← Search

Yangzhen Wu

2 accepted papers

2025

Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for LLM Problem-Solving

ICLR 2025poster

While the scaling laws of large language models (LLMs) training have been extensively studied, optimal inference configurations of LLMs remain underexplored. We study inference scaling laws (aka test-time scaling laws) and compute-optimal inference, focusing on the trade-offs between model sizes an…

Cited by 10SourcePDFScholar
2025

The Lessons of Developing Process Reward Models in Mathematical Reasoning

ACL 2025finding

Process Reward Models (PRMs) aim to identify and mitigate intermediate errors in the reasoning processes in mathematical reasoning of Large Language Models (LLMs).However, the development of effective PRMs faces significant challenges, particularly in data annotation and evaluation methodologies.In…