1 citations · 3 across the 6 of their papers we have counts for
7 papers
Cross-Embodiment Causal Transfer from Human Videos to Robot Manipulation
Xingyu Zhang, Yingchao Li, Peizheng Guo +3
Scaling robot manipulation models requires large amounts of interaction data, yet collecting diverse real-robot experience remains costly. Human manipulation videos, in contrast, p…
On the Plasticity and Stability for Post-Training Large Language Models
Wenwen Qiang, Ziyin Gu, Jiahuan Zhou +4
Training stability remains a critical bottleneck for Group Relative Policy Optimization (GRPO), often manifesting as a trade-off between reasoning plasticity and general capability…
Self-Supervised Representation Learning with Meta Comprehensive Regularization
Huijie Guo, Ying Ba, Jie Hu +3
Self-Supervised Learning (SSL) methods harness the concept of semantic invariance by utilizing data augmentation strategies to produce similar representations for different deforma…
Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective
Qirui Ji, Jiangmeng Li, Jie Hu +3
Graph contrastive learning is a general learning paradigm excelling at capturing invariant information from diverse perturbations in graphs. Recent works focus on exploring the str…
Information Theory-Guided Heuristic Progressive Multi-View Coding
Jiangmeng Li, Hang Gao, Wenwen Qiang +1
Multi-view representation learning aims to capture comprehensive information from multiple views of a shared context. Recent works intuitively apply contrastive learning to differe…
Intriguing Property and Counterfactual Explanation of GAN for Remote Sensing Image Generation
Xingzhe Su, Wenwen Qiang, Jie Hu +3
Generative adversarial networks (GANs) have achieved remarkable progress in the natural image field. However, when applying GANs in the remote sensing (RS) image generation task, a…
Information Theory-Guided Heuristic Progressive Multi-View Coding
Jiangmeng Li, Wenwen Qiang, Hang Gao +5
Multi-view representation learning captures comprehensive information from multiple views of a shared context. Recent works intuitively apply contrastive learning (CL) to learn rep…