4 citations · 4 across the 5 of their papers we have counts for
5 papers
Modality Equilibrium Matters: Minor-Modality-Aware Adaptive Alternating for Cross-Modal Memory Enhancement
Xiang Shi, Rui Zhang, Jiawei Liu +3
Multimodal fusion is susceptible to modality imbalance, where dominant modalities overshadow weak ones, easily leading to biased learning and suboptimal fusion, especially for inco…
PersonaMark: Personalized LLM watermarking for model protection and user attribution
Yuehan Zhang, Peizhuo Lv, Yinpeng Liu +5
The rapid advancement of customized Large Language Models (LLMs) offers considerable convenience. However, it also intensifies concerns regarding the protection of copyright/confid…
Every Part Matters: Integrity Verification of Scientific Figures Based on Multimodal Large Language Models
Xiang Shi, Jiawei Liu, Yinpeng Liu +2
This paper tackles a key issue in the interpretation of scientific figures: the fine-grained alignment of text and figures. It advances beyond prior research that primarily dealt w…
Let's Learn Step by Step: Enhancing In-Context Learning Ability with Curriculum Learning
Yinpeng Liu, Jiawei Liu, Xiang Shi +3
Demonstration ordering, which is an important strategy for in-context learning (ICL), can significantly affects the performance of large language models (LLMs). However, most of th…
Know Where to Go: Make LLM a Relevant, Responsible, and Trustworthy Searcher
Xiang Shi, Jiawei Liu, Yinpeng Liu +2
The advent of Large Language Models (LLMs) has shown the potential to improve relevance and provide direct answers in web searches. However, challenges arise in validating the reli…