Ivison, Hamish

7 publications

NeurIPS 2025 Generalizing Verifiable Instruction Following Valentina Pyatkin, Saumya Malik, Victoria Graf, Hamish Ivison, Shengyi Huang, Pradeep Dasigi, Nathan Lambert, Hannaneh Hajishirzi

ICLRW 2025 The Delta Learning Hypothesis: Preference Tuning on Weak Data Can Yield Strong Gains Scott Geng, Hamish Ivison, Chun-Liang Li, Maarten Sap, Jerry Li, Ranjay Krishna, Pang Wei Koh

NeurIPSW 2024 Best Unpacking DPO and PPO: Disentangling Practices for Learning from Preference Feedback Hamish Ivison, Yizhong Wang, Jiacheng Liu, Zeqiu Wu, Valentina Pyatkin, Nathan Lambert, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi

NeurIPS 2024 Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning Sriyash Poddar, Yanming Wan, Hamish Ivison, Abhishek Gupta, Natasha Jaques

NeurIPSW 2024 Personalizing Reinforcement Learning from Human Feedback with Variational Preference Learning Sriyash Poddar, Yanming Wan, Hamish Ivison, Abhishek Gupta, Natasha Jaques

NeurIPS 2024 Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback Hamish Ivison, Yizhong Wang, Jiacheng Liu, Zeqiu Wu, Valentina Pyatkin, Nathan Lambert, Noah A. Smith, Yejin Choi, Hannaneh Hajishirzi

NeurIPS 2023 How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources Yizhong Wang, Hamish Ivison, Pradeep Dasigi, Jack Hessel, Tushar Khot, Khyathi Chandu, David Wadden, Kelsey MacMillan, Noah A. Smith, Iz Beltagy, Hannaneh Hajishirzi