26 citations · 132 across the 36 of their papers we have counts for
12 papers · 1 filter
Beyond Single Models: Mitigating Multimodal Hallucinations via Adaptive Token Ensemble Decoding
Jinlin Li, Yuran Wang, Yifei Yuan +5
Large Vision-Language Models (LVLMs) have recently achieved impressive results in multimodal tasks such as image captioning and visual question answering. However, they remain pron…
MME-Emotion: A Holistic Evaluation Benchmark for Emotional Intelligence in Multimodal Large Language Models
Fan Zhang, Zebang Cheng, Chong Deng +18
Recent advances in multimodal large language models (MLLMs) have catalyzed transformative progress in affective computing, enabling models to exhibit emergent emotional intelligenc…
IQE-CLIP: Instance-aware Query Embedding for Zero-/Few-shot Anomaly Detection in Medical Domain
Hong Huang, Weixiang Sun, Zhijian Wu +4
Recently, the rapid advancements of vision-language models, such as CLIP, leads to significant progress in zero-/few-shot anomaly detection (ZFSAD) tasks. However, most existing CL…
A Multi-Expert Structural-Semantic Hybrid Framework for Unveiling Historical Patterns in Temporal Knowledge Graphs
Yimin Deng, Yuxia Wu, Yejing Wang +9
Temporal knowledge graph reasoning aims to predict future events with knowledge of existing facts and plays a key role in various downstream tasks. Previous methods focused on eith…
Model Merging for Knowledge Editing
Zichuan Fu, Xian Wu, Guojing Li +6
Large Language Models (LLMs) require continuous updates to maintain accurate and current knowledge as the world evolves. While existing knowledge editing approaches offer various s…
Training-free LLM Merging for Multi-task Learning
Zichuan Fu, Xian Wu, Yejing Wang +6
Large Language Models (LLMs) have demonstrated exceptional capabilities across diverse natural language processing (NLP) tasks. The release of open-source LLMs like LLaMA and Qwen…
MemeReaCon: Probing Contextual Meme Understanding in Large Vision-Language Models
Zhengyi Zhao, Shubo Zhang, Yuxi Zhang +10
Memes have emerged as a popular form of multimodal online communication, where their interpretation heavily depends on the specific context in which they appear. Current approaches…
T: An Adaptive Test-Time Scaling Strategy for Contextual Question Answering
Zhengyi Zhao, Shubo Zhang, Zezhong Wang +7
Recent advances in Large Language Models (LLMs) have demonstrated remarkable performance in Contextual Question Answering (CQA). However, prior approaches typically employ elaborat…
The Butterfly Effect in Pathology: Exploring Security in Pathology Foundation Models
Jiashuai Liu, Yingjia Shang, Yingkang Zhan +7
With the widespread adoption of pathology foundation models in both research and clinical decision support systems, exploring their security has become a critical concern. However,…
Think or Not? Exploring Thinking Efficiency in Large Reasoning Models via an Information-Theoretic Lens
Xixian Yong, Xiao Zhou, Yingying Zhang +3
The recent rise of Large Reasoning Models (LRMs) has significantly improved multi-step reasoning performance, but often at the cost of generating excessively long reasoning chains.…
CellVerse: Do Large Language Models Really Understand Cell Biology?
Fan Zhang, Tianyu Liu, Zhihong Zhu +7
Recent studies have demonstrated the feasibility of modeling single-cell data as natural languages and the potential of leveraging powerful large language models (LLMs) for underst…
Sliding Window Attention Training for Efficient Large Language Models
Zichuan Fu, Wentao Song, Yejing Wang +7
Recent advances in transformer-based Large Language Models (LLMs) have demonstrated remarkable capabilities across various tasks. However, their quadratic computational complexity…