Papers by Wuqi Wang

2 papers
Sanitizing Large Language Models in Bug Detection with Data-Flow (2024.findings-emnlp)

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Challenge: Large language models (LLMs) have potential in code reasoning tasks but the hallucination effect can compromise the reliability of bug reports.
Approach: They propose a new schema of bug detection that enforces LLMs to emit data-flow paths in few-shot chain-of-thought prompting and validates them via the program-property decomposition.
Outcome: The proposed approach achieves 91.03% precision and 74.00% recall upon synthetic benchmarks and boosts precision by 21.99% with the sanitization.
Learn Like Humans: Use Meta-cognitive Reflection for Efficient Self-Improvement (2026.acl-long)

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Challenge: Existing self-improving frameworks rely on inefficient, multi-turn recursive loops that incur high computational costs.
Approach: They propose a framework that achieves efficient self-evolution within a single recurrence cycle.
Outcome: The proposed framework outperforms state-of-the-art self-evolving systems while significantly reducing computational overhead.

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