Yingying Cheng — accepted AI-conference papers

2026

CIRBench: Evaluating Large Language Models as LLVM IR Optimizers

Zi Yang, Haifeng Ding, Fei Liu, Yingying Cheng, Han Cheng, Zhilei Chai +1

ICML 2026spotlight

Large language models are beginning to introduce a new paradigm for compilation: instead of only assisting at the source level, they can operate directly on **intermediate representations (IRs)**, the compiler’s internal code representation, Early studies suggest that LLM-guided optimization can som…

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2026

Making Slow Thinking Faster: Compressing LLM Chain-of-Thought via Step Entropy

Zeju Li, Jianyuan Zhong, Ziyang Zheng, Xiangyu Wen, Zhijian Xu, Yingying Cheng +2

ICLR 2026poster

Large Language Models (LLMs) using Chain-of-Thought (CoT) prompting excel at complex reasoning but generate verbose thought processes with considerable redundancy, leading to increased inference costs and reduced efficiency. We introduce a novel CoT compression framework based on step entropy, a met…

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