Summary of Towards Better Multi-head Attention Via Channel-wise Sample Permutation, by Shen Yuan et al.
Towards Better Multi-head Attention via Channel-wise Sample Permutationby Shen Yuan, Hongteng XuFirst submitted to arxiv…
Summary of Efficiently Scanning and Resampling Spatio-temporal Tasks with Irregular Observations, by Bryce Ferenczi et al.
Efficiently Scanning and Resampling Spatio-Temporal Tasks with Irregular Observationsby Bryce Ferenczi, Michael Burke, Tom DrummondFirst…
Summary of Improving Image Clustering with Artifacts Attenuation Via Inference-time Attention Engineering, by Kazumoto Nakamura et al.
Improving Image Clustering with Artifacts Attenuation via Inference-Time Attention Engineeringby Kazumoto Nakamura, Yuji Nozawa, Yu-Chieh…
Summary of Equivariant Neural Functional Networks For Transformers, by Viet-hoang Tran et al.
Equivariant Neural Functional Networks for Transformersby Viet-Hoang Tran, Thieu N. Vo, An Nguyen The, Tho…
Summary of Hydravit: Stacking Heads For a Scalable Vit, by Janek Haberer et al.
HydraViT: Stacking Heads for a Scalable ViTby Janek Haberer, Ali Hojjat, Olaf LandsiedelFirst submitted to…
Summary of Test Time Learning For Time Series Forecasting, by Panayiotis Christou et al.
Test Time Learning for Time Series Forecastingby Panayiotis Christou, Shichu Chen, Xupeng Chen, Parijat DubeFirst…
Summary of Low Latency Transformer Inference on Fpgas For Physics Applications with Hls4ml, by Zhixing Jiang et al.
Low Latency Transformer Inference on FPGAs for Physics Applications with hls4mlby Zhixing Jiang, Dennis Yin,…
Summary of Multi-modal Adapter For Vision-language Models, by Dominykas Seputis et al.
Multi-Modal Adapter for Vision-Language Modelsby Dominykas Seputis, Serghei Mihailov, Soham Chatterjee, Zehao XiaoFirst submitted to…
Summary of Reprogramming Foundational Large Language Models(llms) For Enterprise Adoption For Spatio-temporal Forecasting Applications: Unveiling a New Era in Copilot-guided Cross-modal Time Series Representation Learning, by Sakhinana Sagar Srinivas et al.
Reprogramming Foundational Large Language Models(LLMs) for Enterprise Adoption for Spatio-Temporal Forecasting Applications: Unveiling a New…
Summary of How Transformers Utilize Multi-head Attention in In-context Learning? a Case Study on Sparse Linear Regression, by Xingwu Chen et al.
How Transformers Utilize Multi-Head Attention in In-Context Learning? A Case Study on Sparse Linear Regressionby…