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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Nudging Sustainable Choices through LLM-Generated Recommendation Explanations
Jul 28, 2026Haya Halimeh, Dietmar Jannach, Oliver MüllerNudges Sustainability
Paderborn University, Germany · University of Klagenfurt, Austria
AIriskEval-edu Demo: Auditing of Pedagogical Risks in Educational Explanations
Jul 28, 2026Javier Irigoyen, Roberto Daza, Francisco Jurado +5Artificial Intelligence Risk Model Auditing
BiometricsAI, Universidad Autónoma de Madrid (UAM), Spain · GHIA, Universidad Autónoma de Madrid (UAM), Spain · Universidad de Las Palmas de Gran Canaria (ULPGC), Spain
Evaluating the Impact of Explainable AI on Trust in AI-Assisted Code Review
Jul 27, 2026Zhenhan Gao, Marvin Muñoz Barón, Umm-e Habiba +2Code Quality Explainable Artificial Intelligence
Technical University of Munich, Heilbronn, Germany · University of Hohenheim, Hohenheim, Germany
Success Is Not Self-Explanatory: Auditing Success Provenance in Agent Evaluation
Jul 27, 2026Jingkun Luo, Da-Tian PengAgentic Evaluations Generation Provenance
Northwestern Polytechnical University
Gaze-to-text Generation: Beyond Categorical Decoding of Human Attention
Jul 27, 2026Sounak Mondal, Dimitris Samaras, Gregory Zelinsky +1Co-Speech Gesture Generation Transcript
Stony Brook University, Stony Brook, New York, USA · Australian Institute for Machine Learning, Adelaide University, Australia
Explaining BiomedCLIP with Weighted Banzhaf Interactions Supported by Tree-Gram Parsing
Jul 25, 2026Jakub Rymarski, Adam Rempała, Bartłomiej Sobieski +1Medical Vision-Language Models Explainable AI Methods
University of Warsaw, Poland · Centre for Credible AI, Warsaw University of Technology, Poland
Towards Faithful Graph Explanations with Synergistic Edge Effects via Granular Balls
Jul 23, 2026Jiancu Chen, Shuyin Xia, Guan Wang +2Graph Neural Networks Subgraphs
Chongqing Key Laboratory of Computational Intelligence, Key Laboratory of Big Data Intelligent Computing, Key Laboratory of Cyberspace Big Data Intelligent Security, Ministry of Education, School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China · School of Computer Science and Engineering, Chongqing Three Gorges University, Chongqing, China
Explaining Weather Bulletins via ILP
Jul 23, 2026Enrico Santi, Alessandro Dal Palù, Agostino Dovier +2Weather Prediction Explainable AI Methods
University of Udine, DMIF · University of Udine, DMIF, Udine, Italy · University of Parma, SMFI +1
Training Large Language Models for Self-Explanation Faithfulness
Jul 23, 2026Yeoktatt Cheah, María Pérez-Ortiz, Noah Y. Siegel +1LLM Reasoning Strategies Large Language Model Reinforcement Learning
Centre for AI, Department of Computer Science University College London · Imperial College London
HalluTruthQA: A Fine-Grained Benchmark for Hallucination Detection, Localization, and Explanation in Arabic Question Answering
Jul 22, 2026Abdessalam Bouchekif, Mohammed-En-Nadhir Zighem, Salah Eddine Bekhouche +9Hallucination Detection Arabic
Hamad Bin Khalifa University, Qatar · University of the Basque Country, Spain · University of Biskra, Algeria +2
Semantic Primes as Explanans for Emotion in Large Language Models
Jul 21, 2026Frank XingEmotion Explainable AI Methods
University of Reading
Attention Without Grounding: Causal Evaluation of Visual Explanations in Medical VLMs
Jul 20, 2026Binesh Sadanandan, Vahid BehzadanMedical Vision-Language Models Explainable AI Methods
SAIL Lab, University of New Haven, West Haven, CT, USA
Human Grounded Evaluation of Large Language Models for Optical Network Automation
Jul 20, 2026Kiarash Rezaei, Omran Ayoub, Paolo Monti +1Large Language Model Evaluation Optical Networks
Department of Electrical Engineering, Chalmers University of Technology, 412 96 Gothenburg, Sweden · University of Applied Sciences and Arts of Southern Switzerland, 6928 Lugano, Switzerland
Financial Audit Assistance using Misinformation Detection and Explanation
Jul 20, 2026Kshitij Madhav Jadhav, Sushodhan Vaishampayan, Manoj Apte +3Misinformation Detection Financial Question Answering
TCS Research, Pune, 411057, Maharashtra, India. · Work done while working at TCS Research.
