15 citations · 26 across the 13 of their papers we have counts for
4 papers · 1 filter
GePBench: Evaluating Fundamental Geometric Perception for Multimodal Large Language Models
Shangyu Xing, Changhao Xiang, Yuteng Han +6
Geometric shapes play important roles in both physical world and human cognition. While multimodal large language models (MLLMs) have made significant advancements in visual unders…
AlignGPT: Multi-modal Large Language Models with Adaptive Alignment Capability
Fei Zhao, Taotian Pang, Chunhui Li +4
Multimodal Large Language Models (MLLMs) are widely regarded as crucial in the exploration of Artificial General Intelligence (AGI). The core of MLLMs lies in their capability to a…
Knowledge-aware Dual-side Attribute-enhanced Recommendation
Taotian Pang, Xingyu Lou, Fei Zhao +5
\textit{Knowledge-aware} recommendation methods (KGR) based on \textit{graph neural networks} (GNNs) and \textit{contrastive learning} (CL) have achieved promising performance. How…
EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models
Shangyu Xing, Fei Zhao, Zhen Wu +5
Multimodal large language models (MLLMs) have attracted increasing attention in the past few years, but they may still generate descriptions that include objects not present in the…