Learning to Defer

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1 paper in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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A Query Is Not a Commitment: Learning to Correct Expert Answers in Online Deferral
Oct 5, 2026Yannis Montreuil, Axel Carlier, Lai Xing Ng +1Cost-Sensitive Learning Learning to Defer
School of Computing, National University of Singapore · IRIT, Toulouse INP, France · Institute for Infocomm Research, A*STAR, Singapore
Learning to Defer with Guidance on Real World Medical Data
Sep 22, 2026Emma Sun, Joshua Strong, Alison NobleLearning to Defer Human-in-the-Loop AI
Department of Engineering Science, University of Oxford, UK
Let it Cook: Learning to Wait in Sequential Decision Making
Aug 11, 2026Christopher Watson, Arjun Krishna, Dinesh Jayaraman +1Sequential Decision Making Learning to Defer
Department of Computer and Information Science, University of Pennsylvania, USA
Multistage Defer Trees for Hybrid Interpretability: If at First You Can't Succeed, Tree Again
Jun 30, 2026Zakk Heile, Hayden McTavish, Margo Seltzer +1Ensemble Learning Learning to Defer
Department of Computer Science · Duke University · Durham, USA +2
Human-AI Teaming Through the Lens of Calibration
Jun 9, 2026Eric Nalisnick, Chi Zhang, Sophia Qian +1Learning to Defer Model Calibration
Department of Computer Science Johns Hopkins University · Department of Statistics University of Michigan
Oversight Has a Capacity: Calibrating Agent Guards to a Subjective, Fatiguing Human
Jun 8, 2026Emre TuranLearning to Defer LLM Guardrails
Independent Researcher
Learning to Assign Prediction Tasks to Agents with Capacity Constraints
May 27, 2026Shang Wu, Saatvik Kher, Padhraic SmythLearning to Defer Contextual Bandits
Department of Computer Science University of California, Irvine Irvine, CA 92697, USA
Knowing When to Ask: Segment-Level Credit Assignment for LLM Tool Use
May 27, 2026Abhijit Kumar, Zoey Wu, Mohit SuleyTool-Augmented Language Model Agents Learning to Defer
Microsoft AI Redmond, WA
Set-Valued Policy Learning
May 19, 2026Laura Fuentes-Vicente, Mathieu Even, Gaëlle Dormion +3Healthcare Learning to Defer
Inria PreMeDICaL, Inserm, Montpellier, France · Elixir Health, Paris, France · Université Paris Cité, CNRS, MAP5, F-75006 Paris, France +1
Density-Ratio Losses for Post-Hoc Learning to Defer
May 19, 2026Alexander Soen, Ragnar Thobaben, Joakim Jaldén +1Learning to Defer Density Ratio Estimation
KTH⋄ · Google Research†
Online Learning-to-Defer with Varying Experts
May 12, 2026Dang Hoang Duy, Yannis Montreuil, Maxime Meyer +3Learning to Defer Multiclass Classification
School of Computing, National University of Singapore, Singapore · IPAL, IRL 2955, Singapore · Department of Mathematics, National University of Singapore, Singapore, 117543 +2
MPD $^2$ -Router: Mask-aware Multi-expert Prior-regularized Dual-head Deferral Router in Glaucoma Screening and Diagnosis
May 8, 2026Wenxin ZhanAI-Assisted Decision Making Learning to Defer
Baruch college
Coherent Hierarchical Multi-Label Learning to Defer for Medical Imaging
May 4, 2026Joshua Strong, Pramit Saha, Emma Sun +2Hierarchical Classification Multi-Label Classification
Department of Engineering Science, University of Oxford, UK · Nuffield Division of Anaesthetics, University of Oxford, The John Radcliffe Hospital, UK
Optimized Deferral for Imbalanced Settings
Apr 30, 2026Corinna Cortes, Anqi Mao, Mehryar Mohri +1Cost-Sensitive Learning Learning to Defer
Google Research, New York, NY · Courant Institute of Mathematical Sciences, New York, NY
People-Centred Medical Image Analysis via Fairness-Aware Human-AI Cooperation
Apr 28, 2026Zheng Zhang, Milad Masroor, Cuong Nguyen +6Healthcare Learning to Defer
CVSSP, PAI, University of Surrey, UK · Southampton Solent University, UK · AIML, Adelaide University, Australia +2
Learning-to-Defer in Non-Stationary Time Series via Switching State-Space Models
Jan 30, 2026Yannis Montreuil, Letian Yu, Axel Carlier +2Cost-Sensitive Learning Adaptive Model Routing
School of Computing National University of Singapore · Université de Toulouse Fédération ENAC ISAE-SUPAERO ONERA · Institute for Infocomm Research A*STAR, Singapore

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A Query Is Not a Commitment: Learning to Correct Expert Answers in Online Deferral

Yannis Montreuil, Axel Carlier, Lai Xing Ng, Wei Tsang Ooi

School of Computing, National University of Singapore · IRIT, Toulouse INP, France · Institute for Infocomm Research, A*STAR, Singapore

Cost-Sensitive Learning Learning to Defer

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An inaccurate expert can still provide useful information after correction. We study online learning to defer in which the learner chooses an expert and fixes a correction function before purchasing its answer, then applies that function to the answer received. The difficulty is that observed losses reflect both expert quality and an unfinished correction: early errors can discourage queries that would be valuable after learning. We propose ORUCB, which pools shared and expert-specific polynomial responses. A bound on cumulative response-learning error calibrates confidence-weighted risk regression and exploration, allowing the router to account for this error when deciding which answers to buy. Under bounded residuals and disagreements, a fixed feasible model of optimal responses, and linear models of free and optimal queried risk, the calibrated algorithm achieves high-probability pseudo-regret

O(\sqrt T\log(T+1))

over

T

rounds for fixed problem parameters. The guarantee permits singular answer distributions and misspecified shared responses; optimality is relative to the bounded response class. On four test streams, the selected cubic policy has lower fee-inclusive cost than seven baselines that deploy answers unchanged. Comparisons with a common correction learner examine routing, while six-price comparisons measure cost and query rates.

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