mlsanityData to 14 Oct 2026

Task Agnostic and Post-hoc Unseen Distribution Detection

arXiv 2207.13083 ↗First posted 26 Jul 2022cs.LG cs.AI cs.CVcited by 8

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Abstract (arXiv)

Despite the recent advances in out-of-distribution(OOD) detection, anomaly detection, and uncertainty estimation tasks, there do not exist a task-agnostic and post-hoc approach. To address this limitation, we design a novel clustering-based ensembling method, called Task Agnostic and Post-hoc Unseen Distribution Detection (TAPUDD) that utilizes the features extracted from the model trained on a specific task. Explicitly, it comprises of TAP-Mahalanobis, which clusters the training datasets' features and determines the minimum Mahalanobis distance of the test sample from all clusters. Further, we propose the Ensembling module that aggregates the computation of iterative TAP-Mahalanobis for a different number of clusters to provide reliable and efficient cluster computation. Through extensive experiments on synthetic and real-world datasets, we observe that our approach can detect unseen samples effectively across diverse tasks and performs better or on-par with the existing baselines. To this end, we eliminate the necessity of determining the optimal value of the number of clusters and demonstrate that our method is more viable for large-scale classification tasks.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 39 of its 61 references that are in the map. First posted on arXiv 26 Jul 2022.

Builds on

39 of 61 references.

References · 39

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27 more
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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 1; 2024: 4; 2025: 1; 2026: 1.

8 papers.

  1. 2024ARGS: Alignment as Reward-Guided Searchcited by 103
  2. 2024Process Reward Model with Q-Value Rankingscited by 80
  3. 2024Towards Explainable Artificial Intelligence (XAI): A Data Mining Perspectivecited by 9
  4. 2024On the Learnability of Out-of-distribution Detectioncited by 8
  5. 2022Automatic Detection of Noisy Electrocardiogram Signals without Explicit Noise Labelscited by 2
  6. 2023VisAlign: Dataset for Measuring the Degree of Alignment between AI and Humans in Visual Perceptioncited by 1
  7. 2025Finer Disentanglement of Aleatoric Uncertainty Can Accelerate Chemical Histopathology Imagingcited by 1
  8. 2026The Invisible Gorilla Effect in Out-of-distribution Detectioncited by 0