Reinterpreting Importance-Weighted Autoencoders. - Chris Cremer; Quaid Morris; David Duvenaud (ICLR (Workshop), 2017)

Inference Suboptimality in Variational Autoencoders. - Chris Cremer; Xuechen Li 005; David Duvenaud (ICML, 2018)

Approximate Inference in Variational Autoencoders. - Chris Cremer (2020)

Back to Basics: Revisiting REINFORCE-Style Optimization for Learning from Human Feedback in LLMs. - Arash Ahmadian; Chris Cremer; Matthias Gallé; Marzieh Fadaee; Julia Kreutzer; Olivier Pietquin; Ahmet Üstün; Sara Hooker (ACL (1), 2024)

Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion. - Yannis Flet-Berliac; Nathan Grinsztajn; Florian Strub; Eugene Choi; Bill Wu; Chris Cremer; Arash Ahmadian; Yash Chandak; Mohammad Gheshlaghi Azar; Olivier Pietquin; Matthieu Geist (EMNLP, 2024)

Contrastive Policy Gradient: Aligning LLMs on sequence-level scores in a supervised-friendly fashion. - Yannis Flet-Berliac; Nathan Grinsztajn; Florian Strub; Eugene Choi; Chris Cremer; Arash Ahmadian; Yash Chandak; Mohammad Gheshlaghi Azar; Olivier Pietquin; Matthieu Geist (CoRR, 2024)

Averaging log-likelihoods in direct alignment. - Nathan Grinsztajn; Yannis Flet-Berliac; Mohammad Gheshlaghi Azar; Florian Strub; Bill Wu; Eugene Choi; Chris Cremer; Arash Ahmadian; Yash Chandak; Olivier Pietquin; Matthieu Geist (CoRR, 2024)