Explainable AI Methods

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23 papers in the last four weeks, up 10% on the four weeks before. 0.3% of all new papers.

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Latest papers 230

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Concept-Based Abductive and Contrastive Explanations for Behaviors of Vision Models
May 7, 2026Ronaldo Canizales, Divya Gopinath, Corina Păsăreanu +1Explainability Explainable AI Methods
Colorado State University, Fort Collins CO, USA · KBR Inc., NASA Ames, Moffett Field CA, USA · Carnegie Mellon University, Pittsburgh PA, USA
eXplaining to Learn (eX2L): Regularization Using Contrastive Visual Explanation Pairs for Distribution Shifts
May 7, 2026Paulo Mario P. Medina, Jose Marie Antonio Miñoza, Sebastian C. IbañezDistribution Shifts Contrastive Learning
Center for AI Research
Temporal Functional Circuits: From Spline Plots to Faithful Explanations in KAN Forecasting
May 7, 2026Naveen MysoreKolmogorov-Arnold Networks Splines
University of California, Santa Barbara
Explaining and Preventing Alignment Collapse in Iterative RLHF
May 5, 2026Etienne Gauthier, Francis Bach, Michael I. JordanReinforcement Learning From Human Feedback Frictive Policy Optimization
Inria, Ecole Normale Sup´erieure, PSL Research University · Ecole Normale Sup´erieure, PSL Research University · PSL Research University +1
Learning to Theorize the World from Observation
May 5, 2026Doojin Baek, Gyubin Lee, Junyeob Baek +2Theory-Of-Mind Reasoning Theory
KAIST
Graph Reconstruction from Differentially Private GNN Explanations
May 5, 2026Rishi Raj Sahoo, Jyotirmaya Shivottam, Subhankar MishraGraph Neural Networks Gradient-Based Attacks
National Institute of Science Education and Research (NISER), Bhubaneswar, India · Homi Bhabha National Institute, Mumbai, India
SAIL: Structure-Aware Interpretable Learning for Anatomy-Aligned Post-hoc Explanations in OCT
May 4, 2026Tienyu Chang, Tianhao Li, Ruogu Fang +2Optical Coherence Tomography Retinal Imaging
Dept. of BioHealth Informatics, Indiana University Indianapolis, Indiana, USA · School of Information, University of Texas at Austin Austin, Texas, USA · Dept. of Biomedical Engineering, University of Florida Gainesville, Florida, USA +1
Less Interaction But More Explanation: A Communication Perspective on Agentic AI Interfaces
May 2, 2026Eunchae Jang, S. Shyam SundarInteraction Data Human Agency
Media Effects Research Laboratory, Pennsylvania State University, Pennsylvania, USA · Center for Socially Responsible AI, Pennsylvania State University, Pennsylvania, USA
KG-First, LLM-Fallback: A Hybrid Microservice for Grounded Skill Search and Explanation
May 2, 2026Ngoc Luyen Le, Marie-Hélène Abel, Bertrand LaforgeSkills Knowledge Graphs
Gamaizer.ia, 93340 Le Raincy, France · Université de technologie de Compiègne, CNRS, Heudiasyc (Heuristics and Diagnosis of Complex Systems), CS 60319 - 60203 Compiègne Cedex, France · Sorbonne Université, CNRS UMR 7585, LPMHE (Laboratoire de Physique Nucléaire et des Hautes Énergies), 75252 Paris cedex 05, France
Rethinking Explanations: Formalizing Contrast in Description Logics
May 2, 2026Yasir Mahmood, Arnab Sharma, Axel-Cyrille Ngonga Ngomo +1Explainable AI Methods Axiom
Data Science Group, Heinz Nixdorf Institute, Paderborn University Germany
LLMs Should Not Yet Be Credited with Decision Explanation
May 1, 2026Wenshuo WangLarge Language Model Decisions Explainable AI Methods
School of Future Technology, South China University of Technology, China
Fairness of Classifiers in the Presence of Constraints between Features
May 1, 2026Martin C. Cooper, Imane BousdiraAlgorithmic Fairness Classifier
IRIT, University of Toulouse · IRIT, Toulouse INP
Are You the A-hole? A Fair, Multi-Perspective Ethical Reasoning Framework
Apr 30, 2026Sheza Munir, Ahanaf Rodoshi, Sumin Lee +3Ethics Disagreement
Computer Science, University of Toronto
Minimal, Local, Causal Explanations for Jailbreak Success in Large Language Models
Apr 30, 2026Shubham Kumar, Narendra AhujaLarge Language Model Jailbreaks Jailbreak Attacks
University of Illinois Urbana-Champaign
Ceci n'est pas une explication: Evaluating Explanation Failures as Explainability Pitfalls in Language Learning Systems
Apr 28, 2026Ben Knight, Wm. Matthew Kennedy, Danielle Carvalho +2Large Language Models Fail Explainable AI Methods
Oxford University Press, UK · Oxford Internet Institute University of Oxford, UK
Explanation of Dynamic Physical Field Predictions using WassersteinGrad: Application to Autoregressive Weather Forecasting
Apr 24, 2026Younes Essafouri, Laure Raynaud, Luciano Drozda +1Artificial Intelligence Weather Models Scalar Field
Univ. Toulouse, INSA Toulouse, CNRS UMR 5219, IMT, Toulouse, France · Météo-France, CNRS, Univ. Toulouse, CNRM, Toulouse, France · Cerfacs, CNRS/Cerfacs/IRD, CECI, Toulouse, France
