1 citations · 2 across the 10 of their papers we have counts for
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FrameScout: Scouting Query-Relevant Frames for Long Video Understanding
Haonan Hu, Shuhao Chen, Weisen Jiang +3
Long video understanding requires VideoLLMs to answer queries about videos spanning tens of minutes to hours, but such long videos produce far more visual tokens than current Video…
Heterogeneous-Modal Unsupervised Domain Adaptation via Latent Space Bridging
Jiawen Yang, Shuhao Chen, Yucong Duan +3
Unsupervised domain adaptation (UDA) effectively bridges the domain gap between a labeled source domain and an unlabeled target domain, but assumes that the two domains share the s…
Open Your Eyes: Vision Enhances Message Passing Neural Networks in Link Prediction
Yanbin Wei, Xuehao Wang, Zhan Zhuang +5
Message-passing graph neural networks (MPNNs) and structural features (SFs) are cornerstones for the link prediction task. However, as a common and intuitive mode of understanding,…
Rethinking Guidance Information to Utilize Unlabeled Samples:A Label Encoding Perspective
Yulong Zhang, Yuan Yao, Shuhao Chen +4
Empirical Risk Minimization (ERM) is fragile in scenarios with insufficient labeled samples. A vanilla extension of ERM to unlabeled samples is Entropy Minimization (EntMin), which…
VLLaVO: Mitigating Visual Gap through LLMs
Shuhao Chen, Yulong Zhang, Weisen Jiang +2
Recent advances achieved by deep learning models rely on the independent and identically distributed assumption, hindering their applications in real-world scenarios with domain sh…
Diffusion-based Target Sampler for Unsupervised Domain Adaptation
Yulong Zhang, Shuhao Chen, Yu Zhang +1
Limited transferability hinders the performance of deep learning models when applied to new application scenarios. Recently, unsupervised domain adaptation (UDA) has achieved signi…