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Mechanistic Interpretability435 papers Model Interpretability269 papers Mechanistic Interpretability159 papers Interpretable Models38 papers Interpretable Diabetic Retinopathy Grading25 papers Interpretive Openness25 papers

541–570 of 6,027

Papers

ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows
May 13, 2026Alvaro Lopez Pellicer, Plamen Angelov, Marwan Bukhari +3Multimodal Clinical Data Mediation
Mechanistic Interpretability of EEG Foundation Models via Sparse Autoencoders
May 13, 2026William Lehn-Schiøler, Magnus Ruud Kjær, Rahul Thapa +10Electroencephalography Foundation Models Mechanistic Interpretability
Mechanistic Interpretability of ASR models using Sparse Autoencoders
May 12, 2026Dan Pluth, Zachary Nicholas Houghton, Yu Zhou +1Llm-Based Automatic Speech Recognition Speech Encoder
E-TCAV: Formalizing Penultimate Proxies for Efficient Concept Based Interpretability
May 11, 2026Hasib Aslam, Muhammad Ali Chattha, Muhammad Taha Mukhtar +3Model Interpretability Model Activations
Explanation-Aware Learning for Enhanced Interpretability in Biomedical Imaging
May 11, 2026Zubair Faruqui, Rahul DubeyModel Interpretability Multiple Instance Learning
Data-driven Circuit Discovery for Interpretability of Language Models
May 9, 2026Daking Rai, Mor Geva, Ziyu YaoCircuits Model Interpretability
Position: Mechanistic Interpretability Must Disclose Identification Assumptions for Causal Claims
May 8, 2026Zezheng Lin, Fengming LiuCausal Reasoning Mechanistic Interpretability
Patch-Effect Graph Kernels for LLM Interpretability
May 7, 2026Ruben Fernandez-Boullon, David N. OlivieriMechanistic Interpretability Heterogeneous Graph Transformers
Superposition Is Not Necessary: A Mechanistic Interpretability Analysis of Transformer Representations for Time Series Forecasting
May 6, 2026Alper YıldırımTransformer Architectures Mechanistic Interpretability
Embodied Interpretability: Linking Causal Understanding to Generalization in Vision-Language-Action Models
May 1, 2026Hanxin Zhang, Mingshuo Xu, Abdulqader Dhafer +3Causal Intervention Model Interpretability
TokenScope: Token-Level Explainability and Interpretability for Code-Oriented Tasks in Large Language Models
Apr 30, 2026Amirreza Esmaeili, Fatemeh FardCode Generation Token-Level Uncertainty
AIPsy-Affect: A Keyword-Free Clinical Stimulus Battery for Mechanistic Interpretability of Emotion in Language Models
Apr 26, 2026Michael KeemanEmotion Priming
Make Mechanistic Interpretability Auditable: A Call to Develop Guidelines via Continuous Collaborative Reviewing
Apr 24, 2026Michael Lan, Narmeen Fatimah Oozeer, Chaithanya Bandi +4Artificial Intelligence Safety Artificial Intelligence Reviewers
Contrastive Attribution in the Wild: An Interpretability Analysis of LLM Failures on Realistic Benchmarks
Apr 20, 2026Rongyuan Tan, Jue Zhang, Zhuozhao Li +3Large Language Model Performance Model Interpretability
Using Large Language Models and Knowledge Graphs to Improve the Interpretability of Machine Learning Models in Manufacturing
Apr 17, 2026Thomas Bayer, Alexander Lohr, Sarah Weiß +2Xai Model Interpretability
Structural interpretability in SVMs with truncated orthogonal polynomial kernels
Apr 16, 2026Víctor Soto-Larrosa, Nuria Torrado, Edmundo J. HuertasSupport Vector Machines Kernel Method
Interpretability and Generalization Bounds for Learning Spatial Physics
Jun 18, 2025Alejandro Francisco Queiruga, Theo Gutman-Solo, Shuai JiangPhysics-Informed Machine Learning Generalization Bounds
A Study of the Limits of Collaborative DCT-Based Image Denoising via Interpretable Neural Networks
Sep 24, 2026Cristian Comellas, Julia Navarro, Antoni BuadesImage Denoising
Detecting GPT-Assisted Writing Using Interpretable Stylometric Features
Sep 22, 2026Rajesh Kumar, Nabeel Siddiqui, Alexander FuchsbergerMachine-Generated Text Detection Human Annotators
Linguistic Features for Interpretable Textual Entailment
Sep 21, 2026David Torres-Moreno, Jorge Hermosillo-Valadez, Asela Reig-AlamilloEntailment
Null importance: Disentangling relevance for interpretable machine learning
Sep 16, 2026Garvesh Raskutti, Kris Sankaran, Jiaxin YeFeature Importance Importance
Interpretable Patch-Based Deep Learning for Wildfire Spread Prediction from Ensemble Simulations
Sep 16, 2026Marcin Lawenda, Aleksandra Krasicka, David Caballero +2Wildfire Prediction Wildfire Spread
Det-LIME: Detector-Aware, Multi-Instance Local Interpretable Model-Agnostic Explanations for Automated Marine Mammal Detection
Sep 15, 2026Jiayi Zhou, David W. Johnston, Brinnae BentDetection Framework Explainability
Concept-Grounded Reasoning with Prompt-Driven Localization for Interpretable Structured Report Generation
Sep 14, 2026Xinyue Xu, Hongbin Lin, Juangui Xu +6Multimodal Clinical Data Medical Report Generation
AXS-Net: Interpretable Deep Unfolding for Hyperspectral Image Denoising via Spectral Basis Unmixing and Structured Noise Refinement
Sep 8, 2026Ziyi Guan, Jianping Zhang, Zheng YangHyperspectral Unmixing Image Denoising
Vision: Data-Centric Anchoring for Robust and Interpretable Agentic AI
Sep 8, 2026Arun Vignesh Malarkkan, Xinyuan Wang, Yanjie FuAgent Loop Taxonomy
Differentiable Interval Bottlenecks for Interpretable Anomaly Detection in Numerical Data
Sep 3, 2026Lamine Diop, Marc PlantevitReconstruction-Based Anomaly Detection Anomaly Detection
CAHR-Net: Condition-Adaptive Hysteresis Reconstruction for Compact and Interpretable Magnetic Core Loss Modeling
Sep 2, 2026Chunye Gong, Cong YaoMagnetic Tunnel Junction
Lightweight Interpretable RGB-Guided Hyperspectral Super-Resolution under Real Cross-resolution Misalignment
Sep 1, 2026Mohamad Jouni, Aurélien Godet, Mauro Dalla MuraHyperspectral Image Super-Resolution Hyperspectral Imaging
VisLens: Single-Pass Interpretable Visual Search for Multimodal LLMs
Aug 31, 2026Jingyi He, Sanghwan Kim, Zeynep AkataMultiple Vision Tasks Multi-Modal Large Language Models

