Summary of Grid and Road Expressions Are Complementary For Trajectory Representation Learning, by Silin Zhou et al.
Grid and Road Expressions Are Complementary for Trajectory Representation Learningby Silin Zhou, Shuo Shang, Lisi…
Grid and Road Expressions Are Complementary for Trajectory Representation Learningby Silin Zhou, Shuo Shang, Lisi…
LLaSA: Large Language and Structured Data Assistantby Yao Xu, Shizhu He, Jiabei Chen, Zeng Xiangrong,…
ScaleKD: Strong Vision Transformers Could Be Excellent Teachersby Jiawei Fan, Chao Li, Xiaolong Liu, Anbang…
Moving Off-the-Grid: Scene-Grounded Video Representationsby Sjoerd van Steenkiste, Daniel Zoran, Yi Yang, Yulia Rubanova, Rishabh…
Rethinking Decoders for Transformer-based Semantic Segmentation: A Compression Perspectiveby Qishuai Wen, Chun-Guang LiFirst submitted to…
LLaMo: Large Language Model-based Molecular Graph Assistantby Jinyoung Park, Minseong Bae, Dohwan Ko, Hyunwoo J.…
Robust and Unbounded Length Generalization in Autoregressive Transformer-Based Text-to-Speechby Eric Battenberg, RJ Skerry-Ryan, Daisy Stanton,…
VEMOCLAP: A video emotion classification web applicationby Serkan Sulun, Paula Viana, Matthew E. P. DaviesFirst…
Multi-Agent Reinforcement Learning with Selective State-Space Modelsby Jemma Daniel, Ruan de Kock, Louay Ben Nessir,…
Generative Diffusion Models for Sequential Recommendationsby Sharare Zolghadr, Ole Winther, Paul JehaFirst submitted to arxiv…