Risk Modeling papers, 2023–2026

Key findings

• Risk Modeling went from 15 papers in 2023 to 48 in 2026, roughly 3.2x in three years.
• NeurIPS publishes the most Risk Modeling work: 47 papers from 2023 to 2026, 41% of the four-venue total.
• The fastest-growing overlap is with Reinforcement Learning: papers tagged with both rose from 4 in 2023 to 12 in 2026.
• Among the 5 topics under Finance and Economics, it ranks #1 by 2026 paper count; the fastest grower in the group, Macro Forecasting, is up 8.0x versus 3.2x here.

Representative papers

Spread across years and venues so every edition shows up

• NeurIPS 2026CCTimeBoost: Learning Time-Varying Relative Risk with Case-Control Boosted Trees
• ICML 2026A Machine-Learned Comorbidity Index
• ICLR 2026SAFER: Risk-Constrained Sample-then-Filter in Large Language Models
• CVPR 2026Spectral Conformal Risk Control Distribution-Free Tail Guarantees via Bayesian Quadrature
• NeurIPS 2025Generating Informative Samples for Risk-Averse Fine-Tuning of Downstream Tasks
• ICML 2025Compositional Risk Minimization
• ICLR 2025Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filtering
• NeurIPS 2024Evaluating language models as risk scores
• ICML 2024Differentially Private Worst-group Risk Minimization
• ICLR 2024SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore
• CVPR 2024Self-Calibrating Vicinal Risk Minimisation for Model Calibration
• NeurIPS 2023Optimal Excess Risk Bounds for Empirical Risk Minimization on $p$-Norm Linear Regression
• ICML 2023Fast Excess Risk Rates via Offset Rademacher Complexity
• ICLR 2023Avoiding spurious correlations via logit correction
• NeurIPS 2026Hidden Tails: Certifying Tail-Risk Claims under Selective Labels
• ICML 2026Disentangling Latent Risk Pathways via Bayesian Hypergraph Inference
• ICLR 2026Conformalized Decision Risk Assessment
• CVPR 2026CoRiM Conflict-driven Risk Minimization for Dynamic Multimodal Fusion
• NeurIPS 2025Risk Bounds For Distributional Regression
• ICML 2025Structure-informed Risk Minimization for Robust Ensemble Learning