Medical Imaging Fusing Vision Transformer: Laryngeal Cancer Screening with Explanation
Jul 20, 2026Haiyang Wang, Luca MainardiColonoscopy Medical Imaging
Department of Electrical, Information and Bioengineering Polytechnic University of Milan Milan, Italy · Department of of Electrical, Information and Bioengineering Polytechnic University of Milan Milan, Italy
Explaining and Tuning Transformer-based LLMs in Arithmetic Tasks with Human Strategies
Jul 19, 2026Luyu Qiu, Jianing Li, Hwanhee Kim +4Transformer Architectures Task Arithmetic
1The Hong Kong University of Science and Technology · 2The Hong Kong Polytechnic University · University of California, Berkeley
From Plausible to Actionable: A Position on LLM Self-Explanations
Jul 17, 2026Elize Herrewijnen, Benedetta Muscato, Gizem Gezici +1Explainable Artificial Intelligence Explainable AI Methods
University of Utrecht, Utrecht, Netherlands · National Police Lab AI, Netherlands Police, Driebergen, Netherlands · Scuola Normale Superiore, Pisa, Italy +1
CoTu at EXACT 2026: Neuro-Symbolic Reasoning for Transparent Educational QA
Jul 16, 2026Quoc-Khang Tran, Minh-Thien Nguyen, Phu-An Thai +3Faithful Question Generation Neuro-Symbolic Framework
Can Tho University, Can Tho city, Vietnam · Tay Do University, Can Tho city, Vietnam
All Explanations are Wrong, But Many Are Useful: Exploring the Rashomon Explanation Set with Large Language Models
Jul 10, 2026Pan LiExplainable Artificial Intelligence Explainable AI Methods
Scheller College of Business, Georgia Tech.
Steering Neural Network Training through Interpretable Constraints Based on Partial Dependence
Jul 9, 2026Yann Claes, Pierre Geurts, Vân Anh Huynh-ThuExplainable AI Methods Structural Constraints
Montefiore Institute University of Liège
Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers
Jul 7, 2026Evgenii Kuriabov, David Miller, Jia LiRobustness Verification Classifier
Department of Statistics, The Pennsylvania State University, University Park, PA 16802, USA · Department of Electrical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
XPlainVerse: A Million-Scale Benchmark for Explainable Deepfake Detection
Jul 3, 2026Abhijeet Narang, Kartik Kuckreja, Shreya Ghosh +3Deepfake Detection Large-Scale Benchmark
Monash University · MBZUAI · The University of Queensland
AIriskEval-edu: New Dataset for Risk Assessment in AI-mediated K-12 Educational Explanations
Jul 2, 2026Javier Irigoyen, Roberto Daza, Francisco Jurado +5Artificial Intelligence Education Computerized Adaptive Testing
BiometricsAI, Universidad Aut´onoma de Madrid (UAM), Spain · GHIA, Universidad Aut´onoma de Madrid (UAM), Spain · Universidad de Las Palmas de Gran Canaria (ULPGC), Spain
Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data
Jul 2, 2026Emmanuel C. Chukwu, Rianne M. Schouten, Monique Tabak +1Counterfactual Explanation Rehabilitation
Eindhoven University of Technology Eindhoven, the Netherlands · University of Twente Enschede, the Netherlands
