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mahalanobis distance

67 papers

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MD

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metric learning (1190) out-of-distribution detection (617) distance metric (84) distance metric learning (54) representation learning (6206) kernel methods (1097) mahalanobis metric (6) support vector machine (978) large margin (23) structured prediction (396)

Papers

Verifiable LLM-Generated Text Detection via Projected Semantic-Structural Distributions ACL 2026
Class Distillation with Mahalanobis Contrast: An Efficient Training Paradigm for Pragmatic Language Understanding Tasks ACL 2025
Max-Mahalanobis Anchors Guidance for Multi-View Clustering AAAI 2025
Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models NAACL 2025
Infinite-dimensional Mahalanobis Distance with Applications to Kernelized Novelty Detection JMLR 2025
Transformer-based Joint Modelling for Automatic Essay Scoring and Off-Topic Detection COLING 2024
SimCalib: Graph Neural Network Calibration Based on Similarity between Nodes AAAI 2024
Elliptical Attention NIPS 2024
Cluster-Adaptive Network A/B Testing: From Randomization to Estimation JMLR 2024
Progressive Transformation Learning for Leveraging Virtual Images in Training CVPR 2023
Hierarchical Visual Categories Modeling: A Joint Representation Learning and Density Estimation Framework for Out-of-Distribution Detection ICCV 2023
Perceptual adjustment queries and an inverted measurement paradigm for low-rank metric learning NIPS 2023
Unsupervised Out-of-Distribution Dialect Detection with Mahalanobis Distance INTERSPEECH 2023
Learning Sample Difficulty from Pre-trained Models for Reliable Prediction NIPS 2023
Task Agnostic and Post-Hoc Unseen Distribution Detection WACV 2023
Simple and Effective Out-of-Distribution Detection via Cosine-based Softmax Loss ICCV 2023
Gradient-Based Novelty Detection Boosted by Self-Supervised Binary Classification AAAI 2022
Individual Fairness Guarantees for Neural Networks IJCAI 2022
Enhancing Few-Shot Image Classification With Unlabelled Examples WACV 2022
Measuring Biases of Word Embeddings: What Similarity Measures and Descriptive Statistics to Use? NAACL 2021
Covariance-Aware Private Mean Estimation Without Private Covariance Estimation NIPS 2021
Reliable and Trustworthy Machine Learning for Health Using Dataset Shift Detection NIPS 2021
Contrastive Out-of-Distribution Detection for Pretrained Transformers EMNLP 2021
Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection AAAI 2021
On Mahalanobis Distance in Functional Settings JMLR 2020