Meta-Learning Initializations for Image Segmentation. - Sean M. Hendryx; Andrew B. Leach; Paul Douglas Hein; Clayton T. Morrison (CoRR, 2019)

Extracting Inter-Sentence Relations for Associating Biological Context with Events in Biomedical Texts. - Enrique Noriega-Atala; Paul Douglas Hein; Shraddha Satish Thumsi; Zechy Wong; Xia Wang; Sean M. Hendryx; Clayton T. Morrison (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

Federated Reconnaissance: Efficient, Distributed, Class-Incremental Learning. - Sean M. Hendryx; Dharma Raj KC; Bradley Walls; Clayton T. Morrison (CoRR, 2021)

Assessing Vegetation Response to Multi-Scalar Drought across the Mojave, Sonoran, Chihuahuan Deserts and Apache Highlands in the Southwest United States. - Pratima Khatri-Chhetri; Sean M. Hendryx; Kyle A. Hartfield; Michael A. Crimmins; Willem J. D. van Leeuwen; Van R. Kane (Remote. Sens., 2021)

A Baseline Analysis of Reward Models' Ability To Accurately Analyze Foundation Models Under Distribution Shift. - Benjamin Pikus; Will LeVine; Tony Chen; Sean Hendryx (CoRR, 2023)

Learning Goal-Conditioned Representations for Language Reward Models. - Vaskar Nath; Dylan Slack; Jeff Da; Yuntao Ma; Hugh Zhang; Spencer Whitehead; Sean Hendryx (NeurIPS, 2024)

A Careful Examination of Large Language Model Performance on Grade School Arithmetic. - Hugh Zhang; Jeff Da; Dean Lee; Vaughn Robinson; Catherine Wu; William Song; Tiffany Zhao; Pranav Raja; Charlotte Zhuang; Dylan Slack; Qin Lyu; Sean Hendryx; et al. (NeurIPS, 2024)

Out-of-Distribution Detection & Applications With Ablated Learned Temperature Energy. - Will LeVine; Benjamin Pikus; Jacob Phillips; Berk Norman; Fernando Amat Gil; Sean Hendryx (CoRR, 2024)

A Careful Examination of Large Language Model Performance on Grade School Arithmetic. - Hugh Zhang; Jeff Da; Dean Lee; Vaughn Robinson; Catherine Wu; Will Song; Tiffany Zhao; Pranav Raja; Dylan Slack; Qin Lyu; Sean Hendryx; Russell Kaplan; et al. (CoRR, 2024)

Pre-Training Multimodal Hallucination Detectors with Corrupted Grounding Data. - Spencer Whitehead; Jacob Phillips; Sean Hendryx (CoRR, 2024)

Planning In Natural Language Improves LLM Search For Code Generation. - Evan Z. Wang; Federico Cassano; Catherine Wu; Yunfeng Bai; Will Song; Vaskar Nath; Ziwen Han; Sean Hendryx; Summer Yue; Hugh Zhang (CoRR, 2024)

Revisiting the Superficial Alignment Hypothesis. - Mohit Raghavendra; Vaskar Nath; Sean Hendryx (CoRR, 2024)

Refusal-Trained LLMs Are Easily Jailbroken As Browser Agents. - Priyanshu Kumar; Elaine Lau; Saranya Vijayakumar; Tu Trinh; Scale Red Team; Elaine T. Chang; Vaughn Robinson; Sean Hendryx; Shuyan Zhou; Matt Fredrikson; Summer Yue; Zifan Wang 001 (CoRR, 2024)

Aligned LLMs Are Not Aligned Browser Agents. - Priyanshu Kumar; Elaine Lau; Saranya Vijayakumar; Tu Trinh; Elaine T. Chang; Vaughn Robinson; Shuyan Zhou; Matt Fredrikson; Sean M. Hendryx; Summer Yue; Zifan Wang 001 (ICLR, 2025)

Planning in Natural Language Improves LLM Search for Code Generation. - Evan Z. Wang; Federico Cassano; Catherine Wu; Yunfeng Bai; William Song; Vaskar Nath; Ziwen Han; Sean M. Hendryx; Summer Yue; Hugh Zhang (ICLR, 2025)

ToolComp: A Multi-Tool Reasoning & Process Supervision Benchmark. - Vaskar Nath; Pranav Raja; Claire Yoon; Sean Hendryx (CoRR, 2025)

EnigmaEval: A Benchmark of Long Multimodal Reasoning Challenges. - Clinton J. Wang; Dean Lee; Cristina Menghini; Johannes Mols; Jack Doughty; Adam Khoja; Jayson Lynch; Sean Hendryx; Summer Yue; Dan Hendrycks (CoRR, 2025)

Agent-RLVR: Training Software Engineering Agents via Guidance and Environment Rewards. - Jeff Da; Clinton Wang; Xiang Deng; Yuntao Ma; Nikhil Barhate; Sean Hendryx (CoRR, 2025)

Adaptive Guidance Accelerates Reinforcement Learning of Reasoning Models. - Vaskar Nath; Elaine Lau; Anisha Gunjal; Manasi Sharma; Nikhil Baharte; Sean Hendryx (CoRR, 2025)

Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains. - Anisha Gunjal; Anthony Wang; Elaine Lau; Vaskar Nath; Bing Liu; Sean Hendryx (CoRR, 2025)