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Tengfei Wen

2 accepted papers

2025

Code-SPA: Style Preference Alignment to Large Language Models for Effective and Robust Code Debugging

ACL 2025finding

Large language models (LLMs) have demonstrated impressive capabilities in coding tasks like code generation and debugging. However, code from real-world users is often poorly styled, containing various types of noise, such as structural inconsistencies, stylistic deviations and flawed test cases. To…

2024

Analyze, Generate and Refine: Query Expansion with LLMs for Zero-Shot Open-Domain QA

ACL 2024findings

Query expansion (QE) is a critical component in the open-domain question answering (OpenQA) pipeline, enhancing the retrieval performance by broadening the scope of queries with additional relevant texts. However, existing methods like GAR and EAR rely heavily on supervised training and often strugg…