5 papers
Delta-JEPA: Learning Action-Sensitive World Models via Latent Difference Decoding
Zhenghao Zhang, Yuanxiang Wang, Zhenyu Guan +11
Learning visual world models for planning requires compact latent dynamics that remain sensitive to actions, yet reconstruction-free joint-embedding objectives can collapse to acti…
RPO:Reinforcement Fine-Tuning with Partial Reasoning Optimization
Hongzhu Yi, Xinming Wang, Zhenghao zhang +12
Within the domain of large language models, reinforcement fine-tuning algorithms necessitate the generation of a complete reasoning trajectory beginning from the input query, which…
Dynamic Deep Graph Learning for Incomplete Multi-View Clustering with Masked Graph Reconstruction Loss
Zhenghao Zhang, Jun Xie, Xingchen Chen +11
The prevalence of real-world multi-view data makes incomplete multi-view clustering (IMVC) a crucial research. The rapid development of Graph Neural Networks (GNNs) has established…
JTCSE: Joint Tensor-Modulus Constraints and Cross-Attention for Unsupervised Contrastive Learning of Sentence Embeddings
Tianyu Zong, Hongzhu Yi, Bingkang Shi +2
Unsupervised contrastive learning has become a hot research topic in natural language processing. Existing works usually aim at constraining the orientation distribution of the rep…
TNCSE: Tensor's Norm Constraints for Unsupervised Contrastive Learning of Sentence Embeddings
Tianyu Zong, Bingkang Shi, Hongzhu Yi +1
Unsupervised sentence embedding representation has become a hot research topic in natural language processing. As a tensor, sentence embedding has two critical properties: directio…