Model Interpretability Methods

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Mechanistic InterpretabilityInterpretable Machine Learning

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Period ending 2026-09-14

8 new papers

A weekly snapshot of new work published in Model Interpretability Methods.

Period ending 2026-09-07

5 new papers

A weekly snapshot of new work published in Model Interpretability Methods.

262 papers

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  1. MAxBench: A Multinomial Concept Recovery Benchmark

    Sep 14, 2026Divya Appapogu, Freya Behrens, Yonatan Belinkov +1Model Interpretability Methods

  2. Auditable Emergency Triage for Maternal and Newborn Care in India

    Sep 10, 2026Shobhit Jagga, Aman Dalmia, Niharika Priyadarshini +7TriageModel Interpretability Methods

  3. XAI-Arena: Can LLMs Assess the Quality of XAI Explanations?

    Sep 10, 2026Yanfei Hu Fleischhauer, Alona Zharova, Nadja Klein +1XaiExplainable Artificial Intelligence

  4. An Explainable Machine Learning Framework for Predicting Blood-Brain Barrier Permeability Using Molecular Descriptors

    Sep 9, 2026Fatemeh MahmoudiMolecular DescriptorsMolecular Structure Elucidation

  5. Do Reasoning Representations Help Humans Evaluate LLM Outputs?

    Sep 8, 2026Jaewoo Lim, Sungbok Shin, Sanghyun HongLLM Reasoning MethodsModel Interpretability Methods

  6. GraphFAS: A Distributed System for Automated Graph Feature Generation and Selection in Industrial Transaction Networks

    Sep 8, 2026Yice Luo, Yun Zhu, Xi Chen +7Fraud DetectionModel Interpretability Methods

  7. LLM Layers Immediately Correct Each Other

    Sep 7, 2026Arjun Patrawala, Jiahai Feng, Erik Jones +1Model ActivationsResidual Stream

  8. When Superpixels Fail on Documents: A Study of Segmentation for LIME Explanations

    Sep 7, 2026Quentin Telnoff, Emanuela Boros, Mickaël Coustaty +3Concept-Based ExplainabilityDocument

  9. Legibility is Not Interpretability: Comparing Judged and Actual Importance in Chain-Of-Thought Reasoning

    Sep 3, 2026Kevin Du, Alexander Hoyle, Laura Ruis +1Reasoning ChainReasoning Traces

  10. Witnesses Explain Anomalies

    Sep 3, 2026Lamine DiopAnomaly ScoreAnomaly

  11. Towards reliable multimodal disaster severity assessment through preference optimization and explainable vision-language reasoning

    Sep 1, 2026Yuanjun Zhang, Fuzel Ahamed Shaik, Suvojit Acharjee +2Post-Disaster Damage AssessmentDisasters

  12. MURANO: Design, Run, and Reproduce Mechanistic Interpretability Experiments as Composable Pipelines

    Aug 31, 2026Alireza Bayat Makou, Emirhan Böge, Phu Gia Hoang +5Model Interpretability MethodsMechanistic Interpretability

  13. Tensor Methods for Language Models: From Token Representation to Training, Adaptation, Inference, Compression, and Interpretability

    Aug 31, 2026Matvei Tarasov, Salman Ahmadi-Asl, Andre L. F. de Almeida +1Large Language Model ScaleTensor

  14. TabSOM: A tabular-to-image encoding method based on self-organizing maps

    Aug 13, 2026David Chushig-Muzo, María Ángeles Rodríguez de Cara, Eva Milara +3Tabular LearningModel Interpretability Methods

  15. Perturbation-based Regional Interpretability through Subtraction Mapping (PRISM): naming-error dissociations in language models and post-stroke aphasia

    Aug 13, 2026Xiang Guan, Roger D. Newman-Norlund, Yong Yang +8Dysarthric SpeechLinguistics

  16. HyperANFIS: Enhancing Rule Representation and Interpretability in Adaptive Neuro-Fuzzy Systems via Hyperbolic Geometry

    Aug 12, 2026Haoran Pei, Zhao Su, Zetao Lin +6Hyperbolic SpaceModel Interpretability Methods

  17. From Interpretability to Control: Insights from Six Years of the TrustNLP Workshop

    Aug 11, 2026Rahul Gupta, Abhinav Mohanty, Anaelia Ovalle +10Large Language Model ReliabilityModel Interpretability Methods

  18. Conversational versus Dashboard Explainable AI for UAV Intrusion Detection: An Empirical Study of Operator Trust and Reliance

    Aug 11, 2026Cong Chi Nguyen, Trang Mai Xuan, Vu-Duc Ngo +3Unmanned Aerial Vehicle TrackingIntrusion Detection

