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cs.LG2026
ArcFlow: Training Flow Policies for Multiple Solver Budgets
Hieu Tran, Hong Yu
Flow-matching policies adjust inference cost through the number of solver steps, but reinforcement learning at a single fixed solver budget can hide degradation at cheaper deployme…
cs.LG2026
Measure First, Then Allocate: Calibrated Rollout Budgets for MCP Agents in Reinforcement Learning
Hieu Tran, Zonghai Yao, Sunjae Kwon +1
Training tool-using language models requires costly interaction, yet identical rewards within a rollout group provide no group-relative learning signal. We use reward disagreement…
cs.LG2026
Second Thoughts: Exploring and Planning through Comparative Imagination in World Models
Hieu Tran, Hong Yu
World models let agents compare imagined outcomes before acting, but an agent must still decide which alternatives to explore and when a proposed plan should replace its learned po…