Misha Khalman

According to our database, Misha Khalman authored at least 9 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Building Math Agents with Multi-Turn Iterative Preference Learning.

Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg, Zhen Qin, Daniele Calandriello, Misha Khalman, Rishabh Joshi, Bilal Piot, Mohammad Saleh, Chi Jin, Tong Zhang, Tianqi Liu

CoRR, 2024

Direct Language Model Alignment from Online AI Feedback.

Shangmin Guo, Biao Zhang, Tianlin Liu, Tianqi Liu, Misha Khalman, Felipe Llinares, Alexandre Ramé, Thomas Mesnard, Yao Zhao, Bilal Piot, Johan Ferret, Mathieu Blondel

CoRR, 2024

LiPO: Listwise Preference Optimization through Learning-to-Rank.

Tianqi Liu, Zhen Qin, Junru Wu, Jiaming Shen, Misha Khalman, Rishabh Joshi, Yao Zhao, Mohammad Saleh, Simon Baumgartner, Jialu Liu, Peter J. Liu, Xuanhui Wang

CoRR, 2024

Statistical Rejection Sampling Improves Preference Optimization.

Tianqi Liu, Yao Zhao, Rishabh Joshi, Misha Khalman, Mohammad Saleh, Peter J. Liu, Jialu Liu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Gemini: A Family of Highly Capable Multimodal Models.

Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M. Dai, Anja Hauth, Katie Millican, David Silver, Slav Petrov, Melvin Johnson, Ioannis Antonoglou, Julian Schrittwieser, Amelia Glaese, Jilin Chen, Emily Pitler, Timothy P. Lillicrap, Angeliki Lazaridou, Orhan Firat, James Molloy, Michael Isard, Paul Ronald Barham, Tom Hennigan, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, Ryan Doherty, Eli Collins, Clemens Meyer, Eliza Rutherford, Erica Moreira, Kareem Ayoub, Megha Goel, George Tucker, Enrique Piqueras, Maxim Krikun, Iain Barr, Nikolay Savinov, Ivo Danihelka, Becca Roelofs, Anaïs White, Anders Andreassen, Tamara von Glehn, Lakshman Yagati, Mehran Kazemi, Lucas Gonzalez, Misha Khalman, Jakub Sygnowski, et al.

CoRR, 2023

Calibrating Likelihoods towards Consistency in Summarization Models.

Polina Zablotskaia, Misha Khalman, Rishabh Joshi, Livio Baldini Soares, Shoshana Jakobovits, Joshua Maynez, Shashi Narayan

CoRR, 2023

SLiC-HF: Sequence Likelihood Calibration with Human Feedback.

Yao Zhao, Rishabh Joshi, Tianqi Liu, Misha Khalman, Mohammad Saleh, Peter J. Liu

CoRR, 2023

Calibrating Sequence likelihood Improves Conditional Language Generation.

Yao Zhao, Misha Khalman, Rishabh Joshi, Shashi Narayan, Mohammad Saleh, Peter J. Liu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2021

ForumSum: A Multi-Speaker Conversation Summarization Dataset.

Misha Khalman, Yao Zhao, Mohammad Saleh

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021