Summary of Task-oriented Communication For Graph Data: a Graph Information Bottleneck Approach, by Shujing Li et al.
Task-Oriented Communication for Graph Data: A Graph Information Bottleneck Approachby Shujing Li, Yanhu Wang, Shuaishuai…
Summary of Edge Ai: Evaluation Of Model Compression Techniques For Convolutional Neural Networks, by Samer Francy et al.
Edge AI: Evaluation of Model Compression Techniques for Convolutional Neural Networksby Samer Francy, Raghubir SinghFirst…
Summary of Foundations Of Large Language Model Compression — Part 1: Weight Quantization, by Sean I. Young
Foundations of Large Language Model Compression – Part 1: Weight Quantizationby Sean I. YoungFirst submitted…
Summary of Robust Clustering on High-dimensional Data with Stochastic Quantization, by Anton Kozyriev et al.
Robust Clustering on High-Dimensional Data with Stochastic Quantizationby Anton Kozyriev, Vladimir NorkinFirst submitted to arxiv…
Summary of One-index Vector Quantization Based Adversarial Attack on Image Classification, by Haiju Fan et al.
One-Index Vector Quantization Based Adversarial Attack on Image Classificationby Haiju Fan, Xiaona Qin, Shuang Chen,…
Summary of Compressing Vae-based Out-of-distribution Detectors For Embedded Deployment, by Aditya Bansal et al.
Compressing VAE-Based Out-of-Distribution Detectors for Embedded Deploymentby Aditya Bansal, Michael Yuhas, Arvind EaswaranFirst submitted to…
Summary of Hyper-compression: Model Compression Via Hyperfunction, by Fenglei Fan et al.
Hyper-Compression: Model Compression via Hyperfunctionby Fenglei Fan, Juntong Fan, Dayang Wang, Jingbo Zhang, Zelin Dong,…
Summary of Tinyagent: Function Calling at the Edge, by Lutfi Eren Erdogan et al.
TinyAgent: Function Calling at the Edgeby Lutfi Eren Erdogan, Nicholas Lee, Siddharth Jha, Sehoon Kim,…
Summary of On-device Ai: Quantization-aware Training Of Transformers in Time-series, by Tianheng Ling et al.
On-device AI: Quantization-aware Training of Transformers in Time-Seriesby Tianheng Ling, Gregor SchieleFirst submitted to arxiv…
Summary of Blending Low and High-level Semantics Of Time Series For Better Masked Time Series Generation, by Johan Vik Mathisen et al.
Blending Low and High-Level Semantics of Time Series for Better Masked Time Series Generationby Johan…