Summary of Geographical Node Clustering and Grouping to Guarantee Data Iidness in Federated Learning, by Minkwon Lee et al.
Geographical Node Clustering and Grouping to Guarantee Data IIDness in Federated Learningby Minkwon Lee, Hyoil…
Geographical Node Clustering and Grouping to Guarantee Data IIDness in Federated Learningby Minkwon Lee, Hyoil…
Reducing annotator bias by belief elicitationby Terne Sasha Thorn Jakobsen, Andreas Bjerre-Nielsen, Robert BöhmFirst submitted…
InternLM2.5-StepProver: Advancing Automated Theorem Proving via Expert Iteration on Large-Scale LEAN Problemsby Zijian Wu, Suozhi…
AutoTrain: No-code training for state-of-the-art modelsby Abhishek ThakurFirst submitted to arxiv on: 21 Oct 2024CategoriesMain:…
Who’s Who: Large Language Models Meet Knowledge Conflicts in Practiceby Quang Hieu Pham, Hoang Ngo,…
Unleashing the Potential of Vision-Language Pre-Training for 3D Zero-Shot Lesion Segmentation via Mask-Attribute Alignmentby Yankai…
GIG: Graph Data Imputation With Graph Differential Dependenciesby Jiang Hua, Michael Bewong, Selasi Kwashie, MD…
Alchemy: Amplifying Theorem-Proving Capability through Symbolic Mutationby Shaonan Wu, Shuai Lu, Yeyun Gong, Nan Duan,…
DeepIcon: A Hierarchical Network for Layer-wise Icon Vectorizationby Qi Bing, Chaoyi Zhang, Weidong CaiFirst submitted…
Learning to Synthesize Graphics Programs for Geometric Artworksby Qi Bing, Chaoyi Zhang, Weidong CaiFirst submitted…