR abs/2212.14578 (2022) - 2021
- [b1]Sean Welleck:
Order and Learning in Sequential Neural Structured Prediction. New York University, USA, 2021 - [c14]Sean Welleck, Kyunghyun Cho:
MLE-Guided Parameter Search for Task Loss Minimization in Neural Sequence Modeling. AAAI 2021: 14032-14040 - [c13]Ilia Kulikov, Sean Welleck, Kyunghyun Cho:
Mode recovery in neural autoregressive sequence modeling. SPNLP@ACL-IJCNLP 2021: 44-52 - [c12]Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, Zaïd Harchaoui:
MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontiers. NeurIPS 2021: 4816-4828 - [c11]Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals. NeurIPS 2021: 12930-12942 - [c10]Sean Welleck, Jiacheng Liu, Ronan Le Bras, Hanna Hajishirzi, Yejin Choi, Kyunghyun Cho:
NaturalProofs: Mathematical Theorem Proving in Natural Language. NeurIPS Datasets and Benchmarks 2021 - [i17]Sean Welleck, Jiacheng Liu, Ronan Le Bras, Hannaneh Hajishirzi, Yejin Choi, Kyunghyun Cho:
NaturalProofs: Mathematical Theorem Proving in Natural Language. CoRR abs/2104.01112 (2021) - [i16]Ilia Kulikov, Sean Welleck, Kyunghyun Cho:
Mode recovery in neural autoregressive sequence modeling. CoRR abs/2106.05459 (2021) - [i15]Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaïd Harchaoui:
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral. CoRR abs/2106.07898 (2021) - [i14]Sean Welleck, Peter West, Jize Cao, Yejin Choi:
Symbolic Brittleness in Sequence Models: on Systematic Generalization in Symbolic Mathematics. CoRR abs/2109.13986 (2021) - [i13]Peter West, Chandra Bhagavatula, Jack Hessel, Jena D. Hwang, Liwei Jiang, Ronan Le Bras, Ximing Lu, Sean Welleck, Yejin Choi:
Symbolic Knowledge Distillation: from General Language Models to Commonsense Models. CoRR abs/2110.07178 (2021) - [i12]Jiacheng Liu, Alisa Liu, Ximing Lu, Sean Welleck, Peter West, Ronan Le Bras, Yejin Choi, Hannaneh Hajishirzi:
Generated Knowledge Prompting for Commonsense Reasoning. CoRR abs/2110.08387 (2021) - [i11]Daniel Khashabi, Shane Lyu, Sewon Min, Lianhui Qin, Kyle Richardson, Sameer Singh, Sean Welleck, Hannaneh Hajishirzi, Tushar Khot, Ashish Sabharwal, Yejin Choi:
PROMPT WAYWARDNESS: The Curious Case of Discretized Interpretation of Continuous Prompts. CoRR abs/2112.08348 (2021) - [i10]Ximing Lu, Sean Welleck, Peter West, Liwei Jiang, Jungo Kasai, Daniel Khashabi, Ronan Le Bras, Lianhui Qin, Youngjae Yu, Rowan Zellers, Noah A. Smith, Yejin Choi:
NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics. CoRR abs/2112.08726 (2021) - 2020
- [c9]Margaret Li, Stephen Roller, Ilia Kulikov, Sean Welleck, Y-Lan Boureau, Kyunghyun Cho, Jason Weston:
Don't Say That! Making Inconsistent Dialogue Unlikely with Unlikelihood Training. ACL 2020: 4715-4728 - [c8]Sean Welleck, Ilia Kulikov, Jaedeok Kim, Richard Yuanzhe Pang, Kyunghyun Cho:
Consistency of a Recurrent Language Model With Respect to Incomplete Decoding. EMNLP (1) 2020: 5553-5568 - [c7]Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, Jason Weston:
Neural Text Generation With Unlikelihood Training. ICLR 2020 - [i9]Sean Welleck, Ilia Kulikov, Jaedeok Kim, Richard Yuanzhe Pang, Kyunghyun Cho:
Consistency of a Recurrent Language Model With Respect to Incomplete Decoding. CoRR abs/2002.02492 (2020) - [i8]Sean Welleck, Kyunghyun Cho:
MLE-guided parameter search for task loss minimization in neural sequence modeling. CoRR abs/2006.03158 (2020)
2010 – 2019
- 2019
- [c6]Sean Welleck, Jason Weston, Arthur Szlam, Kyunghyun Cho:
Dialogue Natural Language Inference. ACL (1) 2019: 3731-3741 - [c5]Kianté Brantley, Kyunghyun Cho, Hal Daumé III, Sean Welleck:
Non-Monotonic Sequential Text Generation. WNLP@ACL 2019: 57-59 - [c4]Sean Welleck, Kianté Brantley, Hal Daumé III, Kyunghyun Cho:
Non-Monotonic Sequential Text Generation. ICML 2019: 6716-6726 - [c3]Sean Welleck, Kyunghyun Cho:
Sequential Graph Dependency Parser. RANLP 2019: 1338-1345 - [i7]Sean Welleck, Kianté Brantley, Hal Daumé III, Kyunghyun Cho:
Non-Monotonic Sequential Text Generation. CoRR abs/1902.02192 (2019) - [i6]Sean Welleck, Kyunghyun Cho:
Sequential Graph Dependency Parser. CoRR abs/1905.10930 (2019) - [i5]Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, Jason Weston:
Neural Text Generation with Unlikelihood Training. CoRR abs/1908.04319 (2019) - [i4]Margaret Li, Stephen Roller, Ilia Kulikov, Sean Welleck, Y-Lan Boureau, Kyunghyun Cho, Jason Weston:
Don't Say That! Making Inconsistent Dialogue Unlikely with Unlikelihood Training. CoRR abs/1911.03860 (2019) - 2018
- [c2]Sean Welleck, Zixin Yao, Yu Gai, Jialin Mao, Zheng Zhang, Kyunghyun Cho:
Loss Functions for Multiset Prediction. NeurIPS 2018: 5788-5797 - [i3]Sean Welleck, Jason Weston, Arthur Szlam, Kyunghyun Cho:
Dialogue Natural Language Inference. CoRR abs/1811.00671 (2018) - 2017
- [c1]Sean Welleck, Jialin Mao, Kyunghyun Cho, Zheng Zhang:
Saliency-based Sequential Image Attention with Multiset Prediction. NIPS 2017: 5173-5183 - [i2]Sean Welleck, Jialin Mao, Kyunghyun Cho, Zheng Zhang:
Saliency-based Sequential Image Attention with Multiset Prediction. CoRR abs/1711.05165 (2017) - [i1]Sean Welleck, Zixin Yao, Yu Gai, Jialin Mao, Zheng Zhang, Kyunghyun Cho:
Loss Functions for Multiset Prediction. CoRR abs/1711.05246 (2017)
Coauthor Index
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