3 papers
cs.CL2026
SafeRun: Enabling Determinism in LLM Planning for Running
Meilin Chen, Zepeng Zhai, Jiaxuan Zhao +1
Large Language Models enable flexible natural-language planning but remain unreliable in determinism-critical domains due to their probabilistic nature. This limitation is especial…
cs.LG2026
Rewards as Labels: Revisiting RLVR from a Classification Perspective
Zepeng Zhai, Meilin Chen, Jiaxuan Zhao +3
Reinforcement Learning with Verifiable Rewards has recently advanced the capabilities of Large Language Models in complex reasoning tasks by providing explicit rule-based supervisi…
cs.CL2025
Beyond the Next Token: Towards Prompt-Robust Zero-Shot Classification via Efficient Multi-Token Prediction
Junlang Qian, Zixiao Zhu, Hanzhang Zhou +3
Zero-shot text classification typically relies on prompt engineering, but the inherent prompt brittleness of large language models undermines its reliability. Minor changes in prom…