6 papers
eMoT: evolving Memory-of-Thought via Symbolic Anchoring and Memory Corrosion
Xiang Li, Jiwei Wei, Ke Liu +5
While Large Language Models (LLMs) achieve impressive performance on multi-step reasoning tasks, their reliability is persistently hindered by critical limitations such as unconstr…
Recent Advances in Multi-modal 3D Intelligence: A Comprehensive Survey and Evaluation
Yinjie Lei, Zixuan Wang, Feng Chen +3
Multi-modal 3D Intelligence has gained considerable attention due to its wide applications in autonomous driving and world simulation, etc. Compared to conventional single-modal 3D…
Efficient and Interpretable Multi-Agent LLM Routing via Ant Colony Optimization
Xudong Wang, Chaoning Zhang, Jiaquan Zhang +8
Large Language Model (LLM)-driven Multi-Agent Systems (MAS) have demonstrated strong capability in complex reasoning and tool use, and heterogeneous agent pools further broaden the…
Language-Guided Token Compression with Reinforcement Learning in Large Vision-Language Models
Sihan Cao, Jianwei Zhang, Pengcheng Zheng +7
Large Vision-Language Models (LVLMs) incur substantial inference costs due to the processing of a vast number of visual tokens. Existing methods typically struggle to model progres…
Implicit Counterfactual Learning for Audio-Visual Segmentation
Mingfeng Zha, Tianyu Li, Guoqing Wang +4
Audio-visual segmentation (AVS) aims to segment objects in videos based on audio cues. Existing AVS methods are primarily designed to enhance interaction efficiency but pay limited…
Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy
Yiting Yang, Hao Luo, Yuan Sun +7
A prevalent approach in Parameter-Efficient Fine-Tuning (PEFT) of pre-trained Vision Transformers (ViT) involves freezing the majority of the backbone parameters and solely learnin…