{"total":22,"rows":[{"id":"2104.05833","title":"Semantic Segmentation with Generative Models: Semi-Supervised Learning and Strong Out-of-Domain Generalization","created":"2021-04-12","cited_by_count":141,"area":null},{"id":"2109.06827","title":"Types of Out-of-Distribution Texts and How to Detect Them","created":"2021-09-14","cited_by_count":80,"area":null},{"id":"2204.02169","title":"Hybrid Predictive Coding: Inferring, Fast and Slow","created":"2022-04-05","cited_by_count":26,"area":null},{"id":"2206.09880","title":"Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities","created":"2022-06-20","cited_by_count":23,"area":null},{"id":"2208.06164","title":"Joint Optimization of Ranking and Calibration with Contextualized Hybrid Model","created":"2022-08-12","cited_by_count":22,"area":null},{"id":"2105.09270","title":"Do We Really Need to Learn Representations from In-domain Data for Outlier Detection?","created":"2021-05-19","cited_by_count":16,"area":null},{"id":"2210.01742","title":"CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning","created":"2022-10-04","cited_by_count":11,"area":null},{"id":"2210.16486","title":"Learning Probabilistic Models from Generator Latent Spaces with Hat EBM","created":"2022-10-29","cited_by_count":11,"area":null},{"id":"2204.13208","title":"ELM: Embedding and Logit Margins for Long-Tail Learning","created":"2022-04-27","cited_by_count":10,"area":null},{"id":"2306.04689","title":"Multiscale Flow for Robust and Optimal Cosmological Analysis","created":"2023-06-07","cited_by_count":10,"area":null},{"id":"2106.06162","title":"Hybrid Generative-Contrastive Representation Learning","created":"2021-06-11","cited_by_count":8,"area":null},{"id":"2212.13425","title":"GEDI: GEnerative and DIscriminative Training for Self-Supervised Learning","created":"2022-12-27","cited_by_count":6,"area":null},{"id":"2106.13798","title":"Conjugate Energy-Based Models","created":"2021-06-25","cited_by_count":2,"area":null},{"id":"2401.00873","title":"Unifying Self-Supervised Clustering and Energy-Based Models","created":"2023-12-30","cited_by_count":2,"area":null},{"id":"2510.21935","title":"AutoSciDACT: Automated Scientific Discovery through Contrastive Embedding and Hypothesis Testing","created":"2025-10-24","cited_by_count":2,"area":null},{"id":"2111.01035","title":"A Unified View of cGANs with and without Classifiers","created":"2021-11-01","cited_by_count":1,"area":null},{"id":"2303.03887","title":"How to Construct Energy for Images? Denoising Autoencoder Can Be Energy Based Model","created":"2023-03-05","cited_by_count":1,"area":null},{"id":"2410.03505","title":"Classification-Denoising Networks","created":"2024-10-04","cited_by_count":1,"area":null},{"id":"2303.04187","title":"Stabilized training of joint energy-based models and their practical applications","created":"2023-03-07","cited_by_count":0,"area":null},{"id":"2303.09827","title":"DORIC : Domain Robust Fine-Tuning for Open Intent Clustering through Dependency Parsing","created":"2023-03-17","cited_by_count":0,"area":null},{"id":"2401.11199","title":"Projected Belief Networks With Discriminative Alignment for Acoustic Event Classification: Rivaling State of the Art CNNs","created":"2024-01-20","cited_by_count":0,"area":null},{"id":"2603.26261","title":"Contrastive Conformal Sets","created":"2026-03-27","cited_by_count":0,"area":null}],"next_cursor":null}