Summary of Fiddler: Cpu-gpu Orchestration For Fast Inference Of Mixture-of-experts Models, by Keisuke Kamahori et al.
Fiddler: CPU-GPU Orchestration for Fast Inference of Mixture-of-Experts Modelsby Keisuke Kamahori, Tian Tang, Yile Gu,…
Summary of Semi-supervised Learning For Bilingual Lexicon Induction, by Paul Garnier and Gauthier Guinet
Semi-Supervised Learning for Bilingual Lexicon Inductionby Paul Garnier, Gauthier GuinetFirst submitted to arxiv on: 10…
Summary of Echoes Of Socratic Doubt: Embracing Uncertainty in Calibrated Evidential Reinforcement Learning, by Alex Christopher Stutts et al.
Echoes of Socratic Doubt: Embracing Uncertainty in Calibrated Evidential Reinforcement Learningby Alex Christopher Stutts, Danilo…
Summary of Efficient Incremental Belief Updates Using Weighted Virtual Observations, by David Tolpin
Efficient Incremental Belief Updates Using Weighted Virtual Observationsby David TolpinFirst submitted to arxiv on: 10…
Summary of Discriminative Adversarial Unlearning, by Rohan Sharma et al.
Discriminative Adversarial Unlearningby Rohan Sharma, Shijie Zhou, Kaiyi Ji, Changyou ChenFirst submitted to arxiv on:…
Summary of Distilling Morphology-conditioned Hypernetworks For Efficient Universal Morphology Control, by Zheng Xiong et al.
Distilling Morphology-Conditioned Hypernetworks for Efficient Universal Morphology Controlby Zheng Xiong, Risto Vuorio, Jacob Beck, Matthieu…
Summary of Prompt Learning on Temporal Interaction Graphs, by Xi Chen et al.
Prompt Learning on Temporal Interaction Graphsby Xi Chen, Siwei Zhang, Yun Xiong, Xixi Wu, Jiawei…
Summary of V-star: Training Verifiers For Self-taught Reasoners, by Arian Hosseini et al.
V-STaR: Training Verifiers for Self-Taught Reasonersby Arian Hosseini, Xingdi Yuan, Nikolay Malkin, Aaron Courville, Alessandro…
Summary of Masked Logonet: Fast and Accurate 3d Image Analysis For Medical Domain, by Amin Karimi Monsefi et al.
Masked LoGoNet: Fast and Accurate 3D Image Analysis for Medical Domainby Amin Karimi Monsefi, Payam…
Summary of Fedmia: An Effective Membership Inference Attack Exploiting “all For One” Principle in Federated Learning, by Gongxi Zhu et al.
FedMIA: An Effective Membership Inference Attack Exploiting “All for One” Principle in Federated Learningby Gongxi…