{"total":90,"rows":[{"id":"2210.11006","title":"SimpleClick: Interactive Image Segmentation with Simple Vision Transformers","created":"2022-10-20","cited_by_count":111,"area":null},{"id":"2111.15430","title":"The Devil is in the Margin: Margin-based Label Smoothing for Network Calibration","created":"2021-11-30","cited_by_count":91,"area":null},{"id":"2308.01222","title":"Calibration in Deep Learning: A Survey of the State-of-the-Art","created":"2023-08-02","cited_by_count":75,"area":null},{"id":"2112.10327","title":"Classifier Calibration: A survey on how to assess and improve predicted class probabilities","created":"2021-12-20","cited_by_count":73,"area":null},{"id":"2203.13834","title":"A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration","created":"2022-03-25","cited_by_count":49,"area":null},{"id":"2207.06211","title":"Sample-dependent Adaptive Temperature Scaling for Improved Calibration","created":"2022-07-13","cited_by_count":48,"area":null},{"id":"2207.05282","title":"PseudoClick: Interactive Image Segmentation with Click Imitation","created":"2022-07-12","cited_by_count":42,"area":null},{"id":"2102.07856","title":"Don't Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification","created":"2021-02-15","cited_by_count":39,"area":null},{"id":"2310.14230","title":"A comprehensive survey on deep active learning in medical image analysis","created":"2023-10-22","cited_by_count":35,"area":null},{"id":"2105.04290","title":"Meta-Cal: Well-controlled Post-hoc Calibration by Ranking","created":"2021-05-10","cited_by_count":33,"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":"2208.00461","title":"Adaptive Temperature Scaling for Robust Calibration of Deep Neural Networks","created":"2022-07-31","cited_by_count":24,"area":null},{"id":"2308.10297","title":"DomainAdaptor: A Novel Approach to Test-time Adaptation","created":"2023-08-20","cited_by_count":20,"area":null},{"id":"2109.05263","title":"Class-Distribution-Aware Calibration for Long-Tailed Visual Recognition","created":"2021-09-11","cited_by_count":19,"area":null},{"id":"2308.11990","title":"RankMixup: Ranking-Based Mixup Training for Network Calibration","created":"2023-08-23","cited_by_count":19,"area":null},{"id":"2303.11298","title":"Reliability in Semantic Segmentation: Are We on the Right Track?","created":"2023-03-20","cited_by_count":16,"area":null},{"id":"2308.11911","title":"ACLS: Adaptive and Conditional Label Smoothing for Network Calibration","created":"2023-08-23","cited_by_count":15,"area":null},{"id":"2211.15088","title":"Class Adaptive Network Calibration","created":"2022-11-28","cited_by_count":13,"area":null},{"id":"2402.05806","title":"On Temperature Scaling and Conformal Prediction of Deep Classifiers","created":"2024-02-08","cited_by_count":13,"area":null},{"id":"2411.01639","title":"Know Where You're Uncertain When Planning with Multimodal Foundation Models: A Formal Framework","created":"2024-11-03","cited_by_count":13,"area":null},{"id":"2303.06268","title":"Trust your neighbours: Penalty-based constraints for model calibration","created":"2023-03-11","cited_by_count":12,"area":null},{"id":"2303.14404","title":"Bridging Precision and Confidence: A Train-Time Loss for Calibrating Object Detection","created":"2023-03-25","cited_by_count":12,"area":null},{"id":"2311.16914","title":"Brain-ID: Learning Contrast-agnostic Anatomical Representations for Brain Imaging","created":"2023-11-28","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":"2208.03284","title":"Interpretable Uncertainty Quantification in AI for HEP","created":"2022-08-05","cited_by_count":8,"area":null},{"id":"2303.01099","title":"Multi-Head Multi-Loss Model Calibration","created":"2023-03-02","cited_by_count":8,"area":null},{"id":"2312.13116","title":"VSR-Net: Vessel-like Structure Rehabilitation Network with Graph Clustering","created":"2023-12-20","cited_by_count":8,"area":null},{"id":"2407.17377","title":"Entropy Reweighted Conformal Classification","created":"2024-07-24","cited_by_count":8,"area":null},{"id":"2509.00549","title":"A Modality-agnostic Multi-task Foundation Model for Human Brain Imaging","created":"2025-08-30","cited_by_count":8,"area":null},{"id":"2104.11949","title":"Automatic Diagnosis of COVID-19 from CT Images using CycleGAN and Transfer Learning","created":"2021-04-24","cited_by_count":7,"area":null},{"id":"2306.00740","title":"On the Limitations of Temperature Scaling for Distributions with Overlaps","created":"2023-06-01","cited_by_count":7,"area":null},{"id":"2401.14487","title":"Neighbor-Aware Calibration of Segmentation Networks with Penalty-Based Constraints","created":"2024-01-25","cited_by_count":7,"area":null},{"id":"2403.00817","title":"Doubly