BFF: Simple explanations for complex phenomena
Jul 1, 2026Charlotte Knierim, Luca Versari, Robert Obryk +2Self-Organization Explainable AI Methods
Google, Paradigms of Intelligence Team
Bi-NAS: Towards Effective and Personalized Explanation for Recommender Systems via Bi-Level Neural Architecture Search
Jul 1, 2026Longfeng Wu, Yao Zhou, Tong Zeng +5Explainable AI Methods Neural Architecture Search
Virginia Tech Blacksburg, VA, USA · Google Mountain View, CA, USA · Amazon Sunnyvale, CA, USA
Faithful by Definition: Emotion Analysis via Natural Semantic Metalanguage Explications
Jul 1, 2026Frank Xing, Erik CambriaEmotion Recognition Explainable AI Methods
University of Reading · Nanyang Technological University
Introspective Coupling: Self-Explanation Training Tracks Behavioral Change Despite Fixed Supervision
Jun 30, 2026Zifan Carl Guo, Laura Ruis, Jacob Andreas +1Introspection Adapters Explainable AI Methods
MIT EECS
Measuring Judgment Quality in Natural-Language Explanations: Evidence from Forecasting Tournaments
Jun 29, 2026Christopher W. Karvetski, Sheldon S. Huang, Simas Kučinskas +4Large Language Model Forecasting Forecast
Forecasting Research Institute · Good Judgment Inc · University of Toronto +4
GRAPE: Graph-Augmented Prototype Explanations for Interactive Medical Image Diagnosis
Jun 29, 2026Rasul Khanbayov, Erchin Serpedin, Hasan KurbanLesion Diagnosis
1Hamad Bin Khalifa University · 2Texas A&M University
Does Role Specialization Matter for Explanation Faithfulness in Mixture-of-Experts?
Jun 28, 2026Yeji Kim, Housam Babiker, Mi-Young Kim +1Mixture-Of-Experts Faithful Explanation
University of Alberta, Edmonton, AB, Canada · University of Waikato, Hamilton, New Zealand · University of Alberta, Camrose, AB, Canada
Understanding LLM Intervention Explanations in Multi-Party Human-Robot Interaction
Jun 28, 2026Micol Spitale, Massimiliano Nigro, Emily CrossHuman-Ai Interaction Human-Robot Interaction
Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy · GESS Department, ETH Zurich, Zurich, Switzerland
Reliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific Models
Jun 28, 2026Nick Oh, Helen JinExplainable AI Methods Post-Hoc
socius labs, London, United Kingdom · Department of Computer and Information Science, University of Pennsylvania, Philadelphia, Pennsylvania, United States.
Exploring the Value of Diverse LLM Explanations in Introductory Programming
Jun 27, 2026Seth Bernstein, Paul Denny, Juho Leinonen +4Ai-Assisted Programming Tasks Computer Science
Temple University Philadelphia, PA, United States · University of Auckland Auckland, New Zealand · Aalto University Espoo, Finland
Majority Vote Silences Minority Values: Annotator Disagreement at the Hate/Offensive Boundary in HateXplain
Jun 27, 2026Joshua Muhumuza, Joab Ezra Agaba, Mercy AmiyoHate Speech Detection Disagreement
Makerere University, Kampala, Uganda.
