xAI-2024:LB/D/DC
xAI-2024 Late-breaking Work, Demos and Doctoral Consortium Joint Proceedings

Table of Contents

• Preface
  Luca Longo Weiru Liu Grégoire Montavon

Late-Breaking Work

• Explainable Artificial Intelligence Beyond Feature Attributions: The Validity and Reliability of Feature Selection Explanations 1-8
  Raphael Wallsberger , Ricardo Knauer , Stephan Matzka

• Shapley values and fairness 9-16
  Paolo Giudici , Parvati Neelakantan

• Perception and Consideration of the Explainees’ Needs for Satisfying Explanations 17-24
  Michael Erol Schaffer , Lutz Terfloth , Carsten Schulte , Heike M. Buhl

• A proposal for improving EEG microstate generation via interpretable deep clustering with convolutional autoencoders 25-32
  Arjun Vinayak Chikkankod , Luca Longo

• Faithful Attention Explainer: Verbalizing Decisions Based on Discriminative Features 33-40
  Yao Rong , David Scheerer , Enkelejda Kasneci

• Use Bag-of-Patterns Approach to Explore Learned Behaviors of Reinforcement Learning 41-48
  Gulsum Alicioglu , Bo Sun

• Generate Explanations for Time-series classification by ChatGPT 49-56
  Zhechang Xue , Yiran Huang , Hongnan Ma , Michael Beigl

• Model agnostic calibration of image classifiers 57-64
  Paolo Giudici , Giulia Vilone

• Interpreting Black-Box Time Series Classifiers using Parameterised Event Primitives 65-72
  Ephrem T. Mekonnen , Luca Longo , Pierpaolo Dondio

• Patch-based Intuitive Multimodal Prototypes Network (PIMPNet) for Alzheimer’s Disease classification 73-80
  Lisa Anita De Santi , Jörg Schlötterer , Meike Nauta , Vincenzo Positano , Christin Seifert

• AnyCBMs: How to Turn Any Black Box into a Concept Bottleneck Model 81-88
  Gabriele Dominici , Pietro Barbiero , Francesco Giannini , Martin Gjoreski , Marc Langeinrich

• Online Explainable Ensemble of Tree Models Pruning for Time Series Forecasting 89-96
  Amal Saadallah

• Towards Mechanistic Interpretability for Autoencoder compression of EEG signals 97-104
  Leon Hegedić , Luka Hobor , Nikola Marić , Martin Ante Rogošić , Mario Brcic

• Integrating XAI for Predictive Conflict Analytics 105-112
  Luca Macis , Marco Tagliapietra , Alessandro Castelnovo , Daniele Regoli , Greta Greco , Andrea Claudio Cosentini , Paola Pisano , Edoardo Carroccetto

• Interpretable Vital Sign Forecasting with Model Agnostic Attention Maps 113-120
  Yuwei Liu , Chen Dan , Anubhav Bhatti , Bingjie Shen , Divij Gupta , Suraj Parmar , San Lee ,

• Towards Assurance of LLM Adversarial Robustness using Ontology-Driven Argumentation 121-128
  Tomas Bueno Momcilovic , Beat Buesser , Giulio Zizzo , Mark Purcell , Dian Balta

• Looking for the Right Paths to Use XAI in the Judiciary. Which Branches of Law Need Inherently Interpretable Machine Learning Models and Why? 129-136
  Andrzej Porębski

• The Dynamics of Explainability: Diverse Insights from SHAP Explanations using Neighbourhoods 137-144
  Urja Pawar , Ruairi O’Reilly , Christian Beder , Donna O’Shea

• Enhancing the analysis of the P300 event-related potential with integrated gradients on a convolutional neural network trained with superlets 145-152
  Vladimir Marochko , Luca Longo ,

• Exploring Commonalities in Explanation Frameworks: A Multi-Domain Survey Analysis 153-160
  Eduard Barbu , Marharytha Domnich , Raul Vicente , Nikos Sakkas

• Investigating Neuron Ablation in Attention Heads: The Case for Peak Activation Centering 161-168
  Nicholas Pochinkov , Ben Pasero , Skylar Shibayama

• CatBoost model with self-explanatory capabilities for predicting SLE in OMAN population 169-176
  Hamza Zidoum , Ali AlShareedah , Aliya Al-Ansari , Batool Al Lawati , Al-Sawafi

• Channel Modeling for Millimeter-Wave UAV Communication based on Explainable Generative Neural Network 177-184
  Ladan Gholami , Pietro Ducange , Pietro Cassará , Alberto Gotta

• Validation of ML Models from the Field of XAI for Computer Vision in Autonomous Driving 185-192
  Antonio Mastroianni , Sibylle D. Sager-Müller

• Second Glance: A Novel Explainable AI to Understand Feature Interactions in Neural Networks using Higher-Order Partial Derivatives 193-200
  Zohaib Shahid , Yogachandran Rahulamathavan , Safak Dogan

• Mediating Explainer for Human Autonomy Teaming 201-208
  Siri Padmanabhan Poti , Christopher J. Stanton

• Exploring Agent Behaviors in Network Security through Trajectory Clustering 209-216
  Ondrej Lukas , Sebastian Garcia

