17 citations · 23 across the 16 of their papers we have counts for
5 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…
Extroversion or Introversion? Controlling The Personality of Your Large Language Models
Yanquan Chen, Zhen Wu, Junjie Guo +2
Large language models (LLMs) exhibit robust capabilities in text generation and comprehension, mimicking human behavior and exhibiting synthetic personalities. However, some LLMs h…
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…
Emotion-Anchored Contrastive Learning Framework for Emotion Recognition in Conversation
Fangxu Yu, Junjie Guo, Zhen Wu +1
Emotion Recognition in Conversation (ERC) involves detecting the underlying emotion behind each utterance within a conversation. Effectively generating representations for utteranc…
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…