2 papers
cs.IR2026
MISO: Model-Internal-State-Guided Optimization for Ranking Models
Yongzhe Zhang, Xiaoyu Deng, Yifan He +29
Ranking models are repeatedly refined within established model families, yet the choice of which component to scale, replace, or retire is often guided by expensive trial-and-error…
cs.LG2026
TAPO: Transition-Aware Policy Optimization for LLM Agents
Cong Li, Peixi Peng, Yisen Zhao +4
Recently, Reinforcement Learning (RL) has emerged as a crucial paradigm for the post-training of Large Language Model (LLM) agents. However, existing methods predominantly rely on…