Evaluating Post-hoc Explanations of the Transformer-based Genome Language Model DNABERT-2
Apr 23, 2026Isabel Kurth, Paulo Yanez Sarmiento, Bernhard Y. RenardGenome-Wide Association Study Explainable AI Methods
Hasso Plattner Institute University of Potsdam
Fine-Grained Perspectives: Modeling Explanations with Annotator-Specific Rationales
Apr 23, 2026Olufunke O. Sarumi, Charles Welch, Daniel BraunHuman Annotators Explainable AI Methods
Marburg University, Marburg, Germany · McMaster University, Hamilton, Ontario, Canada
Mind the Prompt: Self-adaptive Generation of Task Plan Explanations via LLMs
Apr 22, 2026Gricel Vázquez, Alexandros Evangelidis, Sepeedeh Shahbeigi +2Large Language Model Planning Automatic Prompt Optimization
University of York, UK · Cyprus University of Technology, Cyprus
Concept Graph Convolutions: Message Passing in the Concept Space
Apr 22, 2026Lucie Charlotte Magister, Pietro LioGraph Neural Networks Edge-Aware
University of Cambridge
Detecting AI-Generated Content on Social Media with Multi-modal Language Models
Apr 21, 2026Chenyang Yang, Shen Yan, Yibo Yang +13Ai-Generated Content Detection Generative Artificial Intelligence
Carnegie Mellon University · Meta
PREF-XAI: Preference-Based Personalized Rule Explanations of Black-Box Machine Learning Models
Apr 21, 2026Salvatore Greco, Jacek Karolczak, Roman Słowiński +1Explainable Artificial Intelligence Preference Learning
University of Catania, Department of Economics and Business, Corso Italia 55, Catania, 95129, Italy · Poznan University of Technology, Institute of Computing Science,2026 Piotrowo 2, Poznań, 60-965, Poland · bPoznan University of Technology, Institute of Computing Science,2026 Piotrowo 2, Poznań, 60-965, Poland +1
From Top-1 to Top-K: A Reproducibility Study and Benchmarking of Counterfactual Explanations for Recommender Systems
Apr 21, 2026Quang-Huy Nguyen, Thanh-Hai Nguyen, Khac-Manh Thai +6Counterfactual Explanation Explainable AI Methods
VNU University of Engineering and Technology · Delft University of Technology
TACENR: Task-Agnostic Contrastive Explanations for Node Representations
Apr 21, 2026Vasiliki Papanikou, Evaggelia PitouraGraph Representation Learning Explainable AI Methods
University of Ioannina, Greece · Archimedes/Athena Research Center, Greece
On the Importance and Evaluation of Narrativity in Natural Language AI Explanations
Apr 20, 2026Mateusz Cedro, David MartensExplainable Artificial Intelligence Explainable AI Methods
University of Antwerp, Belgium
From Scoring to Explanations: Evaluating SHAP and LLM Rationales for Rubric-based Teaching Quality Assessment
Apr 18, 2026Ivo Bueno, Babette Bühler, Philipp Stark +5Rubric-Based Scoring Free-Form Textual Rationales
1Technical University of Munich · 2Munich Center for Machine Learning (MCML) · 3Lund University +3
The Query Channel: Information-Theoretic Limits of Masking-Based Explanations
Apr 17, 2026Erciyes Karakaya, Ozgur ErcetinInformation-Theoretic Limits Explainable AI Methods
*Department of Electrical and Computer Engineering, University of Maryland, College Park, USA · †Faculty of Engineering and Natural Sciences, Sabanci University, Turkiye
Explain the Flag: Contextualizing Hate Speech Beyond Censorship
Apr 16, 2026Jason Liartis, Eirini Kaldeli, Lambrini Gyftokosta +2Hate Speech Detection Hate Speech
National Technical University of Athens · Datoptron · Independent Researcher +3
Rethinking Patient Education as Multi-turn Multi-modal Interaction
Apr 16, 2026Zonghai Yao, Zhipeng Tang, Chengtao Lin +5Multimodal Clinical Data Medical Visual Question Answering
1VA Bedford Health Care · 2UMass Amherst · 4Yale University +3
Robust Explanations for User Trust in Enterprise NLP Systems
Apr 13, 2026Guilin Zhang, Kai Zhao, Jeffrey Friedman +3Large Language Model Reliability Explainability
Workday AI Research
Exploring Plan Space through Conversation: An Agentic Framework for LLM-Mediated Explanations in Planning
Mar 2, 2026Guilhem Fouilhé, Rebecca Eifler, Antonin Poché +2Large Language Model Planning Agentic Framework
IRIT, Toulouse, France · LAAS-CNRS, Toulouse, France · IRT Saint Exupery, Toulouse, France +2
Quantifying Retriever-Generator Alignment in RAG with Local Explanations
Jan 29, 2026Korbinian Randl, Guido Rocchietti, Aron Henriksson +3Agentic Retrieval-Augmented Generation Systems Explainability
Department of Computer and Systems Sciences, Stockholm University, Sweden · BIFOLD, Technische Universität Berlin, Germany · Department of Informatics, Athens University of Economics and Business, Greece +1
TxSum: User-Centered Ethereum Transaction Understanding with Micro-Level Semantic Grounding
Dec 7, 2025Zifan Peng, Jingyi Zheng, Yule Liu +8Bitcoin Transaction Evidence
