Welleck, Sean

33 publications

ICML 2025 AlphaVerus: Bootstrapping Formally Verified Code Generation Through Self-Improving Translation and Treefinement Pranjal Aggarwal, Bryan Parno, Sean Welleck
ICLRW 2025 AlphaVerus: Bootstrapping Formally Verified Code Generation Through Self-Improving Translation and Treefinement Pranjal Aggarwal, Bryan Parno, Sean Welleck
ICLR 2025 ImProver: Agent-Based Automated Proof Optimization Riyaz Ahuja, Jeremy Avigad, Prasad Tetali, Sean Welleck
ICLR 2025 Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for LLM Problem-Solving Yangzhen Wu, Zhiqing Sun, Shanda Li, Sean Welleck, Yiming Yang
ICLR 2025 Lean-STaR: Learning to Interleave Thinking and Proving Haohan Lin, Zhiqing Sun, Sean Welleck, Yiming Yang
ICML 2025 Optimizing Temperature for Language Models with Multi-Sample Inference Weihua Du, Yiming Yang, Sean Welleck
ICLRW 2025 Programming with Pixels: Towards Generalist Software Engineering Agents Pranjal Aggarwal, Sean Welleck
ICLR 2025 miniCTX: Neural Theorem Proving with (Long-)Contexts Jiewen Hu, Thomas Zhu, Sean Welleck
NeurIPS 2024 Easy-to-Hard Generalization: Scalable Alignment Beyond Human Supervision Zhiqing Sun, Longhui Yu, Yikang Shen, Weiyang Liu, Yiming Yang, Sean Welleck, Chuang Gan
TMLR 2024 From Decoding to Meta-Generation: Inference-Time Algorithms for Large Language Models Sean Welleck, Amanda Bertsch, Matthew Finlayson, Hailey Schoelkopf, Alex Xie, Graham Neubig, Ilia Kulikov, Zaid Harchaoui
NeurIPSW 2024 Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for LLM Problem-Solving Yangzhen Wu, Zhiqing Sun, Shanda Li, Sean Welleck, Yiming Yang
NeurIPSW 2024 Lean-STaR: Learning to Interleave Thinking and Proving Haohan Lin, Zhiqing Sun, Sean Welleck, Yiming Yang
ICLR 2024 Llemma: An Open Language Model for Mathematics Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, Marco Dos Santos, Stephen Marcus McAleer, Albert Q. Jiang, Jia Deng, Stella Biderman, Sean Welleck
NeurIPSW 2024 miniCTX: Neural Theorem Proving with (Long-)Contexts Jiewen Hu, Thomas Zhu, Sean Welleck
NeurIPSW 2024 miniCodeProps: A Minimal Benchmark for Proving Code Properties Evan Lohn, Sean Welleck
ICLR 2023 Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs Albert Qiaochu Jiang, Sean Welleck, Jin Peng Zhou, Timothee Lacroix, Jiacheng Liu, Wenda Li, Mateja Jamnik, Guillaume Lample, Yuhuai Wu
NeurIPS 2023 Faith and Fate: Limits of Transformers on Compositionality Nouha Dziri, Ximing Lu, Melanie Sclar, Xiang Li, Liwei Jiang, Bill Yuchen Lin, Sean Welleck, Peter West, Chandra Bhagavatula, Ronan Le Bras, Jena Hwang, Soumya Sanyal, Xiang Ren, Allyson Ettinger, Zaid Harchaoui, Yejin Choi
ICLR 2023 Generating Sequences by Learning to Self-Correct Sean Welleck, Ximing Lu, Peter West, Faeze Brahman, Tianxiao Shen, Daniel Khashabi, Yejin Choi
NeurIPSW 2023 Llemma: An Open Language Model for Mathematics Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, Marco Dos Santos, Stephen McAleer, Albert Jiang, Jia Deng, Stella Biderman, Sean Welleck
NeurIPSW 2023 Llmstep: LLM Proofstep Suggestions in Lean Sean Welleck, Rahul Saha
JMLR 2023 MAUVE Scores for Generative Models: Theory and Practice Krishna Pillutla, Lang Liu, John Thickstun, Sean Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Zaid Harchaoui
NeurIPS 2023 Self-Refine: Iterative Refinement with Self-Feedback 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
NeurIPS 2022 COLD Decoding: Energy-Based Constrained Text Generation with Langevin Dynamics Lianhui Qin, Sean Welleck, Daniel Khashabi, Yejin Choi
NeurIPS 2022 NaturalProver: Grounded Mathematical Proof Generation with Language Models Sean Welleck, Jiacheng Liu, Ximing Lu, Hannaneh Hajishirzi, Yejin Choi
NeurIPS 2022 QUARK: Controllable Text Generation with Reinforced Unlearning Ximing Lu, Sean Welleck, Jack Hessel, Liwei Jiang, Lianhui Qin, Peter West, Prithviraj Ammanabrolu, Yejin Choi
AAAI 2022 Symbolic Brittleness in Sequence Models: On Systematic Generalization in Symbolic Mathematics Sean Welleck, Peter West, Jize Cao, Yejin Choi
NeurIPS 2021 Divergence Frontiers for Generative Models: Sample Complexity, Quantization Effects, and Frontier Integrals Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaid Harchaoui
NeurIPS 2021 MAUVE: Measuring the Gap Between Neural Text and Human Text Using Divergence Frontiers Krishna Pillutla, Swabha Swayamdipta, Rowan Zellers, John Thickstun, Sean Welleck, Yejin Choi, Zaid Harchaoui
AAAI 2021 MLE-Guided Parameter Search for Task Loss Minimization in Neural Sequence Modeling Sean Welleck, Kyunghyun Cho
ICLR 2020 Neural Text Generation with Unlikelihood Training Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, Jason Weston
ICML 2019 Non-Monotonic Sequential Text Generation Sean Welleck, Kianté Brantley, Hal Daumé Iii, Kyunghyun Cho
NeurIPS 2018 Loss Functions for Multiset Prediction Sean Welleck, Zixin Yao, Yu Gai, Jialin Mao, Zheng Zhang, Kyunghyun Cho
NeurIPS 2017 Saliency-Based Sequential Image Attention with Multiset Prediction Sean Welleck, Jialin Mao, Kyunghyun Cho, Zheng Zhang