6 papers
EXAONE Tabular 1.0 : Technical Report
Moonjung Eo, Min-Kook Suh, Hye-Seung Cho +4
EXAONE Tabular is a compact tabular foundation model family for classification and regression via in-context learning, producing predictions without dataset-specific gradient updat…
ReTabAD: A Benchmark for Restoring Semantic Context in Tabular Anomaly Detection
Sanghyu Yoon, Dongmin Kim, Suhee Yoon +6
In tabular anomaly detection (AD), textual semantics often carry critical signals, as the definition of an anomaly is closely tied to domain-specific context. However, existing ben…
MultiTab: A Comprehensive Benchmark Suite for Multi-Dimensional Evaluation in Tabular Domains
Kyungeun Lee, Moonjung Eo, Hye-Seung Cho +5
Despite the widespread use of tabular data in real-world applications, most benchmarks rely on average-case metrics, which fail to reveal how model behavior varies across diverse d…
ImagePiece: Content-aware Re-tokenization for Efficient Image Recognition
Seungdong Yoa, Seungjun Lee, Hyeseung Cho +2
Vision Transformers (ViTs) have achieved remarkable success in various computer vision tasks. However, ViTs have a huge computational cost due to their inherent reliance on multi-h…
Diffusion based Semantic Outlier Generation via Nuisance Awareness for Out-of-Distribution Detection
Suhee Yoon, Sanghyu Yoon, Ye Seul Sim +5
Out-of-distribution (OOD) detection, which determines whether a given sample is part of the in-distribution (ID), has recently shown promising results through training with synthet…
Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains
Kyungeun Lee, Ye Seul Sim, Hye-Seung Cho +4
The ability of deep networks to learn superior representations hinges on leveraging the proper inductive biases, considering the inherent properties of datasets. In tabular domains…