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cs.AI2026
RPCBench: A Benchmark for Proactive Premise Critique in LLM-based Recommendation
Zhongru Chen, Yuan Wu, Yi Chang
Large language models are increasingly used as interactive recommender assistants. Their evaluation should therefore go beyond plausible item recommendation and test whether they c…
cs.AI2026
CaSKG: Counterfactual-Causal Skill Graphs for Scalable Agent Skill Retrieval
Zhiyuan Li, Linyuan Gao, Xuechun Ding +3
Reusable skill libraries allow large language model (LLM) agents to reuse procedural knowledge across tasks, but they also turn memory access into a challenging retrieval problem.…
cs.AI2026
BV-Blend: Uncertainty-Weighted Historical Baselines for Stable Critic-Free RL with Verifiable Rewards
Yupeng Chang, Yuan Wu, Yi Chang
Critic-free reinforcement learning with verifiable rewards (RLVR), exemplified by Group Relative Policy Optimization (GRPO), avoids training a value function (critic) and reduces m…