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Towards Unifying Evaluation of Counterfactual Explanations: Leveraging Large Language Models for Human-Centric Assessments

AAAI Conference on Artificial Intelligence (AAAI), 2024

28 October 2024

Raul Vicente

Papers citing "Towards Unifying Evaluation of Counterfactual Explanations: Leveraging Large Language Models for Human-Centric Assessments"

27 / 27 papers shown

Title
Through a Compressed Lens: Investigating The Impact of Quantization on Factual Knowledge Recall Qianli Wang Mingyang Wang Nils Feldhus Simon Ostermann Yuan Cao Hinrich Schütze Sebastian Möller Vera Schmitt MQ 220 2 0 20 May 2025
Truth or Twist? Optimal Model Selection for Reliable Label Flipping Evaluation in LLM-based Counterfactuals Qianli Wang Van Bach Nguyen Nils Feldhus Luis Felipe Villa-Arenas Christin Seifert Sebastian Möller Vera Schmitt 365 2 0 20 May 2025
Predicting Satisfaction of Counterfactual Explanations from Human Ratings of Explanatory Qualities M. Domnich Rasmus Moorits Veski Julius Valja Kadi Tulver Raul Vicente FAtt 254 0 0 07 Apr 2025
FitCF: A Framework for Automatic Feature Importance-guided Counterfactual Example GenerationAnnual Meeting of the Association for Computational Linguistics (ACL), 2025 Qianli Wang Nils Feldhus Simon Ostermann Luis Felipe Villa-Arenas Sebastian Möller Vera Schmitt AAML 462 4 0 01 Jan 2025
Lusifer: LLM-based User SImulated Feedback Environment for online Recommender systems Danial Ebrat Luis Rueda Luis Rueda 272 6 0 22 May 2024
Aligning LLM Agents by Learning Latent Preference from User Edits Ge Gao Alexey Taymanov Eduardo Salinas Paul Mineiro Dipendra Kumar Misra LLMAG 275 47 0 23 Apr 2024
Enhancing Counterfactual Explanation Search with Diffusion Distance and Directional Coherence M. Domnich Raul Vicente 187 4 0 19 Apr 2024
CountARFactuals -- Generating plausible model-agnostic counterfactual explanations with adversarial random forests Susanne Dandl Kristin Blesch Timo Freiesleben Gunnar Konig Jan Kapar J. Herbinger Marvin N. Wright AAML 277 6 0 04 Apr 2024
Explainable Artificial Intelligence (XAI) 2.0: A Manifesto of Open Challenges and Interdisciplinary Research DirectionsInformation Fusion (Inf. Fusion), 2023 Luca Longo Mario Brcic Federico Cabitza Jaesik Choi Roberto Confalonieri ... Andrés Páez Wojciech Samek Johannes Schneider Timo Speith Simone Stumpf 458 356 0 30 Oct 2023
Towards LLM-guided Causal Explainability for Black-box Text Classifiers Amrita Bhattacharjee Raha Moraffah Joshua Garland Huan Liu 267 48 0 23 Sep 2023
A Survey on Large Language Model based Autonomous Agents Lei Wang Chengbang Ma Xueyang Feng Zeyu Zhang Hao-ran Yang ... Xu Chen Yankai Lin Wayne Xin Zhao Zhewei Wei Ji-Rong Wen LLMAG AI4CE LM&Ro 650 2,043 0 22 Aug 2023
Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment Yang Liu Yuanshun Yao Jean-François Ton Xiaoying Zhang Ruocheng Guo Hao Cheng Yegor Klochkov Muhammad Faaiz Taufiq Hanguang Li ALM 350 457 0 10 Aug 2023
For Better or Worse: The Impact of Counterfactual Explanations' Directionality on User Behavior in xAI Ulrike Kuhl André Artelt Barbara Hammer 202 5 0 13 Jun 2023
QLoRA: Efficient Finetuning of Quantized LLMsNeural Information Processing Systems (NeurIPS), 2023 Tim Dettmers Artidoro Pagnoni Ari Holtzman Luke Zettlemoyer ALM 551 3,612 0 23 May 2023
TalkToModel: Explaining Machine Learning Models with Interactive Natural Language ConversationsNature Machine Intelligence (Nat. Mach. Intell.), 2022 Dylan Slack Satyapriya Krishna Himabindu Lakkaraju Sameer Singh 293 110 0 08 Jul 2022
Features of Explainability: How users understand counterfactual and causal explanations for categorical and continuous features in XAI Greta Warren Mark T. Keane R. Byrne CML 145 27 0 21 Apr 2022
DNSMOS P.835: A Non-Intrusive Perceptual Objective Speech Quality Metric to Evaluate Noise Suppressors Chandan K. A. Reddy Vishak Gopal Ross Cutler 440 325 0 05 Oct 2021
CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models Arjun Reddy Akula Keze Wang Changsong Liu Sari Saba-Sadiya Hongjing Lu S. Todorovic J. Chai Song-Chun Zhu 199 56 0 03 Sep 2021
CARE: Coherent Actionable Recourse based on Sound Counterfactual Explanations P. Rasouli Ingrid Chieh Yu 113 32 0 18 Aug 2021
Understanding Consumer Preferences for Explanations Generated by XAI Algorithms Yanou Ramon T. Vermeire Olivier Toubia David Martens Theodoros Evgeniou 137 12 0 06 Jul 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI TechniquesInternational Joint Conference on Artificial Intelligence (IJCAI), 2021 Mark T. Keane Eoin M. Kenny Eoin Delaney Barry Smyth CML 278 165 0 26 Feb 2021
PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender SystemsWeb Search and Data Mining (WSDM), 2019 Azin Ghazimatin Oana Balalau Rishiraj Saha Roy Gerhard Weikum FAtt 398 107 0 19 Nov 2019
Explanation in Human-AI Systems: A Literature Meta-Review, Synopsis of Key Ideas and Publications, and Bibliography for Explainable AI Shane T. Mueller R. Hoffman W. Clancey Abigail Emrey Gary Klein XAI 233 305 0 05 Feb 2019
Metrics for Explainable AI: Challenges and Prospects R. Hoffman Shane T. Mueller Gary Klein Jordan Litman XAI 292 821 0 11 Dec 2018
A review of possible effects of cognitive biases on the interpretation of rule-based machine learning models Tomáš Kliegr Š. Bahník Johannes Furnkranz 254 116 0 09 Apr 2018
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 861 2,709 0 01 Nov 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 725 4,783 0 22 Jun 2017