Summary of Confidence-aware Multi-field Model Calibration, by Yuang Zhao et al.
Confidence-Aware Multi-Field Model Calibrationby Yuang Zhao, Chuhan Wu, Qinglin Jia, Hong Zhu, Jia Yan, Libin…
Summary of Torchmd-net 2.0: Fast Neural Network Potentials For Molecular Simulations, by Raul P. Pelaez et al.
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulationsby Raul P. Pelaez, Guillem Simeon, Raimondas…
Summary of Securing Reliability: a Brief Overview on Enhancing In-context Learning For Foundation Models, by Yunpeng Huang et al.
Securing Reliability: A Brief Overview on Enhancing In-Context Learning for Foundation Modelsby Yunpeng Huang, Yaonan…
Summary of Fedbrb: An Effective Solution to the Small-to-large Scenario in Device-heterogeneity Federated Learning, by Ziyue Xu et al.
FedBRB: An Effective Solution to the Small-to-Large Scenario in Device-Heterogeneity Federated Learningby Ziyue Xu, Mingfeng…
Summary of Temporal Logic Specification-conditioned Decision Transformer For Offline Safe Reinforcement Learning, by Zijian Guo et al.
Temporal Logic Specification-Conditioned Decision Transformer for Offline Safe Reinforcement Learningby Zijian Guo, Weichao Zhou, Wenchao…
Summary of Efficient Backpropagation with Variance-controlled Adaptive Sampling, by Ziteng Wang et al.
Efficient Backpropagation with Variance-Controlled Adaptive Samplingby Ziteng Wang, Jianfei Chen, Jun ZhuFirst submitted to arxiv…
Summary of Preserving Fairness Generalization in Deepfake Detection, by Li Lin et al.
Preserving Fairness Generalization in Deepfake Detectionby Li Lin, Xinan He, Yan Ju, Xin Wang, Feng…
Summary of Stochastic Gradient Succeeds For Bandits, by Jincheng Mei and Zixin Zhong and Bo Dai and Alekh Agarwal and Csaba Szepesvari and Dale Schuurmans
Stochastic Gradient Succeeds for Banditsby Jincheng Mei, Zixin Zhong, Bo Dai, Alekh Agarwal, Csaba Szepesvari,…
Summary of Does Negative Sampling Matter? a Review with Insights Into Its Theory and Applications, by Zhen Yang et al.
Does Negative Sampling Matter? A Review with Insights into its Theory and Applicationsby Zhen Yang,…
Summary of Rime: Robust Preference-based Reinforcement Learning with Noisy Preferences, by Jie Cheng et al.
RIME: Robust Preference-based Reinforcement Learning with Noisy Preferencesby Jie Cheng, Gang Xiong, Xingyuan Dai, Qinghai…