3 papers
cs.CV2026
Data Selection Through Iterative Self-Filtering for Vision-Language Settings
Andrei Liviu Nicolicioiu, Sarvjeet Singh Ghotra, Morgane M. Moss +1
The availability of large amounts of clean data is paramount to training neural networks. However, at large scales, manual oversight is impractical, resulting in sizeable datasets…
cs.LG2026
Putting the Value Back in RL: Better Test-Time Scaling by Unifying LLM Reasoners With Verifiers
Kusha Sareen, Morgane M Moss, Alessandro Sordoni +2
Prevalent reinforcement learning~(RL) methods for fine-tuning LLM reasoners, such as GRPO or Leave-one-out PPO, abandon the learned value function in favor of empirically estimated…
cs.AI2025
debug-gym: A Text-Based Environment for Interactive Debugging
Xingdi Yuan, Morgane M Moss, Charbel El Feghali +8
Large Language Models (LLMs) are increasingly relied upon for coding tasks, yet in most scenarios it is assumed that all relevant information can be either accessed in context or m…