• A geometric XAI approach to protein pocket detection 217-224
  Giovanni Bocchi , Patrizio Frosini , Alessandra Micheletti , Alessandro Pedretti , Gianluca Palermo , Davide Gadioli , Carmen Gratteri , Filippo Lunghini , Andrea Rosario Beccari , Anna Fava , Carmine Talarico

• An Empirical Investigation of Users’ Assessment of XAI Explanations: Identifying the Sweet Spot of Explanation Complexity and Value 225-232
  Felix Liedeker , Christoph Düsing , Marcel Nieveler , Philipp Cimiano

• A Two-Stage Algorithm for Cost-Efficient Multi-instance Counterfactual Explanations 233-240
  André Artelt , Andreas Gregoriades

• Interactive xAI-dashboard for Semantic Segmentation 241-248
  Finn Schürmann , Sibylle D. Sager-Müller

• XAI for Group-AI Interaction: Towards Collaborative and Inclusive Explanations 249-256
  Mohammad Naiseh , Catherine Webb , Tim Underwood , Gopal Ramchurn , Zoe Walters Navamayooran Thavanesan , Ganesh Vigneswaran

• Unraveling Anomalies: Explaining Outliers with DTOR 257-264
  Riccardo Crupi , Daniele Regoli , Alessandro Damiano Sabatino , Immacolata Marano , Massimiliano Brinis , Luca Albertazzi , Andrea Cirillo , Andrea Claudio Cosentini

Demos

• CaBRNet, An Open-Source Library For Developing And Evaluating Case-Based Reasoning Models 265-272
  Romain Xu-Darme , Aymeric Varasse , Alban Grastien , Julien Girard-Satabin , Zakaria Chihani

• XAgent: A Conversational XAI Agent Harnessing the Power of Large Language Models 273-280
  Van Bach Nguyen , Jörg Schlötterer , Christin Seifert

• mlr3summary: Concise and interpretable summaries for machine learning models 281-288
  Susanne Dandl , Marc Becker , Bernd Bischl , Giuseppe Casalicchio , Ludwig Bothmann ,

• Democratizing Advanced Attribution Analyses of Generative Language Models with the Inseq Toolkit 289-296
  Gabriele Sarti , Nils Feldhus , Jirui Qi , Malvina Nissim , Arianna Bisazza

• Human-in-the-loop testing of the explainability of robot navigation algorithms in extended reality 297-304
  Jérôme Guzzi , Alessandro Giusti

• Rulex Platform: leveraging domain knowledge and data-driven rules to support decisions in the fintech sector through eXplainable AI models 305-312
  Claudio Muselli , Damiano Verda , Enrico Ferrari , Claire Thomas Gaggiotti , Marco Muselli

• Building Personalised XAI Experiences Through iSee: a Case-Based Reasoning-Driven Platform 313-320
  Marta Caro-Martínez , Anne Liret , Belén Díaz-Agudo , Juan A. Recio-García , Jesús Darias , Nirmalie Wiratunga , Anjana Wijekoon , Kyle Martin , Ikechukwu Nkisi-Orji , David Corsar , Chamath Palihawadana , Craig Pirie , Derek Bridge , Preeja Pradeep , Bruno Fleisch

Doctoral Consortium

• Fostering Human-AI interaction: development of a Clinical Decision Support System enhanced by eXplainable AI and Natural Language Processing 321-328
  Laura Bergomi

• Optimizing Synthetic Data from Scarcity: Towards Meaningful Data Generation in High-Dimensional Low-Sample Size Domains 329-336
  Danilo Danese

• Assesing the Interpretability of the Statistical Radiomic Features via Image Saliency Maps in Medical Image Classification Tasks 337-344
  Oleksandr Davydko

• Explainable AI as a Crucial Factor for Improving Human-AI Decision-Making Processes 345-352
  Regina de Brito Duarte

• Counterfactual generating Variational Autoencoder for Anomaly Detection 353-360
  Renate Ernst

• Privacy Implications of Explainable AI in Data-Driven Systems 361-368
  Fatima Ezzeddine

• XAI-driven Model Improvements in Interpretable Image Segmentation 369-376
  Rokas Gipiškis

• Design Guidelines for XAI in the Healthcare Domain 377-384
  Iris Heerlien

• Explainable MLOps: A Methodological Framework for the Development of Explainable AI in Practice 385-392
  Annemarie Jutte

• A Novel Model-Agnostic xAI Method Guided by Cost-Sensitive Tree Models and Argumentative Decision Graphs 393-400
  Marija Kopanja

• Explainable Artificial Intelligence and Reasoning in the Context of Large Neural Network Models 401-408
  Stefanie Krause

• Artificial Representative Trees as Interpretable Surrogates for Random Forests 409-416
  Lea Louisa Kronziel

• Can Reduction of Bias Decrease the Need for Explainability? Working with Simplified Models to Understand Complexity 417-424
  Pedro M. Marques

• Towards XAI for Optimal Transport 425-432
  Philip Naumann

• Knowledge Graphs and Explanations for Improving Detection of Diseases in Images of Grains 433-440
  Lenka Tětková

• Topological Data Analysis for Trustworthy AI 441-448
  Victor Toscano Durán

• Explainable Deep Reinforcement Learning through Introspective Explanations 449-456
  Nils Wenninghoff

• Explainable and Debiased Misogyny Identification In Code-Mixed Hinglish using Artificial Intelligence Models 457-464
  Sargam Yadav