Summary of Federated Graph Condensation with Information Bottleneck Principles, by Bo Yan et al.
Federated Graph Condensation with Information Bottleneck Principlesby Bo Yan, Sihao He, Cheng Yang, Shang Liu,…
Federated Graph Condensation with Information Bottleneck Principlesby Bo Yan, Sihao He, Cheng Yang, Shang Liu,…
KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantizationby…
Tilt your Head: Activating the Hidden Spatial-Invariance of Classifiersby Johann Schmidt, Sebastian StoberFirst submitted to…
E2GNN: Efficient Graph Neural Network Ensembles for Semi-Supervised Classificationby Xin Zhang, Daochen Zha, Qiaoyu TanFirst…
Enhancing Q-Learning with Large Language Model Heuristicsby Xiefeng WuFirst submitted to arxiv on: 6 May…
CRA5: Extreme Compression of ERA5 for Portable Global Climate and Weather Research via an Efficient…
Deep Learning for Causal Inference: A Comparison of Architectures for Heterogeneous Treatment Effect Estimationby Demetrios…
Anchored Answers: Unravelling Positional Bias in GPT-2’s Multiple-Choice Questionsby Ruizhe Li, Yanjun GaoFirst submitted to…
Beyond Unimodal Learning: The Importance of Integrating Multiple Modalities for Lifelong Learningby Fahad Sarfraz, Bahram…
Robustness of Decentralised Learning to Nodes and Data Disruptionby Luigi Palmieri, Chiara Boldrini, Lorenzo Valerio,…