Summary of Attention Is All You Need but You Don’t Need All Of It For Inference Of Large Language Models, by Georgy Tyukin et al.
Attention Is All You Need But You Don’t Need All Of It For Inference of…
Summary of Efficient Visual Transformer by Learnable Token Merging, By Yancheng Wang et al.
Efficient Visual Transformer by Learnable Token Mergingby Yancheng Wang, Yingzhen YangFirst submitted to arxiv on:…
Summary of Toward Efficient Convolutional Neural Networks with Structured Ternary Patterns, by Christos Kyrkou
Toward Efficient Convolutional Neural Networks With Structured Ternary Patternsby Christos KyrkouFirst submitted to arxiv on:…
Summary of Hyperspectral Unmixing Under Endmember Variability: a Variational Inference Framework, by Yuening Li et al.
Hyperspectral Unmixing Under Endmember Variability: A Variational Inference Frameworkby Yuening Li, Xiao Fu, Junbin Liu,…
Summary of Nnsight and Ndif: Democratizing Access to Open-weight Foundation Model Internals, by Jaden Fiotto-kaufman et al.
NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internalsby Jaden Fiotto-Kaufman, Alexander R. Loftus,…
Summary of Bond: Aligning Llms with Best-of-n Distillation, by Pier Giuseppe Sessa et al.
BOND: Aligning LLMs with Best-of-N Distillationby Pier Giuseppe Sessa, Robert Dadashi, Léonard Hussenot, Johan Ferret,…
Summary of Universally Harmonizing Differential Privacy Mechanisms For Federated Learning: Boosting Accuracy and Convergence, by Shuya Feng et al.
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergenceby Shuya Feng, Meisam…
Summary of Forward-forward Learning Achieves Highly Selective Latent Representations For Out-of-distribution Detection in Fully Spiking Neural Networks, by Erik B. Terres-escudero et al.
Forward-Forward Learning achieves Highly Selective Latent Representations for Out-of-Distribution Detection in Fully Spiking Neural Networksby…
Summary of Realistic Evaluation Of Test-time Adaptation Algorithms: Unsupervised Hyperparameter Selection, by Sebastian Cygert et al.
Realistic Evaluation of Test-Time Adaptation Algorithms: Unsupervised Hyperparameter Selectionby Sebastian Cygert, Damian Sójka, Tomasz Trzciński,…
Summary of Enhancing Graph Neural Networks with Limited Labeled Data by Actively Distilling Knowledge From Large Language Models, By Quan Li et al.
Enhancing Graph Neural Networks with Limited Labeled Data by Actively Distilling Knowledge from Large Language…