2 citations · 2 across the 2 of their papers we have counts for
3 papers
Tapered Off-Policy REINFORCE: Stable and efficient reinforcement learning for LLMs
Nicolas Le Roux, Marc G. Bellemare, Jonathan Lebensold +7
We propose a new algorithm for fine-tuning large language models using reinforcement learning. Tapered Off-Policy REINFORCE (TOPR) uses an asymmetric, tapered variant of importance…
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation
Guillaume Huguet, James Vuckovic, Kilian Fatras +9
Proteins are essential for almost all biological processes and derive their diverse functions from complex 3D structures, which are in turn determined by their amino acid sequences…
GSNs : Generative Stochastic Networks
Guillaume Alain, Yoshua Bengio, Li Yao +4
We introduce a novel training principle for probabilistic models that is an alternative to maximum likelihood. The proposed Generative Stochastic Networks (GSN) framework is based…