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cs.CL2026
Self-Improvement of Large Language Models: A Technical Overview and Future Outlook
Haoyan Yang, Mario Xerri, Solha Park +4
As large language models (LLMs) continue to advance, improving them solely through human supervision is becoming increasingly costly and limited in scalability. As models approach…
cs.CL2025
PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models
Mingyang Song, Zhaochen Su, Xiaoye Qu +2
Process-level Reward Models (PRMs) are crucial for complex reasoning and decision-making tasks, where each intermediate step plays an important role in the reasoning process. Since…