2 papers
cs.LG2026
Cliff: Learning Process Rewards from the First Mistake
Peixuan Han, Runhui Wang, Ketan Ramaneti +3
Reinforcement learning with verifiable rewards (RLVR) has emerged as a powerful paradigm for large language model (LLM) post-training, but its reliance on coarse outcome rewards le…
cs.CL2026
Can LLM Agents Stick to the Script? A Benchmark for Long-Horizon Consistency in Interactive Narratives
Yingpeng Ma, Jianhao Yan, Bei Shi +6
The rapid advancement of Large Language Models (LLMs) is revolutionizing AI for Games by enabling open-ended and fluid interactive storytelling. However, existing research has larg…