1Hong Kong University of Science and Technology (Guangzhou) · 3Independent Researcher · University of North Texas +2
Critical or Compliant? The Double-Edged Sword of Reasoning in Chain-of-Thought Explanations
Nov 15, 2025Eunkyu Park, Wesley Hanwen Deng, Vasudha Varadarajan +4Chain-of-Thought Reasoning Reasoning Errors
Seoul National University · Human-Computer Interaction Institute, Carnegie Mellon University · Language Technologies Institute, Carnegie Mellon University
Multi-Step Knowledge Interaction Analysis via Rank-2 Subspace Disentanglement
Nov 3, 2025Sekh Mainul Islam, Pepa Atanasova, Isabelle AugensteinLLM Reasoning Strategies Contextual Grounding
University of Copenhagen
Activation-Deactivation: A General Framework for Robust Post-hoc Explainable AI
Oct 1, 2025Akchunya Chanchal, David A. Kelly, Hana ChocklerExplainability Explainable Artificial Intelligence
Department of Informatics King’s College London Strand, WC2R 2LS, London, UK
Cross-Attention is Half Explanation in Speech-to-Text Models
Sep 22, 2025Sara Papi, Dennis Fucci, Marco Gaido +2Cross-Attention Natural Language Processing
Fondazione Bruno Kessler, Italy
Ultra Strong Machine Learning: LLM-Generated Explanations Do Not Yet Suffice for Teaching Humans Active Learning Strategy
Aug 31, 2025Lun Ai, Johannes Langer, Ute Schmid +1Active Learning Interactive Learning
Department of Computing, Imperial College London, UK · Faculty Information Systems and Applied Computer Science, University of Bamberg, Germany
Explain Before You Answer: A Survey on Compositional Visual Reasoning
Aug 24, 2025Fucai Ke, Joy Hsu, Zhixi Cai +10Visual Reasoning Multimodal Reasoning
Monash University · Stanford University · University of Washington +3
Rule2Text: A Framework for Generating and Evaluating Natural Language Explanations of Knowledge Graph Rules
Aug 14, 2025Nasim Shirvani-Mahdavi, Chengkai LiKnowledge Graphs Explainable AI Methods
University of Texas at Arlington, Arlington, Texas 76019, USA
A Communication-First Account of Explanation
May 6, 2025Jacqueline Harding, Tobias Gerstenberg, Thomas IcardExplainable AI Methods Causal
Stanford University
Truthful or Fabricated? Using Causal Attribution to Mitigate Reward Hacking in Explanations
Apr 7, 2025Pedro Ferreira, Wilker Aziz, Ivan TitovExplainable AI Methods Chain-of-Thought Reasoning
Institute for Logic, Language and Computation (ILLC), University of Amsterdam · Institute for Language, Cognition and Computation (ILCC), University of Edinburgh
Verbosity Tradeoffs and the Impact of Scale on the Faithfulness of LLM Self-Explanations
Mar 17, 2025Noah Y. Siegel, Nicolas Heess, Maria Perez-Ortiz +1Faithfulness Explainable AI Methods
Google DeepMind · Centre for AI, University College London · Imperial College London +1
Robust Counterfactual Explanations under Model Multiplicity Using Multi-Objective Optimization
Jan 10, 2025Keita KinjoCounterfactual Explanation Explainability
Faculty of Business, Kyoritsu Women’s University, 2-2-1 Hitotsubashi, Chiyoda-ku, 101-8437, Tokyo, Japan.
Causal Explanations for Image Classifiers
Nov 13, 2024Hana Chockler, David A. Kelly, Daniel Kroening +1Explainability Explainable AI Methods
King’s College London, London, UK · Amazon.com, Inc.,, USA · Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, UAE +1
Towards Complete Causal Explanation with Expert Knowledge
Jul 10, 2024Aparajithan Venkateswaran, Emilija PerkovićAcyclic Graphs Causal
Microsoft · Redmond, WA 98052, USA · Department of Statistics +2
Dont Just Teach, Explain! A Gamified 20Q Recommender for Cybersecurity Education
Date pendingMary Nusrat, Sarfuddin Bhuiyan, Gahangir HossainCybersecurity Interactive Learning
Information Science, University of North Texas, Denton, TX, USA · Mechanical Engineering, Bangladesh University of Eng. and Tech., BUET, Dhaka, Bangladesh
SAEExplainer: Interpreting SAE Features with Activation-Guided Preference Optimization
Date pendingJingyi He, Haiyan Zhao, Ruxue Shi +4Sparse Autoencoder Features Explainable AI Methods
The Chinese University of Hong Kong, Shenzhen · Shanghai Jiao Tong University · NJIT +2
Limitations of Automated Simulatability: LLM Simulators Can Bypass Explanations
Date pendingAntonin Poché, Fanny Jourdan, Nils Feldhus +6User Simulation Explainable AI Methods
IRT Saint Exupéry · IRIT, Université de Toulouse · University of Groningen +7
PACE: A Neuro-Symbolic Framework for Plausible and Actionable Counterfactual Explanations
Date pendingPavel Iakovets, Liyanapathiranage Sudeepika Wajirakumari Samarathunga, Martin Thomas Horsch +1Counterfactual Explanation Explainable Artificial Intelligence
University of Klagenfurt, Universitätsstraße 65/67, 9020 Klagenfurt am Wörthersee, Austria · Norwegian University of Life Sciences, Elizabeth Stephansens v. 15, 1433 ˚As, Norway

