1 citations · 1 across the 4 of their papers we have counts for
4 papers · 1 filter
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…
VinePPO: Refining Credit Assignment in RL Training of LLMs
Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance +4
Large language models (LLMs) are increasingly applied to complex reasoning tasks that require executing several complex steps before receiving any reward. Properly assigning credit…
Towards Modular LLMs by Building and Reusing a Library of LoRAs
Oleksiy Ostapenko, Zhan Su, Edoardo Maria Ponti +5
The growing number of parameter-efficient adaptations of a base large language model (LLM) calls for studying whether we can reuse such trained adapters to improve performance for…
Language-guided Skill Learning with Temporal Variational Inference
Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin +4
We present an algorithm for skill discovery from expert demonstrations. The algorithm first utilizes Large Language Models (LLMs) to propose an initial segmentation of the trajecto…