AnTenA: Actionable and Explainable Tensor Analysis System with Large Language Models
Jun 27, 2026Dawon Ahn, Auder Der, Evangelos E. PapalexakisExplainable AI Methods Model Discovery
University of California, Riverside CA 92507, USA · Neuralix AI, Houston, TX, USA
What LLMs explain is not what they believe: Evaluating explanation sufficiency under models' own input beliefs
Jun 26, 2026Nhi Nguyen, Shauli Ravfogel, Rajesh RanganathLLM Reasoning Strategies Explainable AI Methods
New York University
OperatorSHAP: Fast and Accurate Shapley Value Estimation for Neural Operators
Jun 26, 2026Joshua Stiller, Santo M. A. R. Thies, Felix Czaja +1Shapley Additive Explanations Shapley Value
LMU Munich, MCML · LMU Munich · LMU Munich, MCML, DFKI
Global Explanations for Multivariate Time Series Forecasting Models via $K$ -Order Markov Approximations
Jun 25, 2026Amadeo TunyiMultivariate Time Series Forecasting Temporal Dependence
XITASO GmbH Austraße 35, 86153 Augsburg, Germany
BetXplain: An Explanation-Annotated Dataset for Detecting Manipulative Betting Advertisements on Social Media
Jun 25, 2026MSVPJ Sathvik, Parmitha Vangapandu, Nishit Rane +3Ads Social Media
University of Birmingham, UK · IIIT Dharwad, India · NUS, Singapore +1
Explaining Temporal Graph Neural Networks via Feature-induced Information Flow
Jun 25, 2026Ping Xiong, Thomas Schnake, Klaus-Robert Müller +1Temporal Graph Neural Networks Information-Flow Control
Berlin Institute for the Foundations of Learning and Data – BIFOLD, 10623 Berlin, Germany · Machine Learning Group, Technical University of Berlin, Berlin, Germany · Department of Chemistry, Chemical Physics Theory Group, University of Toronto, Toronto, Canada +5
auto-psych: Automating the science of mind using agent-driven theory discovery and experimentation
Jun 24, 2026Ben Prystawski, Kushin Mukherjee, Daniel Wurgaft +4Artificial Intelligence Scientists Psychology
Department of Psychology, Stanford University · Department of Computer Science, Stanford University
Few-class Fidelity: Evaluating Explanations of Real-conditions CNN classifiers with Optimized Perturbations
Jun 23, 2026Wistan Marchadour, Pedro Soto Vega, Franck Vermet +1Xai Explainable Artificial Intelligence
LaTIM, INSERM, UMR 1101, Univ Brest, Brest, France · LMBA, CNRS, UMR 6205, Univ Brest, Brest, France
Cycle-Consistent Neural Explanation of Formal Verification Certificates
Jun 23, 2026Andoni Rodriguez, Alberto Pozanco, Daniel BorrajoFormal Verification Neural Network Verification
J.P. Morgan AI Research
Can Language Model Agents be Helpful Circuit Explainers in Mechanistic Interpretability?
Jun 23, 2026Ayan Antik Khan, Harsh Kohli, Yuekun Yao +2Mechanistic Interpretability Explainable AI Methods
George Mason University · The Ohio State University
Trustworthy Image Authentication using Forensic Knowledge Graphs
Jun 22, 2026Tai D. Nguyen, Matthew C. StammDigital Forensics Knowledge Graphs
Drexel University, Philadelphia, PA 19104, USA
UnBias-Plus: Detect, Explain, and Rewrite Bias
Jun 22, 2026Ahmed Y. Radwan, Ahmed ElKady, Sindhuja Chaduvula +3Rewrite Paraphrasing
Vector Institute for Artificial Intelligence, Toronto, Canada · Independent Researcher
A Completion-Aware Framework for Impactful Counterfactual Explainability in Graph Neural Networks
Jun 20, 2026Maria Myrto Villia, Filippos Gouidis, Theodore Patkos +1Counterfactual Explanation Graph Neural Networks
Institute of Computer Science, Foundation for Research and Technology - Hellas (FORTH), Heraklion, Greece · Computer Science Department, University of Crete, Greece
Towards Dys-XAI: Influence-Based Explanations for Dysarthria Severity Assessment
Jun 19, 2026Xiaoliang Wu, Qiyang Sun, Yupei Li +3Explainability Xai
University of Southampton, United Kingdom · Imperial College London, United Kingdom · University of Edinburgh, United Kingdom +1
GLARE: A Natural Language Interface for Querying Global Explanations
Jun 18, 2026Bhavan Vasu, Rajesh MangannavarExplainable AI Methods
Oregon State University, Corvallis OR 97330, USA
CIExplainer++: Generating Causal and Interpretable Explanations for Graph Neural Networks
Jun 17, 2026Francisco Caldas, Sahil Satish Kumar, Ruben Belo +1Explainable Artificial Intelligence Causal Graph
NOVA LINCS, NOVA School of Science and Technology, Lisbon, Portugal
P $^2$ CE: Model-Agnostic Plausible Pareto-Optimal Counterfactual Explanations
Jun 16, 2026Arthur Hendricks Mendes de Oliveira, Giovani Valdrighi, Marcos Medeiros RaimundoCounterfactual Explanation Shapley Additive Explanations
Instituto de Computa¸c˜ao, Universidade Estadual de Campinas, Albert Einstein Avenue, Campinas, 13083-889, S˜ao Paulo, Brazil.
