1 citations · 2 across the 6 of their papers we have counts for
7 papers
From Data to Program: Fast & Direct Generative Program Inference from Empirical Data
Simon Klüttermann, Xueying Ding, Leman Akoglu
Estimating probability densities from a finite set of samples typically requires dataset-specific model fitting. We introduce PRODiGI, a pretrained data-to-program model that infer…
MacrOData: New Benchmarks of Thousands of Datasets for Tabular Outlier Detection
Xueying Ding, Simon Klüttermann, Haomin Wen +2
Quality benchmarks are essential for fairly and accurately tracking scientific progress and enabling practitioners to make informed methodological choices. Outlier detection (OD) o…
From Zero to Hero: Advancing Zero-Shot Foundation Models for Tabular Outlier Detection
Xueying Ding, Haomin Wen, Simon Klüttermann +1
Outlier detection (OD) is widely used in practice; but its effective deployment on new tasks is hindered by lack of labeled outliers, which makes algorithm and hyperparameter selec…
Hierarchical Token Prepending: Enhancing Information Flow in Decoder-based LLM Embeddings
Xueying Ding, Xingyue Huang, Mingxuan Ju +5
Large language models produce powerful text embeddings, but their causal attention mechanism restricts the flow of information from later to earlier tokens, degrading representatio…
Outlier Detection Bias Busted: Understanding Sources of Algorithmic Bias through Data-centric Factors
Xueying Ding, Rui Xi, Leman Akoglu
The astonishing successes of ML have raised growing concern for the fairness of modern methods when deployed in real world settings. However, studies on fairness have mostly focuse…
Unified Discrete Diffusion for Categorical Data
Lingxiao Zhao, Xueying Ding, Lijun Yu +1
Discrete diffusion models have seen a surge of attention with applications on naturally discrete data such as language and graphs. Although discrete-time discrete diffusion has bee…
Pard: Permutation-Invariant Autoregressive Diffusion for Graph Generation
Lingxiao Zhao, Xueying Ding, Leman Akoglu
Graph generation has been dominated by autoregressive models due to their simplicity and effectiveness, despite their sensitivity to ordering. Yet diffusion models have garnered in…