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Concept-Based Abductive and Contrastive Explanations for Behaviors of Vision Models

Ronaldo Canizales, Divya Gopinath, Corina Păsăreanu, Ravi Mangal

Colorado State University, Fort Collins CO, USA · KBR Inc., NASA Ames, Moffett Field CA, USA · Carnegie Mellon University, Pittsburgh PA, USA

Explainability Explainable AI Methods Vision Foundation Models Concept Bottleneck Models Abductive Reasoning Agent Behavior Modeling+1

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Concept-based explanations offer a promising approach for explaining the predictions of deep neural networks in terms of high-level, human-understandable concepts. However, existing methods either do not establish a causal connection between the concepts and model predictions or are limited in expressivity and only able to infer causal explanations involving single concepts. At the same time, the parallel line of work on formal abductive and contrastive explanations computes the minimal set of input features causally relevant for model outcomes but only considers low-level features such as pixels. Merging these two threads, in this work, we propose the notion of concept-based abductive and contrastive explanations that capture the minimal sets of high-level concepts causally relevant for model outcomes. We then present a family of algorithms that enumerate all minimal explanations while using concept erasure procedures to establish causal relationships. By appropriately aggregating such explanations, we are not only able to understand model predictions on individual images but also on collections of images where the model exhibits a user-specified, common behavior. We evaluate our approach on multiple models, datasets, and behaviors, and demonstrate its effectiveness in computing helpful, user-friendly explanations.

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