{"total":62,"rows":[{"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":"2301.06197","title":"Who Should Predict? Exact Algorithms For Learning to Defer to Humans","created":"2023-01-15","cited_by_count":70,"area":null},{"id":"2210.16955","title":"Learning to Defer to Multiple Experts: Consistent Surrogate Losses, Confidence Calibration, and Conformal Ensembles","created":"2022-10-30","cited_by_count":60,"area":null},{"id":"2310.14772","title":"Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and Algorithms","created":"2023-10-23","cited_by_count":36,"area":null},{"id":"2310.14770","title":"Theoretically Grounded Loss Functions and Algorithms for Score-Based Multi-Class Abstention","created":"2023-10-23","cited_by_count":32,"area":null},{"id":"2403.19494","title":"Regression with Multi-Expert Deferral","created":"2024-03-28","cited_by_count":29,"area":null},{"id":"2403.02683","title":"Learning to Defer to a Population: A Meta-Learning Approach","created":"2024-03-05","cited_by_count":27,"area":null},{"id":"2311.01106","title":"In Defense of Softmax Parametrization for Calibrated and Consistent Learning to Defer","created":"2023-11-02","cited_by_count":26,"area":null},{"id":"2407.13732","title":"Realizable $H$-Consistent and Bayes-Consistent Loss Functions for Learning to Defer","created":"2024-07-18","cited_by_count":26,"area":null},{"id":"2405.05968","title":"A Universal Growth Rate for Learning with Smooth Surrogate Losses","created":"2024-05-09","cited_by_count":24,"area":null},{"id":"2407.13722","title":"Enhanced $H$-Consistency Bounds","created":"2024-07-18","cited_by_count":18,"area":null},{"id":"2410.15729","title":"A Two-Stage Learning-to-Defer Approach for Multi-Task Learning","created":"2024-10-21","cited_by_count":17,"area":null},{"id":"2206.13202","title":"Human-AI Collaboration in Decision-Making: Beyond Learning to Defer","created":"2022-06-27","cited_by_count":16,"area":null},{"id":"2506.20650","title":"Mastering Multiple-Expert Routing: Realizable $H$-Consistency and Strong Guarantees for Learning to Defer","created":"2025-06-25","cited_by_count":16,"area":null},{"id":"2406.00060","title":"Cascade-Aware Training of Language Models","created":"2024-05-29","cited_by_count":15,"area":null},{"id":"2301.12386","title":"Plugin estimators for selective classification with out-of-distribution detection","created":"2023-01-29","cited_by_count":14,"area":null},{"id":"2405.18902","title":"A Causal Framework for Evaluating Deferring Systems","created":"2024-05-29","cited_by_count":13,"area":null},{"id":"2510.26706","title":"Budgeted Multiple-Expert Deferral","created":"2025-10-30","cited_by_count":13,"area":null},{"id":"2403.06906","title":"Cost-Sensitive Learning to Defer to Multiple Experts with Workload Constraints","created":"2024-03-11","cited_by_count":12,"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":"2311.13355","title":"Unified Classification and Rejection: A One-versus-All Framework","created":"2023-11-22","cited_by_count":9,"area":null},{"id":"2402.06287","title":"AI, Meet Human: Learning Paradigms for Hybrid Decision Making Systems","created":"2024-02-09","cited_by_count":7,"area":null},{"id":"2407.07003","title":"Learning to Complement and to Defer to Multiple Users","created":"2024-07-09","cited_by_count":7,"area":null},{"id":"2510.23476","title":"Human-AI Collaborative Uncertainty Quantification","created":"2025-10-27","cited_by_count":7,"area":null},{"id":"2311.13172","title":"Learning to Complement with Multiple Humans","created":"2023-11-22","cited_by_count":5,"area":null},{"id":"2409.20489","title":"Online Decision Deferral under Budget Constraints","created":"2024-09-30","cited_by_count":5,"area":null},{"id":"2403.16501","title":"Learning To Guide Human Decision Makers With Vision-Language Models","created":"2024-03-25","cited_by_count":4,"area":null},{"id":"2502.01459","title":"Learning to Partially Defer for Sequences","created":"2025-02-03","cited_by_count":4,"area":null},{"id":"2602.17144","title":"When More Experts Hurt: Underfitting in Multi-Expert Learning to Defer","created":"2026-02-19","cited_by_count":3,"area":null},{"id":"2602.17646","title":"Multi-Round Human-AI Collaboration with User-Specified Requirements","created":"2026-02-19","cited_by_count":3,"area":null},{"id":"2604.00904","title":"Fatigue-Aware Learning to Defer via Constrained Optimisation","created":"2026-04-01","cited_by_count":3,"area":null},{"id":"2307.02932","title":"When No-Rejection Learning is Consistent for Regression with Rejection","created":"2023-07-06","cited_by_count":2,"area":null},{"id":"2312.07679","title":"Bayesian