7 papers
Multi-Branch Policy Optimization for Multimodal Large Language Models
Shuai Lyu, Yuning Gong, Ruiling Gao +7
Group-based reinforcement learning methods for multimodal large language models typically rely on trajectory-level credit assignment that applies a single advantage to all tokens i…
Robust Fuzzy Multi-view Learning under View Conflict
Siyuan Duan, Yuan Sun, Dezhong Peng +3
Trusted multi-view classification aims to deliver reliable fusion for accurate predictions and has recently attracted substantial attention in both academia and industry. However,…
Semantic-Consistent Bidirectional Contrastive Hashing for Noisy Multi-Label Cross-Modal Retrieval
Likang Peng, Chao Su, Wenyuan Wu +4
Cross-modal hashing (CMH) facilitates efficient retrieval across different modalities (e.g., image and text) by encoding data into compact binary representations. While recent meth…
Reliable Disentanglement Multi-view Learning Against View Adversarial Attacks
Xuyang Wang, Siyuan Duan, Qizhi Li +3
Trustworthy multi-view learning has attracted extensive attention because evidence learning can provide reliable uncertainty estimation to enhance the credibility of multi-view pre…
Robust Duality Learning for Unsupervised Visible-Infrared Person Re-Identification
Yongxiang Li, Yuan Sun, Yang Qin +3
Unsupervised visible-infrared person re-identification (UVI-ReID) aims to retrieve pedestrian images across different modalities without costly annotations, but faces challenges du…
Robust Self-Paced Hashing for Cross-Modal Retrieval with Noisy Labels
Ruitao Pu, Yuan Sun, Yang Qin +4
Cross-modal hashing (CMH) has appeared as a popular technique for cross-modal retrieval due to its low storage cost and high computational efficiency in large-scale data. Most exis…