13 papers
Geometry-Guided Self-Supervision for Ultra-Fine-Grained Recognition with Limited Data
Shijie Wang, Yadan Luo, Zijian Wang +3
This paper investigates the intrinsic geometrical features of highly similar objects and introduces a general self-supervised framework called the Geometric Attribute Exploration N…
MambaNetBurst: Direct Byte-level Network Traffic Classification without Tokenization or Pretraining
Gayan K. Kulatilleke, Siamak Layeghy, Mahsa Baktashmotlagh +1
We present MambaNetBurst, a compact tokenizer-free byte-level sequence classifier for network burst classification based on a Mamba-2 backbone. In contrast to most recent strong tr…
Divide-and-Conquer Approach to Holistic Cognition in High-Similarity Contexts with Limited Data
Shijie Wang, Zijian Wang, Yadan Luo +3
Ultra-fine-grained visual categorization (Ultra-FGVC) aims to classify highly similar subcategories within fine-grained objects using limited training samples. However, holistic ye…
GIQ: Benchmarking 3D Geometric Reasoning of Vision Foundation Models with Simulated and Real Polyhedra
Mateusz Michalkiewicz, Anekha Sokhal, Tadeusz Michalkiewicz +4
Modern monocular 3D reconstruction methods and vision-language models (VLMs) demonstrate impressive results on standard benchmarks, yet recent works cast doubt on their true unders…
Minimal Semantic Sufficiency Meets Unsupervised Domain Generalization
Tan Pan, Kaiyu Guo, Dongli Xu +8
The generalization ability of deep learning has been extensively studied in supervised settings, yet it remains less explored in unsupervised scenarios. Recently, the Unsupervised…
ALSA: Anchors in Logit Space for Out-of-Distribution Accuracy Estimation
Chenzhi Liu, Mahsa Baktashmotlagh, Yanran Tang +2
Estimating model accuracy on unseen, unlabeled datasets is crucial for real-world machine learning applications, especially under distribution shifts that can degrade performance.…