Online Learning for Consensus Prediction","created":"2023-12-12","cited_by_count":2,"area":null},{"id":"2409.16253","title":"Learning To Help: Training Models to Assist Legacy Devices","created":"2024-09-24","cited_by_count":2,"area":null},{"id":"2501.13810","title":"Learning to Help in Multi-Class Settings","created":"2025-01-23","cited_by_count":2,"area":null},{"id":"2508.06997","title":"Conformal Set-based Human-AI Complementarity with Multiple Experts","created":"2025-08-09","cited_by_count":2,"area":null},{"id":"2509.12573","title":"No Need for Learning to Defer? A Training Free Deferral Framework to Multiple Experts through Conformal Prediction","created":"2025-09-16","cited_by_count":2,"area":null},{"id":"2601.06119","title":"L2CU: Learning to Complement Unseen Users","created":"2026-01-03","cited_by_count":2,"area":null},{"id":"2604.27723","title":"Optimized Deferral for Imbalanced Settings","created":"2026-04-30","cited_by_count":2,"area":null},{"id":"2403.20047","title":"Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World","created":"2024-03-29","cited_by_count":1,"area":null},{"id":"2506.05636","title":"Bayesian Inference for Correlated Human Experts and Classifiers","created":"2025-06-05","cited_by_count":1,"area":null},{"id":"2507.04431","title":"MedGellan: LLM-Generated Medical Guidance to Support Physicians","created":"2025-07-06","cited_by_count":1,"area":null},{"id":"2604.12411","title":"DeferredSeg:A Multi-Expert Deferral Framework for Medical Image Segmentation","created":"2026-04-14","cited_by_count":1,"area":null},{"id":"2604.20409","title":"Calibrating conditional risk","created":"2026-04-22","cited_by_count":1,"area":null},{"id":"2605.19557","title":"Density-Ratio Losses for Post-Hoc Learning to Defer","created":"2026-05-19","cited_by_count":1,"area":null},{"id":"2606.12587","title":"Strategic Decision Support for AI Agents","created":"2026-06-10","cited_by_count":1,"area":null},{"id":"2308.06039","title":"Learning to Guide Human Experts via Personalized Large Language Models","created":"2023-08-11","cited_by_count":0,"area":null},{"id":"2412.19530","title":"The Value of AI Advice: Personalized and Value-Maximizing AI Advisors Are Necessary to Reliably Benefit Experts and Organizations","created":"2024-12-27","cited_by_count":0,"area":null},{"id":"2505.19220","title":"DeCoDe: Defer-and-Complement Decision-Making via Decoupled Concept Bottleneck Models","created":"2025-05-25","cited_by_count":0,"area":null},{"id":"2508.02319","title":"Is Uncertainty Quantification a Viable Alternative to Learned Deferral?","created":"2025-08-04","cited_by_count":0,"area":null},{"id":"2510.19351","title":"Learning To Defer To A Population With Limited Demonstrations","created":"2025-10-22","cited_by_count":0,"area":null},{"id":"2603.07867","title":"Slumbering to Precision: Enhancing Artificial Neural Network Calibration Through Sleep-like Processes","created":"2026-03-09","cited_by_count":0,"area":null},{"id":"2603.09947","title":"The Confidence Gate Theorem: When Should Ranked Decision Systems Abstain?","created":"2026-03-10","cited_by_count":0,"area":null},{"id":"2604.14980","title":"Hybrid Decision Making via Conformal VLM-generated Guidance","created":"2026-04-16","cited_by_count":0,"area":null},{"id":"2605.08024","title":"MPD$^2$-Router: Mask-aware Multi-expert Prior-regularized Dual-head Deferral Router in Glaucoma Screening and Diagnosis","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2605.08388","title":"PLACO: A Multi-Stage Framework for Cost-Effective Performance in Human-AI Teams","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2606.10906","title":"Human-AI Teaming Through the Lens of Calibration","created":"2026-06-09","cited_by_count":0,"area":null},{"id":"2609.07095","title":"Risk Is Not Review Value: Wrong-Answer Exposure Under Bounded Review Budgets","created":"2026-09-07","cited_by_count":0,"area":null},{"id":"2609.09235","title":"Cost-Aware Post-Hoc Deferral Under Calibration and Shift: An Environmental AI Case Study","created":"2026-09-07","cited_by_count":0,"area":null},{"id":"2609.21953","title":"RACER: Role-Aligned Competence Estimation for Human-AI Routing","created":"2026-09-18","cited_by_count":0,"area":null},{"id":"2609.39818","title":"Should I stay or should I show? Learning to selectively disclose information","created":"2026-09-30","cited_by_count":0,"area":null},{"id":"2610.02632","title":"Online Verification of Language Model Responses Under Cost Constraints","created":"2026-10-02","cited_by_count":0,"area":null}],"next_cursor":null}