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2020 – today
- 2024
[c4]Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, Julia Kreutzer, Olivier Pietquin, Ahmet Üstün, Sara Hooker:
Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs. ACL (1) 2024: 12248-12267- [c3]Yannis Flet-Berliac, Nathan Grinsztajn, Florian Strub, Eugene Choi, Bill Wu, Chris Cremer, Arash Ahmadian, Yash Chandak, Mohammad Gheshlaghi Azar, Olivier Pietquin, Matthieu Geist:
Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion. EMNLP 2024: 21353-21370 - [i4]Arash Ahmadian, Chris Cremer, Matthias Gallé, Marzieh Fadaee, Julia Kreutzer, Olivier Pietquin, Ahmet Üstün, Sara Hooker:
Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs. CoRR abs/2402.14740 (2024) - [i3]Yannis Flet-Berliac, Nathan Grinsztajn, Florian Strub, Eugene Choi, Chris Cremer, Arash Ahmadian, Yash Chandak, Mohammad Gheshlaghi Azar, Olivier Pietquin, Matthieu Geist:
Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion. CoRR abs/2406.19185 (2024) - [i2]Nathan Grinsztajn, Yannis Flet-Berliac, Mohammad Gheshlaghi Azar, Florian Strub, Bill Wu, Eugene Choi, Chris Cremer, Arash Ahmadian, Yash Chandak, Olivier Pietquin, Matthieu Geist:
Averaging log-likelihoods in direct alignment. CoRR abs/2406.19188 (2024) - 2020
- [b1]Chris Cremer:
Approximate Inference in Variational Autoencoders. University of Toronto, Canada, 2020
2010 – 2019
- 2018
- [c2]Chris Cremer, Xuechen Li, David Duvenaud:
Inference Suboptimality in Variational Autoencoders. ICML 2018: 1086-1094 - [i1]Chris Cremer, Xuechen Li, David Duvenaud:
Inference Suboptimality in Variational Autoencoders. CoRR abs/1801.03558 (2018) - 2017
- [c1]Chris Cremer, Quaid Morris, David Duvenaud:
Reinterpreting Importance-Weighted Autoencoders. ICLR (Workshop) 2017
Coauthor Index
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