1 citations · 2 across the 10 of their papers we have counts for
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MIRTH: Mutual-Information Reasoning with Temporal Hubs for Vision-Language-Action Agents
Hao Sun, Yu Song, Shiyu Teng +2
VLA models have emerged as a powerful paradigm for transferring semantic knowledge from web-scale data to physical robotic control. However, current single-frame architectures suff…
Pelican-Unify 1.0: A Unified Embodied Intelligence Model for Understanding, Reasoning, Imagination and Action
Yi Zhang, Yinda Chen, Che Liu +26
We present Pelican-Unify 1.0, the first embodied foundation model trained according to the principle of unification. Pelican-Unify 1.0 uses a single VLM as a unified understanding…
Unlocking Patch-Level Features for CLIP-Based Class-Incremental Learning
Hao Sun, Zi-Jun Ding, Da-Wei Zhou
Class-Incremental Learning (CIL) enables models to continuously integrate new knowledge while mitigating catastrophic forgetting. Driven by the remarkable generalization of CLIP, l…
Power Reinforcement Post-Training of Text-to-Image Models with Super-Linear Advantage Shaping
Haoyuan Sun, Jing Wang, Yuxin Song +9
Recently, post-training methods based on reinforcement learning, with a particular focus on Group Relative Policy Optimization (GRPO), have emerged as the robust paradigm for furth…
Cross-Sample Relational Fusion: Unifying Domain Generalization and Class-Incremental Learning
Zhen-Hao Xie, Yan Wang, Hao Sun +3
Class-Incremental Learning (CIL) requires a learning system to learn new classes while retaining previously learned knowledge. However, in real-world scenarios such as autonomous d…