{"total":23,"rows":[{"id":"2305.08455","title":"Document Understanding Dataset and Evaluation (DUDE)","created":"2023-05-15","cited_by_count":135,"area":null},{"id":"2210.03736","title":"Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis","created":"2022-10-05","cited_by_count":63,"area":null},{"id":"2212.12053","title":"On Calibrating Semantic Segmentation Models: Analyses and An Algorithm","created":"2022-12-22","cited_by_count":25,"area":null},{"id":"2307.00934","title":"Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration","created":"2023-07-03","cited_by_count":19,"area":null},{"id":"2311.03570","title":"Cal-DETR: Calibrated Detection Transformer","created":"2023-11-06","cited_by_count":11,"area":null},{"id":"2403.17010","title":"Calib3D: Calibrating Model Preferences for Reliable 3D Scene Understanding","created":"2024-03-25","cited_by_count":11,"area":null},{"id":"2405.20459","title":"On Calibration of Object Detectors: Pitfalls, Evaluation and Baselines","created":"2024-05-30","cited_by_count":11,"area":null},{"id":"2306.04985","title":"Beyond Probability Partitions: Calibrating Neural Networks with Semantic Aware Grouping","created":"2023-06-08","cited_by_count":10,"area":null},{"id":"2312.06645","title":"Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection","created":"2023-12-11","cited_by_count":9,"area":null},{"id":"2409.18026","title":"ReliOcc: Towards Reliable Semantic Occupancy Prediction via Uncertainty Learning","created":"2024-09-26","cited_by_count":6,"area":null},{"id":"2312.06106","title":"AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images","created":"2023-12-11","cited_by_count":3,"area":null},{"id":"2407.02386","title":"OpenSlot: Mixed Open-Set Recognition with Object-Centric Learning","created":"2024-07-02","cited_by_count":2,"area":null},{"id":"2412.01782","title":"Uncertainty Quantification in Detection Transformers: Object-Level Calibration and Image-Level Reliability","created":"2024-12-02","cited_by_count":2,"area":null},{"id":"2309.00464","title":"A Theoretical and Practical Framework for Evaluating Uncertainty Calibration in Object Detection","created":"2023-09-01","cited_by_count":1,"area":null},{"id":"2310.06380","title":"CAST: Cluster-Aware Self-Training for Tabular Data via Reliable Confidence","created":"2023-10-10","cited_by_count":1,"area":null},{"id":"2402.03292","title":"Detecting Out-of-Distribution Objects through Class-Conditioned Inpainting","created":"2024-02-05","cited_by_count":1,"area":null},{"id":"2409.16678","title":"TSBP: Improving Object Detection in Histology Images via Test-time Self-guided Bounding-box Propagation","created":"2024-09-25","cited_by_count":1,"area":null},{"id":"2510.19330","title":"Exploring Scale Shift in Crowd Localization under the Context of Domain Generalization","created":"2025-10-22","cited_by_count":1,"area":null},{"id":"2605.05328","title":"Query2Uncertainty: Robust Uncertainty Quantification and Calibration for 3D Object Detection under Distribution Shift","created":"2026-05-06","cited_by_count":1,"area":null},{"id":"2605.24722","title":"Calibrating Probabilistic Object Detectors with Annotator Disagreement","created":"2026-05-23","cited_by_count":0,"area":null},{"id":"2607.29040","title":"Rethinking Detection Calibration: A Coordinate and Direction Perspective","created":"2026-07-31","cited_by_count":0,"area":null},{"id":"2608.17917","title":"Comparative Study of Out-of-the-Box Technology for Automatic Target Detection and Recognition","created":"2026-08-18","cited_by_count":0,"area":null},{"id":"2609.36426","title":"Losing the name before the box: measuring and repairing what narrow fine-tuning costs a detector outside its deployment vocabulary","created":"2026-09-29","cited_by_count":0,"area":null}],"next_cursor":null}