  19. Intrinsic Structure: Spectral Identifiability for Mechanistic Interpretability

    Aug 10, 2026Ashim Dhor, Pin-Yu ChenMechanistic InterpretabilityModel Interpretability Methods

  20. Multilingual Emotion Neurons in Large Audio-Language Models

    Aug 9, 2026Xiutian Zhao, Philipp Koehn, Björn Schuller +1Large Audio Language ModelsProtein Language Model

  21. The Spectral Neuron

    Aug 8, 2026Alex ShtoffModel Interpretability MethodsAffine

  22. Transformer Geometry Observatory TGO-IV: Developmental Topology Observatory

    Aug 7, 2026Kaustubh Kapil, Kishor P. UplaVisual Geometry Grounded TransformerTopology

  23. Interpretable reinforcement learning with decision-tree pruning

    Aug 7, 2026Mark Leon Ringer, Michel TokicSafe Reinforcement LearningModel Interpretability Methods

  24. Faster Query-Key Learning Sharpens Attention in Self-Attention Models

    Aug 7, 2026Rahul Vashisht, Harish G. RamaswamySelf-Attention MechanismLearning Rates

  25. Scaling Inherently Interpretable Language Models

    Aug 6, 2026Guide Labs Team, Andreas Madsen, Aya Abdelsalam Ismail +7Model Interpretability MethodsDiffusion Language Models

  26. Persistent Convolution: A Topological Framework for AI Alignment Testing and Semantic Space Characterization

    Jul 31, 2026Tyler Ashoff, Jordan RoduArtificial Intelligence AlignmentArtificial Intelligence Benchmarks

  27. HealthCAT: An Interpretable Encoder-only Transformer Framework for Health Indicator Prediction and Temporal Interpretation of Wearable Sensor Data

    Jul 30, 2026Xiaotong Yu, Joshua Y. Kim, HaeJin Lee +1Wearable DevicesTransformer Encoder

  28. ECG-InterpBench: Benchmarking the Interpretability of ECG Foundation Models with Matched-Scale Sparse Autoencoders

    Jul 29, 2026Yixuan Duan, Wei QiuEcg-Specific AugmentationsElectronic Health Record Foundation Models

  29. KANEx: Translating Kolmogorov-Arnold Networks' Interpretability to Medical Explainability

    Jul 27, 2026Krithi Shailya, Ananya Lakshmi Ravi, Venkatanathan K. V. +4Concept-Based ExplainabilityMedical Vision-Language Models

  30. Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects

    Jul 27, 2026Phu Gia Hoang, Anwoy Chatterjee, Tanmoy Chakraborty +2Improving Sparse AutoencodersSparse Autoencoders

  31. LEX-EC: A Lexical Evidence-Channel Audit Framework for Zero-Shot LLM Personality Classification in Black-Box Settings

    Jul 27, 2026Brittany Harbison, Ashok K. GoelPersonalityLarge Language Model Bias

  32. LAWFUL: Law-Aligned Witness for Faithful Use of Latents

    Jul 26, 2026Kevin Chen, Kenneth W. Parker, Anish AroraModel Interpretability MethodsPhysics-Aware Models

  33. Same Predictions, Different Reasons: The Effect of Quantization on Model Explanations

    Jul 24, 2026Kazi Kamruzzaman Rabbi, Md. Zami Al Zunaed Farabe, M. Sohel RahmanPost-Training QuantizationQuantization Effects

  34. Interior interpretability with attention rollout: contraction and propagation profiles in Transformers

    Jul 24, 2026Umberto Biccari, Qian Huang, Enrique ZuazuaModel Interpretability MethodsLong Rollouts

  35. Probing Latent Colombian Identity Inferences in Qwen2.5-7B with Natural Language Autoencoders

    Jul 23, 2026Pablo Santiago Potes Velasco, María del Mar García Matabanchoy, Óscar Julián Pérez Ladino +3Large Language Model BiasStereotype Mitigation

  36. PrefReward: Learning User Preference Matrix for Personalized Text Generation

    Jul 23, 2026Yue Wu, Chengbing Wang, Yimeng Bai +3Large Language Model PersonalizationText Generation

  37. Neural Feature Governance: Extending Atom Prevalence

    Jul 23, 2026Idris Karel Seunda Ekwe, Patrick Tenga Shako, Ernest Parfait FokouéBayesian Neural NetworksModel Interpretability Methods

  38. Efficient and Interpretable Body-Based Emotion Recognition with Lightweight Temporal Convolutional Networks

    Jul 23, 2026Christian Arzate Cruz, Stefanos Gkikas, Houshyar AsadiTemporal Convolutional NetworksSkeleton-Based Action Recognition

  39. Scaling Interpretable Transformers with Parity Bottleneck Layers

    Jul 22, 2026Andrew Mack, Kraig Yuheng Tou, Mark Henry +2Sparse AutoencodersModel Interpretability Methods

