3 papers
cs.LG2026
AdvantageFlow: Advantage-Weighted Least Squares for RL in Flow Models
Branislav Kveton, Anup Rao, Subhojyoti Mukherjee +2
We introduce AdvantageFlow, a forward-process reinforcement learning algorithm for rectified flow models. Unlike Flow-GRPO, which optimizes the reverse process, we optimize an adva…
cs.LG2026
ML-Tool-Bench: Tool-Augmented Planning for ML Tasks
Yaswanth Chittepu, Raghavendra Addanki, Tung Mai +2
The development of autonomous machine learning (ML) agents capable of end-to-end data science workflows represents a significant frontier in artificial intelligence. These agents m…
cs.CL2026
Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization
Subhojyoti Mukherjee, Viet Dac Lai, Raghavendra Addanki +6
Offline reinforcement learning (RL) is a variant of RL where the policy is learned from a previously collected dataset of trajectories and rewards. In our work, we propose a practi…