2 citations · 5 across the 21 of their papers we have counts for
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Building A Coding Assistant via the Retrieval-Augmented Language Model
Xinze Li, Hanbin Wang, Zhenghao Liu +6
Pretrained language models have shown strong effectiveness in code-related tasks, such as code retrieval, code generation, code summarization, and code completion tasks. In this pa…
COAST: Enhancing the Code Debugging Ability of LLMs through Communicative Agent Based Data Synthesis
Weiqing Yang, Hanbin Wang, Zhenghao Liu +7
Code debugging is a vital stage of software development, essential for ensuring the reliability and performance of Large Language Models (LLMs) in the code generation task. Human d…
WorldValuesBench: A Large-Scale Benchmark Dataset for Multi-Cultural Value Awareness of Language Models
Wenlong Zhao, Debanjan Mondal, Niket Tandon +3
The awareness of multi-cultural human values is critical to the ability of language models (LMs) to generate safe and personalized responses. However, this awareness of LMs has bee…
LegalDuet: Learning Fine-grained Representations for Legal Judgment Prediction via a Dual-View Contrastive Learning
Buqiang Xu, Xin Dai, Zhenghao Liu +7
Legal Judgment Prediction (LJP) is a fundamental task of legal artificial intelligence, aiming to automatically predict the judgment outcomes of legal cases. Existing LJP models pr…