Calibrated Estimator for Recommendation on Data Missing Not At Random","created":"2024-02-26","cited_by_count":7,"area":null},{"id":"2210.11318","title":"A Survey of Computer Vision Technologies In Urban and Controlled-environment Agriculture","created":"2022-10-20","cited_by_count":6,"area":null},{"id":"2403.06759","title":"Average Calibration Error: A Differentiable Loss for Improved Reliability in Image Segmentation","created":"2024-03-11","cited_by_count":6,"area":null},{"id":"2408.06742","title":"Long-Tailed Out-of-Distribution Detection: Prioritizing Attention to Tail","created":"2024-08-13","cited_by_count":6,"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":"2411.16370","title":"A Review of Bayesian Uncertainty Quantification in Deep Probabilistic Image Segmentation","created":"2024-11-25","cited_by_count":6,"area":null},{"id":"2208.02870","title":"Improved post-hoc probability calibration for out-of-domain MRI segmentation","created":"2022-08-04","cited_by_count":5,"area":null},{"id":"2212.09368","title":"TAS-NIR: A VIS+NIR Dataset for Fine-grained Semantic Segmentation in Unstructured Outdoor Environments","created":"2022-12-19","cited_by_count":5,"area":null},{"id":"2303.06946","title":"Context-Aware Selective Label Smoothing for Calibrating Sequence Recognition Model","created":"2023-03-13","cited_by_count":5,"area":null},{"id":"2303.16296","title":"Dice Semimetric Losses: Optimizing the Dice Score with Soft Labels","created":"2023-03-28","cited_by_count":5,"area":null},{"id":"2403.02998","title":"Towards Calibrated Deep Clustering Network","created":"2024-03-04","cited_by_count":4,"area":null},{"id":"2501.13370","title":"Unraveling Normal Anatomy via Fluid-Driven Anomaly Randomization","created":"2025-01-23","cited_by_count":4,"area":null},{"id":"2503.22163","title":"T-CIL: Temperature Scaling using Adversarial Perturbation for Calibration in Class-Incremental Learning","created":"2025-03-28","cited_by_count":4,"area":null},{"id":"2504.00795","title":"Explainable AI-Based Interface System for Weather Forecasting Model","created":"2025-04-01","cited_by_count":4,"area":null},{"id":"2209.01880","title":"ScaleFace: Uncertainty-aware Deep Metric Learning","created":"2022-09-05","cited_by_count":3,"area":null},{"id":"2506.03942","title":"Average Calibration Losses for Reliable Uncertainty in Medical Image Segmentation","created":"2025-06-04","cited_by_count":3,"area":null},{"id":"2506.05917","title":"Rethinking Semi-supervised Segmentation Beyond Accuracy: Reliability and Robustness","created":"2025-06-06","cited_by_count":3,"area":null},{"id":"2506.23492","title":"Sample Margin-Aware Recalibration of Temperature Scaling","created":"2025-06-30","cited_by_count":3,"area":null},{"id":"2512.09054","title":"Improving Multi-Class Calibration through Normalization-Aware Isotonic Techniques","created":"2025-12-09","cited_by_count":3,"area":null},{"id":"2403.12364","title":"Class and Region-Adaptive Constraints for Network Calibration","created":"2024-03-19","cited_by_count":2,"area":null},{"id":"2403.15567","title":"Do not trust what you trust: Miscalibration in Semi-supervised Learning","created":"2024-03-22","cited_by_count":2,"area":null},{"id":"2408.14284","title":"May the Forgetting Be with You: Alternate Replay for Learning with Noisy Labels","created":"2024-08-26","cited_by_count":2,"area":null},{"id":"2506.17968","title":"h-calibration: Rethinking Classifier Recalibration with Probabilistic Error-Bounded Objective","created":"2025-06-22","cited_by_count":2,"area":null},{"id":"2606.21749","title":"Quantile Adaptive Temperature Scaling for Confidence Calibration","created":"2026-06-19","cited_by_count":2,"area":null},{"id":"2305.19498","title":"Perception and Semantic Aware Regularization for Sequential Confidence Calibration","created":"2023-05-31","cited_by_count":1,"area":null},{"id":"2309.02636","title":"Multiclass Alignment of Confidence and Certainty for Network Calibration","created":"2023-09-06","cited_by_count":1,"area":null},{"id":"2405.05830","title":"Mask-TS Net: Mask Temperature Scaling Uncertainty Calibration for Polyp Segmentation","created":"2024-05-09","cited_by_count":1,"area":null},{"id":"2406.10017","title":"Tilt and Average : Geometric Adjustment of the Last Layer for Recalibration","created":"2024-06-14","cited_by_count":1,"area":null},{"id":"2409.03470","title":"Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation","created":"2024-09-05","cited_by_count":1,"area":null},{"id":"2506.10572","title":"Probability Bounding: Post-Hoc Calibration via Box-Constrained