1 citations · 2 across the 10 of their papers we have counts for
11 papers
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…
EPIC: Efficient Prompt Interaction for Text-Image Classification
Xinyao Yu, Hao Sun, Zeyu Ling +5
In recent years, large-scale pre-trained multimodal models (LMMs) generally emerge to integrate the vision and language modalities, achieving considerable success in multimodal tas…
One Framework to Rule Them All: Unifying Multimodal Tasks with LLM Neural-Tuning
Hao Sun, Yu Song, Jiaqing Liu +3
Large-scale models have exhibited remarkable capabilities across diverse domains, including automated medical services and intelligent customer support. However, as most large mode…
Robust Latent Representation Tuning for Image-text Classification
Hao Sun, Yu Song
Large models have demonstrated exceptional generalization capabilities in computer vision and natural language processing. Recent efforts have focused on enhancing these models wit…
Multimodal Infusion Tuning for Large Models
Hao Sun, Yu Song, Xinyao Yu +3
Recent advancements in large-scale models have showcased remarkable generalization capabilities in various tasks. However, integrating multimodal processing into these models prese…
Memory-Inspired Temporal Prompt Interaction for Text-Image Classification
Xinyao Yu, Hao Sun, Ziwei Niu +4
In recent years, large-scale pre-trained multimodal models (LMM) generally emerge to integrate the vision and language modalities, achieving considerable success in various natural…
Modality-invariant and Specific Prompting for Multimodal Human Perception Understanding
Hao Sun, Ziwei Niu, Xinyao Yu +3
Understanding human perceptions presents a formidable multimodal challenge for computers, encompassing aspects such as sentiment tendencies and sense of humor. While various method…