4 papers
Compressing then Matching: An Efficient Pre-training Paradigm for Multimodal Embedding
Da Li, Yuxiao Luo, Keping Bi +7
Multimodal Large Language Models advance multimodal representation learning by acquiring transferable semantic embeddings, thereby substantially enhancing performance across a rang…
CREM: Compression-Driven Representation Enhancement for Multimodal Retrieval and Comprehension
Lihao Liu, Yan Wang, Biao Yang +10
Multimodal Large Language Models (MLLMs) have shown remarkable success in comprehension tasks such as visual description and visual question answering. However, their direct applic…
VRAgent-R1: Boosting Video Recommendation with MLLM-based Agents via Reinforcement Learning
Siran Chen, Boyu Chen, Chenyun Yu +6
Owing to powerful natural language processing and generative capabilities, large language model (LLM) agents have emerged as a promising solution for enhancing recommendation syste…
H-MBA: Hierarchical MamBa Adaptation for Multi-Modal Video Understanding in Autonomous Driving
Siran Chen, Yuxiao Luo, Yue Ma +2
With the prevalence of Multimodal Large Language Models(MLLMs), autonomous driving has encountered new opportunities and challenges. In particular, multi-modal video understanding…