Softmax","created":"2025-06-12","cited_by_count":1,"area":null},{"id":"2507.17494","title":"To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networks","created":"2025-07-23","cited_by_count":1,"area":null},{"id":"2509.24951","title":"Evaluating Temperature Scaling Calibration Effectiveness for CNNs under Varying Noise Levels in Brain Tumour Detection","created":"2025-09-29","cited_by_count":1,"area":null},{"id":"2510.00594","title":"Probability calibration for precipitation nowcasting","created":"2025-10-01","cited_by_count":1,"area":null},{"id":"2512.07390","title":"Towards Reliable Test-Time Adaptation: Style Invariance as a Correctness Likelihood","created":"2025-12-08","cited_by_count":1,"area":null},{"id":"2602.20860","title":"DA-Cal: Towards Cross-Domain Calibration in Semantic Segmentation","created":"2026-02-24","cited_by_count":1,"area":null},{"id":"2605.21060","title":"Divide et Calibra: Multiclass Local Calibration via Vector Quantization","created":"2026-05-20","cited_by_count":1,"area":null},{"id":"2108.07083","title":"Identifying and Exploiting Structures for Reliable Deep Learning","created":"2021-08-16","cited_by_count":0,"area":null},{"id":"2206.11562","title":"A Geometric Method for Improved Uncertainty Estimation in Real-time","created":"2022-06-23","cited_by_count":0,"area":null},{"id":"2301.04452","title":"Uncertainty Estimation based on Geometric Separation","created":"2023-01-11","cited_by_count":0,"area":null},{"id":"2307.07489","title":"PseudoCal: A Source-Free Approach to Unsupervised Uncertainty Calibration in Domain Adaptation","created":"2023-07-14","cited_by_count":0,"area":null},{"id":"2408.11239","title":"A Little Confidence Goes a Long Way","created":"2024-08-20","cited_by_count":0,"area":null},{"id":"2501.00053","title":"Implementing Trust in Non-Small Cell Lung Cancer Diagnosis with a Conformalized Uncertainty-Aware AI Framework in Whole-Slide Images","created":"2024-12-28","cited_by_count":0,"area":null},{"id":"2504.06358","title":"Towards Calibration Enhanced Network by Inverse Adversarial Attack","created":"2025-04-08","cited_by_count":0,"area":null},{"id":"2505.23463","title":"Revisiting Reweighted Risk for Calibration: AURC, Focal, and Inverse Focal Loss","created":"2025-05-29","cited_by_count":0,"area":null},{"id":"2602.23133","title":"From Calibration to Refinement: Seeking Certainty via Probabilistic Evidence Propagation for Noisy-Label Person Re-Identification","created":"2026-02-26","cited_by_count":0,"area":null},{"id":"2605.11954","title":"Assessing and Mitigating Miscalibration in LLM-Based Social Science Measurement","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2605.23249","title":"Enhancing Deep Neural Network Reliability with Refinement and Calibration","created":"2026-05-22","cited_by_count":0,"area":null},{"id":"2605.29773","title":"Energy-Aware NECO for Single-Pass Pixel-wise Out-of-Distribution Detection in Semantic Segmentation","created":"2026-05-28","cited_by_count":0,"area":null},{"id":"2606.04469","title":"Adaptive Calibration for Fair and Performant Facial Recognition","created":"2026-06-03","cited_by_count":0,"area":null},{"id":"2606.22308","title":"Specificity- and Calibration-Aware Breast Ultrasound Segmentation via Entropy-Guided Boundary Supervision","created":"2026-06-21","cited_by_count":0,"area":null},{"id":"2607.01902","title":"Rethinking Post-Hoc Calibration in Semantic Segmentation","created":"2026-07-02","cited_by_count":0,"area":null},{"id":"2607.14934","title":"Still image and spatial-temporal tomato data enabling detection, segmentation, tracking, and video-instance segmentation using strong and weak labels","created":"2026-07-16","cited_by_count":0,"area":null},{"id":"2608.01530","title":"ST-LoRA: Single Trajectory LoRA Ensemble for Uncertainty Aware Agricultural Segmentation","created":"2026-08-02","cited_by_count":0,"area":null},{"id":"2608.11537","title":"Generative Semantic Segmentation via an Observable Semantic-Image Interface and Hierarchical Generator Evidence Alignment","created":"2026-08-12","cited_by_count":0,"area":null},{"id":"2608.18715","title":"The Impact of CutMix on Reliability and Robustness in Semantic Segmentation","created":"2026-08-19","cited_by_count":0,"area":null},{"id":"2608.28681","title":"CARD: Calibration via Agreement in Reverse Diffusion for Out-of-Domain MRI Segmentation","created":"2026-08-26","cited_by_count":0,"area":null},{"id":"2609.17386","title":"Bridging the Confidence Gap: Temperature Scaling for Calibrating Test-Time Prompt Tuning","created":"2026-09-15","cited_by_count":0,"area":null},{"id":"2609.38936","title":"Signal-Routed Temperature Scaling: Low-Capacity Risk-Conditioned Calibration for Small Validation Budgets","created":"2026-09-30","cited_by_count":0,"area":null}],"next_cursor":null}