Summary of Ai Oversight and Human Mistakes: Evidence From Centre Court, by David Almog et al.
AI Oversight and Human Mistakes: Evidence from Centre Courtby David Almog, Romain Gauriot, Lionel Page,…
Summary of One-step Forward and Backtrack: Overcoming Zig-zagging in Loss-aware Quantization Training, by Lianbo Ma et al.
One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Trainingby Lianbo Ma, Yuee Zhou, Jianlun…
Summary of Swapnet: Efficient Swapping For Dnn Inference on Edge Ai Devices Beyond the Memory Budget, by Kun Wang et al.
SwapNet: Efficient Swapping for DNN Inference on Edge AI Devices Beyond the Memory Budgetby Kun…
Summary of Detection and Recovery Against Deep Neural Network Fault Injection Attacks Based on Contrastive Learning, by Chenan Wang et al.
Detection and Recovery Against Deep Neural Network Fault Injection Attacks Based on Contrastive Learningby Chenan…
Summary of Molpla: a Molecular Pretraining Framework For Learning Cores, R-groups and Their Linker Joints, by Mogan Gim et al.
MolPLA: A Molecular Pretraining Framework for Learning Cores, R-Groups and their Linker Jointsby Mogan Gim,…
Summary of Extrinsicaly Rewarded Soft Q Imitation Learning with Discriminator, by Ryoma Furuyama et al.
Extrinsicaly Rewarded Soft Q Imitation Learning with Discriminatorby Ryoma Furuyama, Daiki Kuyoshi, Satoshi YamaneFirst submitted…
Summary of Activity Detection For Massive Connectivity in Cell-free Networks with Unknown Large-scale Fading, Channel Statistics, Noise Variance, and Activity Probability: a Bayesian Approach, by Hao Zhang et al.
Activity Detection for Massive Connectivity in Cell-free Networks with Unknown Large-scale Fading, Channel Statistics, Noise…
Summary of In-flow: Instance Normalization Flow For Non-stationary Time Series Forecasting, by Wei Fan et al.
IN-Flow: Instance Normalization Flow for Non-stationary Time Series Forecastingby Wei Fan, Shun Zheng, Pengyang Wang,…
Summary of Graph Fairness Learning Under Distribution Shifts, by Yibo Li et al.
Graph Fairness Learning under Distribution Shiftsby Yibo Li, Xiao Wang, Yujie Xing, Shaohua Fan, Ruijia…
Summary of Hawkeye: Advancing Robust Regression with Bounded, Smooth, and Insensitive Loss Function, by Mushir Akhtar et al.
HawkEye: Advancing Robust Regression with Bounded, Smooth, and Insensitive Loss Functionby Mushir Akhtar, M. Tanveer,…