All Risk Modeling papers

47 papers, page 1 of 1

1. NeurIPS 2026Anytime-Valid Conformal Risk Control
2. NeurIPS 2026Benchmarking Risk Attitudes of LLMs
3. NeurIPS 2026Bridging Risk Approximation Gaps in Model Predictive Task Sampling via In-Context Modeling
4. NeurIPS 2026CCTimeBoost: Learning Time-Varying Relative Risk with Case-Control Boosted Trees
5. NeurIPS 2026CompilerKV: Risk-Adaptive KV Cache Compression via Offline Experience Compilation
6. NeurIPS 2026DiffRisk: Diffusion Representation Learning with Informative Missingness for Health Risk Prediction
7. NeurIPS 2026Distribution-First Framework for Learning Risk-Sensitive Individualized Treatment Rules
8. NeurIPS 2026Ensemble Modeling for Time Series Forecasting: an Adaptive Robust Optimization Approach
9. NeurIPS 2026Finite Time Analysis of Risk-Sensitive RL via Noisy Power Iteration
10. NeurIPS 2026Hidden Tails: Certifying Tail-Risk Claims under Selective Labels
11. NeurIPS 2026KVFocus: A Perturbation-Theoretic Token-Risk Score for Selective KV Cache Reuse in RAG
12. NeurIPS 2026Long-Term Risks of Risk-Based Allocation
13. NeurIPS 2026NNCoxKL: Risk-Set Distillation from Probability-Free Prognostic Teachers for Deep Cox Models
14. NeurIPS 2026Occupancy-based Quantile Risk Control
15. NeurIPS 2026Optimal Risk Bounds of Stochastic Gradient Descent for Shallow ReLU Networks
16. NeurIPS 2026Progressive Risk Estimation for Accident Anticipation
17. NeurIPS 2026Retrieval-Augmented Diffusion Modeling for Stochastic Discount Factor Portfolios
18. NeurIPS 2026Risk-Controlled Post-Processing of Decision Policies
19. NeurIPS 2026Risk-guided Estimation-aware Acceptance for Learning with Synthetic Data
20. NeurIPS 2026Risk-Sensitive Deep Optimal Stopping
21. NeurIPS 2026Statistical Estimation of Adversarial Risk in Large Language Models under Best-of-N Sampling
22. NeurIPS 2026Steering Externalities: Benign Activation Steering Unintentionally Increases Jailbreak Risk for Large Language Models
23. NeurIPS 2026Tail-Risk-Aware Stackelberg Learning
24. NeurIPS 2026Training Generalizable Collaborative Agents via Strategic Risk Aversion
25. NeurIPS 2026WURI: Watching Unfolding Risk in Agent Interactions
26. NeurIPS 2025Establishing Linear Surrogate Regret Bounds for Convex Smooth Losses via Convolutional Fenchel–Young Losses
27. NeurIPS 2025Generating Informative Samples for Risk-Averse Fine-Tuning of Downstream Tasks
28. NeurIPS 2025Pareto Optimal Risk-Agnostic Distributional Bandits with Heavy-Tail Rewards
29. NeurIPS 2025Performative Risk Control: Calibrating Models for Reliable Deployment under Performativity
30. NeurIPS 2025Risk Bounds For Distributional Regression
31. NeurIPS 2025Risk-Averse Constrained Reinforcement Learning with Optimized Certainty Equivalents
32. NeurIPS 2025Risk-Averse Total-Reward Reinforcement Learning
33. NeurIPS 2025Subsampled Ensemble Can Improve Generalization Tail Exponentially
34. NeurIPS 2025Towards Evaluating Proactive Risk Awareness of Multimodal Language Models
35. NeurIPS 2024$\epsilon$-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise
36. NeurIPS 2024Evaluating language models as risk scores
37. NeurIPS 2024Fast yet Safe: Early-Exiting with Risk Control
38. NeurIPS 2024Risk-sensitive control as inference with Rényi divergence
39. NeurIPS 2024Spectral-Risk Safe Reinforcement Learning with Convergence Guarantees
40. NeurIPS 2024Universal Rates of Empirical Risk Minimization
41. NeurIPS 2023GRAND-SLAMIN’ Interpretable Additive Modeling with Structural Constraints
42. NeurIPS 2023Improved Bayes Risk Can Yield Reduced Social Welfare Under Competition
43. NeurIPS 2023Minimum-Risk Recalibration of Classifiers
44. NeurIPS 2023One Risk to Rule Them All: A Risk-Sensitive Perspective on Model-Based Offline Reinforcement Learning
45. NeurIPS 2023Optimal Excess Risk Bounds for Empirical Risk Minimization on $p$-Norm Linear Regression
46. NeurIPS 2023Pitfall of Optimism: Distributional Reinforcement Learning by Randomizing Risk Criterion
47. NeurIPS 2023The probability flow ODE is provably fast

FAQ

How many Risk Modeling papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

115 in total: 15 in 2023, 26 in 2024, 26 in 2025, 48 in 2026.

How many Risk Modeling papers are at NeurIPS 2026?

NeurIPS 2026 has 25 Risk Modeling papers, versus 9 the year before.

How many Risk Modeling papers are at ICLR 2026?

ICLR 2026 has 6 Risk Modeling papers, versus 9 the year before.

How many Risk Modeling papers are at ICML 2026?

ICML 2026 has 14 Risk Modeling papers, versus 8 the year before.

How many Risk Modeling papers are at CVPR 2026?

CVPR 2026 has 3 Risk Modeling papers.

Which conference publishes the most Risk Modeling papers?

NeurIPS, with 47 papers from 2023 to 2026.