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Zhaoyang Chu

3 accepted papers

2025

CodeSync: Synchronizing Large Language Models with Dynamic Code Evolution at Scale

ICML 2025poster

Large Language Models (LLMs) have exhibited exceptional performance in software engineering yet face challenges in adapting to continually evolving code knowledge, particularly the frequent updates of third-party library APIs. This limitation, rooted in the static pre-training datasets, often result…

2025

TESTEVAL: Benchmarking Large Language Models for Test Case Generation

NAACL 2025findings

For program languages, testing plays a crucial role in the software development cycle, enabling the detection of bugs, vulnerabilities, and other undesirable behaviors. To perform software testing, testers need to write code snippets that execute the program under test. Recently, researchers have re…

2025

Wait, We Don’t Need to “Wait”! Removing Thinking Tokens Improves Reasoning Efficiency

EMNLP 2025

Recent advances in large reasoning models have enabled complex, step-by-step reasoning but often introduce significant overthinking, resulting in verbose and redundant outputs that hinder efficiency. In this study, we examine whether explicit self-reflection, signaled by tokens such as “Wait” and “H

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