Papers by Mengyue Yang

2 papers
CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challenges (2026.findings-acl)

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Challenge: Increasing saturation of web data limits further scaling of model intelligence.
Approach: They propose a benchmark to evaluate machine creativity in code generation that combines combinatorial and exploratory creativity through reverse engineering and self-play.
Outcome: The proposed benchmark targets combinatorial and exploratory creativity through reverse engineering and self-play.
A Comprehensive Survey of Process Reward Models: Data Generation, Model Construction, and Usage (2026.acl-long)

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Challenge: Large Language Models (LLMs) have advanced reasoning ability, yet conventional alignment remains dominated by outcome reward models that judge only final answers.
Approach: They summarize applications across math, code, text, multimodal reasoning, robotics, and agents . goal is to clarify design spaces, reveal open challenges, and guide future research toward fine-grained, robust reasoning alignment.
Outcome: The proposed model enables finer credit assignment, richer diagnostics, and improved robustness.

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