From Sparse Features to Trustworthy Proxies: Certifying SAE-Based Interpretability
Jun 16, 2026Dibyanayan Bandyopadhyay, Asif EkbalInterpretability Model Activations
Department of Computer Science and Engineering, Indian Institute of Technology Patna, Bihar, India.
Self-CTRL: Self-Consistency Training with Reinforcement Learning
Jun 16, 2026Itamar Pres, Laura Ruis, Melat Ghebreselassie +2Artificial Intelligence Alignment Explainable AI Methods
MIT CSAIL
SPHINX: First Explain, Then Explore
Jun 16, 2026Nguyen Do, Tue M. Cao, Tien Van Do +3Scenario Generation Autonomous Driving Simulation
University of Florida, Gainesville, Florida, USA · Budapest University of Technology and Economics, Department of Networked Systems and Services, Budapest, Hungary · University of Debrecen, Debrecen, Hungary
Translating the Untranslatable: An Operationalizable Ontology for Untranslatability
Jun 15, 2026Jacob Bremerman, Brihi Joshi, Hirona Arai +2Translation Quality Ontology
University of Southern California Information Sciences Institute
We Need Explanation Cards to Connect Explanation Algorithms to the Real World
Jun 15, 2026Eric Günther, Balázs Szabados, Kristof Meding +3Explainability Explainable AI Methods
University of Tübingen · Tübingen AI Center · HUN-REN Institute for Computer Science and Control (SZTAKI), Budapest, Hungary
XAI-Grounded Explanation Generation for Speech Deepfake Detection with Training-Free Multimodal Large Language Models
Jun 15, 2026Yupei Li, Qiyang Sun, Xiaoliang Wu +3Speech Language Models Explainable Artificial Intelligence
Imperial College London, United Kingdom · University of Southampton, United Kingdom · MBZUAI, United Arab Emirates +2
A Definition of Good Explanations and the Challenges Explaining LLM Outputs
Jun 12, 2026Louis Mahon, Elliot Ford, Callum HackettExplainable AI Methods Explainability
UnlikelyAI, London, UK
The Perceived Fragility of Explanations in Audio Models: Manipulation of Attribution with Unchanged Predictions
Jun 12, 2026Piotr Kitłowski, Dominik Wiącek, Mateusz ModrzejewskiAudio Deepfake Detection Explainable AI Methods
Faculty of Electronics and Information Technology, Warsaw University of Technology, Warsaw, Poland.

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Nudging Sustainable Choices through LLM-Generated Recommendation Explanations

Haya Halimeh, Dietmar Jannach, Oliver Müller

Paderborn University, Germany · University of Klagenfurt, Austria

Nudges Sustainability Recommendation Explainable AI Methods Choice

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Recommender systems mediate everyday consumption, offering a promising channel for encouraging sustainable choices. Prior research shows that explanations influence users' perceptions of recommendations and can support more informed decisions. We argue that explanations can also serve as behavioral nudges by foregrounding sustainability information at the moment of choice. This study investigates how different behavioral framings of sustainability information in recommendation explanations affect user choices and perceptions. Using generative AI, we generate sustainability-aware explanations by drawing on nudge theory and validate them through human evaluation and LLM-as-a-judge audits. Building on this foundation, we conduct two randomized studies (N = 529) in a low involvement domain (instant coffee) and a high involvement domain (hotel bookings), in which participants choose among preference matched recommendations accompanied by these explanations. Our results show that, across both domains, merely disclosing sustainability information in explanations does not change choices, whereas framing that information or invoking a descriptive social norm significantly increases sustainable selections and eases decision-making. Notably, perception and behavior diverge, as plain disclosure improves explanation evaluations without translating into more sustainable selection behavior. Our work demonstrates how LLMs can generate theory-grounded explanations at scale, pointing toward practical explanation-based interventions for social good. We conclude by discussing implications for adaptive explanation design with generative AI.

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