3 citations · 3 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
The First Drop of Ink: Nonlinear Impact of Distracting Information in Long-Context Reasoning
Muhan Gao, Zih-Ching Chen, Kuan-Hao Huang
As large language models are increasingly deployed in retrieval-augmented generation and agentic systems that accumulate extensive context, understanding how distracting informatio…
Visual Preference Optimization with Rubric Rewards
Ya-Qi Yu, Fangyu Hong, Xiangyang Qu +15
The effectiveness of Direct Preference Optimization (DPO) depends on preference data that reflect the quality differences that matter in multimodal tasks. Existing pipelines often…