Summary of Seeing Syntax: Uncovering Syntactic Learning Limitations in Vision-language Models, by Sri Harsha Dumpala et al.
Seeing Syntax: Uncovering Syntactic Learning Limitations in Vision-Language Modelsby Sri Harsha Dumpala, David Arps, Sageev…
Summary of Dense Depth From Event Focal Stack, by Kenta Horikawa and Mariko Isogawa and Hideo Saito and Shohei Mori
Dense Depth from Event Focal Stackby Kenta Horikawa, Mariko Isogawa, Hideo Saito, Shohei MoriFirst submitted…
Summary of Progressive Multi-granular Alignments For Grounded Reasoning in Large Vision-language Models, by Quang-hung Le et al.
Progressive Multi-granular Alignments for Grounded Reasoning in Large Vision-Language Modelsby Quang-Hung Le, Long Hoang Dang,…
Summary of Why Does Dropping Edges Usually Outperform Adding Edges in Graph Contrastive Learning?, by Yanchen Xu et al.
Why Does Dropping Edges Usually Outperform Adding Edges in Graph Contrastive Learning?by Yanchen Xu, Siqi…
Summary of Difframan: a Conditional Latent Denoising Diffusion Probabilistic Model For Bacterial Raman Spectroscopy Identification Under Limited Data Conditions, by Haiming Yao et al.
DiffRaman: A Conditional Latent Denoising Diffusion Probabilistic Model for Bacterial Raman Spectroscopy Identification Under Limited…
Summary of Learn How to Query From Unlabeled Data Streams in Federated Learning, by Yuchang Sun and Xinran Li and Tao Lin and Jun Zhang
Learn How to Query from Unlabeled Data Streams in Federated Learningby Yuchang Sun, Xinran Li,…
Summary of Wasserstein Distance Rivals Kullback-leibler Divergence For Knowledge Distillation, by Jiaming Lv et al.
Wasserstein Distance Rivals Kullback-Leibler Divergence for Knowledge Distillationby Jiaming Lv, Haoyuan Yang, Peihua LiFirst submitted…
Summary of How Vision-language Tasks Benefit From Large Pre-trained Models: a Survey, by Yayun Qi et al.
How Vision-Language Tasks Benefit from Large Pre-trained Models: A Surveyby Yayun Qi, Hongxi Li, Yiqi…
Summary of Agmixup: Adaptive Graph Mixup For Semi-supervised Node Classification, by Weigang Lu et al.
AGMixup: Adaptive Graph Mixup for Semi-supervised Node Classificationby Weigang Lu, Ziyu Guan, Wei Zhao, Yaming…
Summary of Dg-mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models, by Haonan Yuan et al.
DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Modelsby Haonan Yuan,…