activity
20232026
most citedODesign: A World Model for Biomolecular Interaction Design

3 citations · 14 across the 33 of their papers we have counts for

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10 papers · 1 filter

cs.CV2026

Struct-Searcher: Agentic Structural Thinking Advances Multimodal Deep Information Seeking

Fan Zhang, Vireo Zhang, Shengju Qian +7

Deep research agents have attracted increasing attention for their ability to collect large-scale online information to acquire target knowledge, with recent efforts shifting from…

cs.CV2026

SurgLQA: Scalable Long-Horizon Surgical Video Question Answering

Diandian Guo, Xikai Yang, Ruiyang Li +2

Surgical Video Question Answering (VideoQA) provides a promising paradigm for dynamic intraoperative interpretation, enabling real-time decision support and context-aware retrieval…

cs.CV2026

Med-Evo: Test-time Self-evolution for Medical Multimodal Large Language Models

Dunyuan Xu, Xikai Yang, Juzheng Miao +3

Medical Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities across diverse healthcare tasks. However, current post-training strategies, such as super…

cs.CV2025

REAR: Rethinking Visual Autoregressive Models via Generator-Tokenizer Consistency Regularization

Qiyuan He, Yicong Li, Haotian Ye +6

Visual autoregressive (AR) generation offers a promising path toward unifying vision and language models, yet its performance remains suboptimal against diffusion models. Prior wor…

cs.CV2025

MME-Emotion: A Holistic Evaluation Benchmark for Emotional Intelligence in Multimodal Large Language Models

Fan Zhang, Zebang Cheng, Chong Deng +18

Recent advances in multimodal large language models (MLLMs) have catalyzed transformative progress in affective computing, enabling models to exhibit emergent emotional intelligenc…

cs.CV20241 cited

Point Cloud Understanding via Attention-Driven Contrastive Learning

Yi Wang, Jiaze Wang, Ziyu Guo +5

Recently Transformer-based models have advanced point cloud understanding by leveraging self-attention mechanisms, however, these methods often overlook latent information in less…