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cs.LG2026
Scaling of Capability and Efficiency at Inference Time in Large Reasoning Models
Moritz Laber, Zohair Shafi, Germans Savcisens +6
Capability and efficiency are two key dimensions of reasoning in large language models (LLMs). Capability refers to the ability to solve a given problem correctly, whereas efficien…
cs.LG2026
Beat the Counter First: A Baseline for Temporal-Graph Anomaly Detectors
Omair Shafi Ahmed, Zohair Shafi
Progress in streaming, edge-level graph anomaly detection (GAD) has been marked by increasingly elaborate architectures, from count-min-sketch chi square tests to memory-augmented…
cs.LG2026
DeepWeightFlow: Re-Basined Flow Matching for Generating Neural Network Weights
Saumya Gupta, Scott Biggs, Moritz Laber +3
Building efficient and effective generative models for neural network weights has been a research focus of significant interest that faces challenges posed by the high-dimensional…