Overview

Sensitivity analysis asks which inputs, assumptions, or model components drive an output, and how strongly their effects change across conditions. Common approaches include controlled perturbations, derivative and adjoint methods, variance-based measures such as Sobol indices, Shapley effects, and surrogate models for costly simulations. These tools are used to understand physical and agent-based models, assess causal conclusions, prioritize features, and audit machine-learning reliability and robustness. A central challenge is making analysis scalable while distinguishing sensitivity from causality or correctness: accurate predictions and strong average scores do not guarantee credible responses to specific changes.

Latest papers

CardsList

39 papers6 papers in the last four weeks, up 20% on the four weeks before. 0.0% of all new papers.

  1. Sensitivity Fidelity Reveals Physical Dependencies Beyond Forecast Accuracy in Deep-Learning Earth-System Models

    Oct 11, 2026Qi Chen, Peng Zhan, Hongxing Cui +2Sensitivity AnalysisNeural Surrogate Modeling

  2. Do Time-Series QA Systems Read the Time Series? Evidence Use and Reasoning Reliability

    Oct 5, 2026Zhuomin Chen, Jingchao Ni, Xu Zheng +4Time Series ReasoningTime Series QA

  3. DePICT: Decision-Preserving Interface for Constrained Downstream Tasks

    Oct 2, 2026Utkarsh Grover, Ravi Ranjan, Agoritsa Polyzou +4Predict-Then-OptimizeConstrained Optimization

  4. Periodic Weak Spots: Phase Sensitivity from Chunked KV-Cache Compression

    Sep 28, 2026Xingyu Zhu, Pu, Yi +6Long-Context RetrievalKV-Cache Compression

  5. Learning Samples Importance: Parameterizing Dual Variables in Everywhere Learning

    Sep 28, 2026Ignacio Boero, Jonathan Nixon, Alejandro RibeiroConstrained OptimizationSensitivity Analysis

  6. Understanding Perturbed Parameter Ensemble Sensitivities Using A Contrastive Learning Approach

    Sep 24, 2026Da Fan, David John Gagne, Gregory S Elsaesser +5Climate ModelingSensitivity Analysis

  7. ModaLens: Measuring Image Sensitivity in Report-Conditioned Medical VLMs

    Sep 14, 2026Sebastián Andrés Cajas Ordóñez, Maximin Lange, Quang Bui +9VLM EvaluationRadiology VLMs

  8. Estimating Inconsistency Response Surfaces under Uncertainty in Cyber-Physical System Development

    Sep 10, 2026Johannes Mäkelburg, Tim Schwabe, Maribel AcostaCyber-Physical SystemsSurrogate Modeling

  9. A Group-Based Resource Allocation Model for the Fractional Knapsack Problem

    Sep 6, 2026Abhinaba ChakrabortyCombinatorial OptimizationSensitivity Analysis

  10. Mutual information and sensitivity analysis for feature selection in customer targeting: a comparative study

    Aug 20, 2026Nestor Barraza, Sergio Moro, Marcelo Ferreyra +1Feature SelectionMutual Information

  11. Information fusion and machine learning for sensitivity analysis using physics knowledge and experimental data

    Aug 18, 2026Berkcan Kapusuzoglu, Sankaran MahadevanSensitivity AnalysisPhysics-Informed ML

  12. BRAID: Learning Equilibrium Maps in Interdependent Security Games via Weight-Tied Iterative Graph Neural Networks

    Aug 14, 2026Elnaz Nowrouzi, Zhiqun Zuo, Xueru Zhang +1Nash Equilibrium ComputationGame Theory

  13. From Training to Deployment: Post-Hoc Causal Feature Identification via Sensitivity Ratios

    Jul 28, 2026Athanasios Vlontzos, Giorgos Papanastasiou, Bernhard Kainz +1Feature AttributionCausal Attribution

  14. An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers

    Jul 20, 2026Cheng Huan, Hongwei YuanLost-in-the-Middle EffectTransformer Attention

  15. Which Hyperparameters Matter? A Game-Theoretic Framework for Interpretable Hyperparameter Sensitivity Analysis

    Jul 17, 2026Nyi Nyi Aung, Heepeom Shin, Abigail Lawlor +1Hyperparameter OptimizationSensitivity Analysis

  16. Hybrid Uncertainty Sensitivity Analysis Based on the HSIC for High-Dimensional Responses with Aleatory--Epistemic Separation

    Jun 12, 2026Shijie Zhong, Jiangfeng Fu, Pengfei WeiUncertainty QuantificationAleatoric Uncertainty

  17. On the Generalization in Topology Optimization via Sensitivity-Conditioned Bernoulli Flow Matching

    Jun 1, 2026Mohammad Rashed, Duarte F. Valoroso Madeira, Babak Gholami +3Neural Surrogate ModelingTopology Optimization

  18. Knowledge Dependency Estimation for Reliable Question Answering

    May 27, 2026Chaodong Tong, Qi Zhang, Nannan Sun +2Knowledge-Intensive QASensitivity Analysis

  19. Quantifying Uncertainty in Space Debris Capture with Active Tether-Net Systems Caused by Noisy Observations

    May 26, 2026Feng Liu, Achira Boonrath, Eleonora M. Botta +1Uncertainty QuantificationSensitivity Analysis

  20. Stop Drawing Scientific Claims from LLM Social Simulations Without Robustness Audits

    May 17, 2026Jinyi Ye, Lei Cao, Ding Chen +1Human Behavior SimulationAgent-Based Modeling

  21. Quantifying Sensitivity for Tree Ensembles: A symbolic and compositional approach

    May 13, 2026Ajinkya Naik, Chaitanya Garg, S. Akshay +2Ensemble LearningFormal Verification

  22. Amortizing Causal Sensitivity Analysis via Prior Data-Fitted Networks

    May 11, 2026Emil Javurek, Dennis Frauen, Marie Brockschmidt +2Causal Effect EstimationAmortized Inference

  23. Statistical Model Checking of the Keynes+Schumpeter Model: A Transient Sensitivity Analysis of a Macroeconomic ABM

    May 11, 2026Stefano Blando, Giorgio Fagiolo, Mauro Napoletano +2Statistical Model CheckingAgent-Based Modeling

  24. Bayesian Sensitivity of Causal Inference Estimators under Evidence-Based Priors

    May 8, 2026Nikita Dhawan, Daniel Shen, Leonardo Cotta +1Causal Effect EstimationBayesian Inference

  25. Minimum Specification Perturbation: Robustness as Distance-to-Falsification in Causal Inference

    May 2, 2026Hoang Dang, Luan Pham, Minh NguyenCausal Effect EstimationCausal Inference

  26. Measuring the Sensitivity of Classification Models with the Error Sensitivity Profile

    Apr 28, 2026Andrea MaurinoTraining Data CurationTabular ML