  40. Train the Model, Not the Reader: Decodability Supervision for Verifiable Activation Explanations

    Jul 22, 2026Hiskias DingetoModel Interpretability MethodsVerbalization

  41. fSRD: Fuzzy Spectral Region Decomposition -- Automated Multi Operator Koopman Representations via an Adaptive Spectral Learning Architecture

    Jul 20, 2026Charles Bokor, Mark Cary, Denise Morrey +1Koopman OperatorSpectral Algorithms

  42. What does a Bayes-filtered transformer believe? A predictive Monte Carlo approach

    Jul 19, 2026Afiq Abdillah Effiezal Aswadi, Haotong Ma, Susan WeiPosteriorNext-Token Prediction

  43. RELIC: Revealed Principles for Learning Interpretable Composable Skills in Multi-Agent Planning

    Jul 18, 2026Nguyen Viet Tuan Kiet, Bui Dinh Pham, Duong Quoc Chinh +3Team FormationPrinciples

  44. Retrieval is Enough: Training-Free Interpretability with a Tool-Using Agent

    Jul 17, 2026Sriram Balasubramanian, Soheil FeiziModel Interpretability MethodsModel Activations

  45. AIMO Interpretability Challenge

    Jul 15, 2026Michal Štefánik, Philipp Mondorf, Andreas Waldis +11Olympiad-Level ProblemModel Interpretability Methods

  46. Decouple and Reason: Anatomically Guided Two-Stage Voxel-Level Grounding of Free-Text Findings in 3D Chest CT

    Jul 14, 2026Kwang-Hyun Uhm, Inhwa Son, Sung-Jea KoComputed Tomography3D Visual Grounding

  47. Understanding Structured Health Data through Interaction-Aware Mixture-of-Experts

    Jul 14, 2026Ji Hwan Park, Ying Ding, Tianjin GuoMixture-Of-Experts LayerElectronic Health Records

  48. Designing Agent-Ready Websites for AI Web Agents: A Framework for Machine Readability, Actionability, and Decision Reliability

    Jul 13, 2026Said Elnaffar, Farzad RashidiWeb AgentsWeb

  49. Auditing the Risk Claims of Distributional Reinforcement Learning

    Jul 13, 2026Hari PrasadDistributional Reinforcement LearningSafe Reinforcement Learning

  50. All you need is SAMPAT

    Jul 10, 2026Jayadeva, Madhur AswaniModel Interpretability MethodsNeural Architectures

  51. Certified Interventional Fidelity: Anytime-Valid, Adaptive Evaluation of Causal Claims in Mechanistic Interpretability

    Jul 9, 2026Amir AsiaeeModel Interpretability MethodsMechanistic Interpretability

  52. MLPTR-CC: Multi-label Pathology Test Recommendation using Classifier Chains and SHAP

    Jul 9, 2026Abu Rafe Md Jamil, Nayan MalakarModel Interpretability MethodsRecommendation

  53. Trustworthy Machine Learning through the Lens of Combinatorial Optimization: Survey and Research Perspectives

    Jul 8, 2026Thibaut Vidal, Julien FerryProbabilistic VerificationMachine Learning

  54. ExplAIner: A Declarative Query Language for Explaining Classification Models

    Jul 7, 2026Marcelo Arenas, Pablo Barceló, Diego Bustamante +3XaiModel Interpretability Methods

  55. Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers

    Jul 7, 2026Evgenii Kuriabov, David Miller, Jia LiImage ClassificationModel Interpretability Methods

  56. Driving the Wrong Way: Leveraging Interpretability in End2End Autonomous Driving Models

    Jul 7, 2026Franz Motzkus, Sebastian BernhardAutonomous DrivingModel Interpretability Methods

  57. Biologically Informed Deep Neural Networks for Multi-Omic Integration, Pathway Activity Inference and Risk Stratification in Cancer

    Jul 6, 2026Pedro Henrique da Costa Avelar, Le Ou-Yang, Min Wu +1Multi-Omic FrameworkModel Interpretability Methods

  58. SHARC: SHAP-Based Interpretability in Machine Learning Risk Models for Regulatory Capital under ICAAP and CCAR

    Jul 6, 2026Ujjwala VadrevuRegulationForward-Looking Fault-Risk Prediction

  59. Noisy-Channel Minimum Bayes Risk Decoding

    Jul 6, 2026Yusuke Sakai, Hidetaka Kamigaito, Taro WatanabeConstrained Decoding StrategiesBayesian Inference Approaches

  60. Unsupervised Features Mining via Activation Geometry

    Jul 5, 2026Amit LeVi, Elad David, Max FominModel ActivationsLLM Reasoning Methods