Summary of Scribformer: Transformer Makes Cnn Work Better For Scribble-based Medical Image Segmentation, by Zihan Li et al.
ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentationby Zihan Li, Yuan Zheng,…
Summary of Topology-informed Graph Transformer, by Yun Young Choi et al.
Topology-Informed Graph Transformerby Yun Young Choi, Sun Woo Park, Minho Lee, Youngho WooFirst submitted to…
Summary of Genformer: a Deep-learning-based Approach For Generating Multivariate Stochastic Processes, by Haoran Zhao et al.
GenFormer: A Deep-Learning-Based Approach for Generating Multivariate Stochastic Processesby Haoran Zhao, Wayne Isaac Tan UyFirst…
Summary of From Peft to Deft: Parameter Efficient Finetuning For Reducing Activation Density in Transformers, by Bharat Runwal et al.
From PEFT to DEFT: Parameter Efficient Finetuning for Reducing Activation Density in Transformersby Bharat Runwal,…
Summary of Systematic Literature Review: Computational Approaches For Humour Style Classification, by Mary Ogbuka Kenneth et al.
Systematic Literature Review: Computational Approaches for Humour Style Classificationby Mary Ogbuka Kenneth, Foaad Khosmood, Abbas…
Summary of Blackmamba: Mixture Of Experts For State-space Models, by Quentin Anthony et al.
BlackMamba: Mixture of Experts for State-Space Modelsby Quentin Anthony, Yury Tokpanov, Paolo Glorioso, Beren MillidgeFirst…
Summary of Detection Of Machine-generated Text: Literature Survey, by Dmytro Valiaiev
Detection of Machine-Generated Text: Literature Surveyby Dmytro ValiaievFirst submitted to arxiv on: 2 Jan 2024CategoriesMain:…
Summary of Linguistic-based Mild Cognitive Impairment Detection Using Informative Loss, by Ali Pourramezan Fard et al.
Linguistic-Based Mild Cognitive Impairment Detection Using Informative Lossby Ali Pourramezan Fard, Mohammad H. Mahoor, Muath…
Summary of Language-guided World Models: a Model-based Approach to Ai Control, by Alex Zhang et al.
Language-Guided World Models: A Model-Based Approach to AI Controlby Alex Zhang, Khanh Nguyen, Jens Tuyls,…
Summary of Lotr: Low Tensor Rank Weight Adaptation, by Daniel Bershatsky et al.
LoTR: Low Tensor Rank Weight Adaptationby Daniel Bershatsky, Daria Cherniuk, Talgat Daulbaev, Aleksandr Mikhalev, Ivan…