1 citations · 1 across the 4 of their papers we have counts for
4 papers
ASPO: Adaptive Sentence-Level Preference Optimization for Fine-Grained Multimodal Reasoning
Yeyuan Wang, Dehong Gao, Rujiao Long +4
Direct Preference Optimization (DPO) has gained significant attention for its simplicity and computational efficiency in aligning large language models (LLMs). Recent advancements…
Instruction-Aligned Visual Attention for Mitigating Hallucinations in Large Vision-Language Models
Bin Li, Dehong Gao, Yeyuan Wang +4
Despite the significant success of Large Vision-Language models(LVLMs), these models still suffer hallucinations when describing images, generating answers that include non-existen…
CoF: Coarse to Fine-Grained Image Understanding for Multi-modal Large Language Models
Yeyuan Wang, Dehong Gao, Bin Li +7
The impressive performance of Large Language Model (LLM) has prompted researchers to develop Multi-modal LLM (MLLM), which has shown great potential for various multi-modal tasks.…
MoDULA: Mixture of Domain-Specific and Universal LoRA for Multi-Task Learning
Yufei Ma, Zihan Liang, Huangyu Dai +9
The growing demand for larger-scale models in the development of \textbf{L}arge \textbf{L}anguage \textbf{M}odels (LLMs) poses challenges for efficient training within limited comp…