53 citations · 61 across the 5 of their papers we have counts for
5 papers
An Empirical Study on Influence-Based Pretraining Data Selection for Code Large Language Models
Chengli Xing, Zhengran Zeng, Gexiang Fang +3
Recent advancements in code large language models (Code-LLMs) have demonstrated remarkable capabilities in resolving programming related tasks. Meanwhile, researchers have recogniz…
Exploring Vision-Language Models for Imbalanced Learning
Yidong Wang, Zhuohao Yu, Jindong Wang +6
Vision-Language models (VLMs) that use contrastive language-image pre-training have shown promising zero-shot classification performance. However, their performance on imbalanced d…
Exploiting Method Names to Improve Code Summarization: A Deliberation Multi-Task Learning Approach
Rui Xie, Wei Ye, Jinan Sun +1
Code summaries are brief natural language descriptions of source code pieces. The main purpose of code summarization is to assist developers in understanding code and to reduce doc…
Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning
Wei Ye, Rui Xie, Jinglei Zhang +3
Code summarization generates brief natural language description given a source code snippet, while code retrieval fetches relevant source code given a natural language query. Since…
Exploiting Entity BIO Tag Embeddings and Multi-task Learning for Relation Extraction with Imbalanced Data
Wei Ye, Bo Li, Rui Xie +3
In practical scenario, relation extraction needs to first identify entity pairs that have relation and then assign a correct relation class. However, the number of non-relation ent…