May 13, 2026 · cs.CVJ/K move · Enter open · S save

ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows

Alvaro Lopez Pellicer, Plamen Angelov, Marwan Bukhari, Yi Li+2

School of Computing and Communications, Lancaster University · Lancaster Medical School, Lancaster University · PUC-Rio, Puc-Behring Institute for AI

While interpretable prototype networks offer compelling case-based reasoning for clinical diagnostics, their raw continuous outputs lack the semantic structure required for medical documentation. Bridging this gap via standard Retrieval-Augmented Generation (RAG) routinely triggers ``retrieval sycophancy,'' where Large Language Models (LLMs) hallucinate post-hoc rationalizations to align with visual predictions. We introduce ProtoMedAgent, a framework that formalizes multimodal clinical reporting as an iterative, zero-gradient test-time optimization problem over a strict neuro-symbolic bottleneck. Operating on a frozen prototype backbone, we distill latent visual and tabular features into a discrete semantic memory. Online generation is strictly constrained by exact set-theoretic differentials and a reflective Scribe-Critic loop, mathematically precluding unsupported narrative claims. To safely bound data disclosure, we introduce a semantic privacy gate governed by

k

-anonymity and

\ell

-diversity. Evaluated on a 4,160-patient clinical cohort, ProtoMedAgent achieves 91.2% Comparison Set Faithfulness where it fundamentally outperforms standard RAG (46.2%). ProtoMedAgent additionally leverages a binding

\ell

-diversity phase transition to systematically reduce artifact-level membership inference risks by an absolute 9.8%.

Multimodal Clinical Data Mediation Model Interpretability Agentic Workflows Long-Term Memory

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