10 citations · 10 across the 3 of their papers we have counts for
4 papers
CoMerge: Conflict-Driven Preference Optimization for Multi-Task Model Merging
Mingjie Zheng, Zihao Chen, Wenqing Chen +4
Model merging provides an efficient paradigm for constructing multi-task large language models (LLMs) without full model retraining, yet it remains challenged by parameter interfer…
Learning Multi-Indicator Weights for Data Selection: A Joint Task-Model Adaptation Framework with Efficient Proxies
Jingze Song, Zihao Chen, Wenqing Chen +1
Data selection is a key component of efficient instruction tuning for large language models, as recent work has shown that data quality often matters more than data quantity. Accor…
You Augment Me: Exploring ChatGPT-based Data Augmentation for Semantic Code Search
Yanlin Wang, Lianghong Guo, Ensheng Shi +8
Code search plays a crucial role in software development, enabling developers to retrieve and reuse code using natural language queries. While the performance of code search models…
Towards an Understanding of Large Language Models in Software Engineering Tasks
Zibin Zheng, Kaiwen Ning, Qingyuan Zhong +5
Large Language Models (LLMs) have drawn widespread attention and research due to their astounding performance in text generation and reasoning tasks. Derivative products, like Chat…