activity
20242026
most citedMemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation

1 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.SD2026

EXAM2: Extending Audio Understanding in Multilingual and Multimodal Analysis

Jiawen Wang, Xiaoxue Gao, Zi Haur Pang +1

Recent large audio language models (LALMs) have achieved impressive progress in audio understanding. However, existing evaluations remain largely constrained to English and narrow…

cs.AI2025

Towards Closed-Loop Embodied Empathy Evolution: Probing LLM-Centric Lifelong Empathic Motion Generation in Unseen Scenarios

Jiawen Wang, Jingjing Wang Tianyang Chen, Min Zhang +1

In the literature, existing human-centric emotional motion generation methods primarily focus on boosting performance within a single scale-fixed dataset, largely neglecting the fl…

cs.AI2025

MLLMs are Deeply Affected by Modality Bias

Xu Zheng, Chenfei Liao, Yuqian Fu +15

Recent advances in Multimodal Large Language Models (MLLMs) have shown promising results in integrating diverse modalities such as texts and images. MLLMs are heavily influenced by…

cs.AI2025

Toward Super Agent System with Hybrid AI Routers

Yuhang Yao, Haixin Wang, Yibo Chen +5

AI Agents powered by Large Language Models are transforming the world through enormous applications. A super agent has the potential to fulfill diverse user needs, such as summariz…

cs.CV2025★ 1 cited

MemorySAM: Memorize Modalities and Semantics with Segment Anything Model 2 for Multi-modal Semantic Segmentation

Chenfei Liao, Xu Zheng, Yuanhuiyi Lyu +5

Research has focused on Multi-Modal Semantic Segmentation (MMSS), where pixel-wise predictions are derived from multiple visual modalities captured by diverse sensors. Recently, th…

cs.CL2024★ 1 cited

MultiClimate: Multimodal Stance Detection on Climate Change Videos

Jiawen Wang, Longfei Zuo, Siyao Peng +1

Climate change (CC) has attracted increasing attention in NLP in recent years. However, detecting the stance on CC in multimodal data is understudied and remains challenging due to…

cs.CV2024

GiMeFive: Towards Interpretable Facial Emotion Classification

Jiawen Wang, Leah Kawka

Deep convolutional neural networks have been shown to successfully recognize facial emotions for the past years in the realm of computer vision. However, the existing detection app…