Papers by Weili Cao
IR2: Information Regularization for Information Retrieval (2024.lrec-main)
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| Challenge: | Effective information retrieval (IR) in settings with limited training data remains a challenging task. |
| Approach: | They propose a technique for reducing overfitting during synthetic data generation . they use DORIS-MAE, ArguAna, and WhatsThatBook as examples . |
| Outcome: | The proposed technique outperforms previous methods and reduces cost by 50% on three recent IR tasks characterized by complex queries. |
Across Programming Language Silos: A Study on Cross-Lingual Retrieval-Augmented Code Generation (2026.findings-acl)
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Qiming Zhu, Jialun Cao, Xuanang Chen, Weili Zhang, Yaojie Lu, Hongyu Lin, Xianpei Han, Le Sun, Shing-Chi Cheung
| Challenge: | Current research on large language models with retrieval-augmented code generation (RACG) has focused on single-language settings, leaving their cross-lingual effectiveness underexplored. |
| Approach: | They construct a dataset covering 13 PLs with nearly 14K instances to study cross-lingual code knowledge transfer in RACG. |
| Outcome: | The proposed model shows unequal cross-lingual knowledge transfer even with direct injection and shows limited reliance on natural language information embedded in code when equipped with a code-specific retriever. |
Measuring Risk of Bias in Biomedical Reports: The RoBBR Benchmark (2025.emnlp-main)
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Jianyou Wang, Weili Cao, Longtian Bao, Youze Zheng, Gil Pasternak, Kaicheng Wang, Xiaoyue Wang, Ramamohan Paturi, Leon Bergen
| Challenge: | Systematic reviews should take into account the quality of available evidence, placing more weight on studies that use a valid methodology. |
| Approach: | They propose to use a risk-of-bias framework to assess the methodological strength of biomedical papers by combining expert reviewers' judgments with research paper sentences. |
| Outcome: | The proposed system measures the methodological strength of biomedical papers using the risk-of-bias framework used for systematic reviews. |