Hugging Face Trending Papers

A Controlled Evaluation of Curvature Inspired Scalar Feature Scaling for Domain Generalization

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The paper evaluates a narrow implementation of domain‑specific curvature called HyperDG, which rescales Euclidean encoder features during training with learned positive scalars and uses a standard linear classifier at inference. Across six conditions on four benchmark datasets (PACS, VLCS, Office Home, TerraIncognita) and 384 runs, the method’s macro performance is 1.61 percentage points below native DomainBed ERM, with no statistically significant difference after adjustment. The study concludes that this scalar‑scaling approach does not provide evidence of improvement over ERM and offers a bounded negative result for this specific training package.

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arXiv Machine Learning
Sep 18

Cross-Architecture Foundation-Model Distillation for Edge Flood Segmentation

The paper presents a method for distilling a large 300‑million‑parameter geospatial foundation model (Prithvi‑EO‑2.0) into a compact 0.7‑million‑parameter EfficientViT‑B0 student for flood segmentation. By using the teacher to supervise additional unlabeled Sentinel‑2 imagery, the student’s training set expands without new manual labels, achieving competitive performance on Sen1Floods11 and STURM‑Flood while remaining smaller and faster. After quantization, the student runs as a 1.5‑MB INT8 TensorRT engine on a Jetson Xavier NX, processing 512×512 images in 5.57 ms with ~14 MB of memory.

By Fabian Schmalstieg, Karsten Mueller, Wojciech Samek
arXiv AI
Aug 6

Adversarially Robust Abductive Fusion of Pre-trained Transformer-based Perception Models

arXiv:2608. 04190v1 Announce Type: new Abstract: Deploying pre-trained perception models in novel environments degrades their accuracy under distributional shift, and assembling them alone does not recover it: combiners such as majority voting trade recall for precision and are brittle to coordinated failures.

By Mario Leiva, Yue Ma, Qinru Qiu, Gerardo Simari, Paulo Shakarian