Counterfactual Explanation

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

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Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

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Most implemented papers archive 2025-07-28

30 shown of 86 papers with code (177 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual Explanation Algorithms
  2 Aug 2021 4 repositories listed Syntology ran 0 of 8 samples · 8 unverified
  In summary, our work provides the following contributions: (i) an extensive benchmark of 11 popular counterfactual explanation methods, (ii) a benchmarking framework for research on future counterfactual explanation…
• Explaining Groups of Points in Low-Dimensional Representations
  3 Mar 2020 3 repositories listed
  A common workflow in data exploration is to learn a low-dimensional representation of the data, identify groups of points in that representation, and examine the differences between the groups to determine what they…
• Counterfactual Explanation Algorithms for Behavioral and Textual Data
  4 Dec 2019 3 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  This study aligns the recently proposed Linear Interpretable Model-agnostic Explainer (LIME) and Shapley Additive Explanations (SHAP) with the notion of counterfactual explanations, and empirically benchmarks their…
• VCNet: A self-explaining model for realistic counterfactual generation
  21 Dec 2022 2 repositories listed Syntology ran 0 of 10 samples · 10 unverified
  Our contribution is the generation of counterfactuals that are close to the distribution of the predicted class.
• OmniXAI: A Library for Explainable AI
  1 Jun 2022 2 repositories listed
  We introduce OmniXAI (short for Omni eXplainable AI), an open-source Python library of eXplainable AI (XAI), which offers omni-way explainable AI capabilities and various interpretable machine learning techniques to…
• On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations
  22 Jan 2022 2 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 3 pointer-only (licence)
  Since CEs typically prescribe a sparse form of intervention (i.
• STEEX: Steering Counterfactual Explanations with Semantics
  17 Nov 2021 2 repositories listed
  In this work, we address the problem of producing counterfactual explanations for high-quality images and complex scenes.
• Counterfactual Shapley Additive Explanations
  27 Oct 2021 2 repositories listed Syntology ran 0 of 13 samples · 13 unverified
  Feature attributions are a common paradigm for model explanations due to their simplicity in assigning a single numeric score for each input feature to a model.
• Counterfactual Explainable Recommendation
  24 Aug 2021 2 repositories listed
  Technically, for each item recommended to each user, CountER formulates a joint optimization problem to generate minimal changes on the item aspects so as to create a counterfactual item, such that the recommendation…
• Graph Style Transfer for Counterfactual Explainability
  23 May 2025 1 repository listed
  Counterfactual explainability seeks to uncover model decisions by identifying minimal changes to the input that alter the predicted outcome.
• COMRECGC: Global Graph Counterfactual Explainer through Common Recourse
  11 May 2025 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  A common recourse explanation is a small set of recourse, from which every ''reject'' graph can be turned into an ''accept'' graph.
• Latent Diffusion Autoencoders: Toward Efficient and Meaningful Unsupervised Representation Learning in Medical Imaging
  11 Apr 2025 1 repository listed
  This study presents Latent Diffusion Autoencoder (LDAE), a novel encoder-decoder diffusion-based framework for efficient and meaningful unsupervised learning in medical imaging, focusing on Alzheimer disease (AD) using…
• Generalized Semantic Contrastive Learning via Embedding Side Information for Few-Shot Object Detection
  9 Apr 2025 1 repository listed
  The core challenge of this task is how to construct a generalized feature space for novel categories with limited data on the basis of the base category space, which could adapt the learned detection model to unknown…
• Multi-SpaCE: Multi-Objective Subsequence-based Sparse Counterfactual Explanations for Multivariate Time Series Classification
  14 Dec 2024 1 repository listed
  Deep Learning systems excel in complex tasks but often lack transparency, limiting their use in critical applications.
• Derivative-Free Diffusion Manifold-Constrained Gradient for Unified XAI
  22 Nov 2024 1 repository listed Syntology ran 0 of 10 samples · 10 unverified
  Gradient-based methods are a prototypical family of explainability techniques, especially for image-based models.
• M-CELS: Counterfactual Explanation for Multivariate Time Series Data Guided by Learned Saliency Maps
  4 Nov 2024 1 repository listed
  Machine learning (ML) models for multivariate time series classification have made significant strides and achieved impressive success in a wide range of applications and tasks.
• Towards Unifying Evaluation of Counterfactual Explanations: Leveraging Large Language Models for Human-Centric Assessments
  28 Oct 2024 1 repository listed
  As machine learning models evolve, maintaining transparency demands more human-centric explainable AI techniques.
• Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective for Molecular Property Prediction
  19 Oct 2024 1 repository listed
  In recent years, Graph Neural Networks (GNNs) have become successful in molecular property prediction tasks such as toxicity analysis.
• The Gaussian Discriminant Variational Autoencoder (GdVAE): A Self-Explainable Model with Counterfactual Explanations
  19 Sep 2024 1 repository listed
  Visual counterfactual explanation (CF) methods modify image concepts, e.
• Global Human-guided Counterfactual Explanations for Molecular Properties via Reinforcement Learning
  19 Jun 2024 1 repository listed
  RLHEX provides a flexible framework to incorporate different human-designed principles into the counterfactual explanation generation process, aligning these explanations with domain expertise.
• Graph Neural Networks for Vulnerability Detection: A Counterfactual Explanation
  24 Apr 2024 1 repository listed
  We argue that these factual reasoning-based explanations cannot answer critical what-if questions: What would happen to the GNN's decision if we were to alter the code graph into alternative structures?
• Does It Make Sense to Explain a Black Box With Another Black Box?
  23 Apr 2024 1 repository listed
  Most methods find those explanations by iteratively perturbing the target document until it is classified differently by the black box.
• Model-Based Counterfactual Explanations Incorporating Feature Space Attributes for Tabular Data
  20 Apr 2024 1 repository listed
  Machine-learning models, which are known to accurately predict patterns from large datasets, are crucial in decision making.
• COIN: Counterfactual inpainting for weakly supervised semantic segmentation for medical images
  19 Apr 2024 1 repository listed
  This evidence suggests that COIN is a promising approach for semantic segmentation of tumors in CT images, and presents a step forward in making deep learning applications more accessible and effective in healthcare,…
• Counterfactual Analysis of Neural Networks Used to Create Fertilizer Management Zones
  15 Mar 2024 1 repository listed
  In response to this gap, we present a MZ clustering method based on fertilizer responsivity.
• Fast Inference of Removal-Based Node Influence
  13 Mar 2024 1 repository listed
  We propose a new method of evaluating node influence, which measures the prediction change of a trained GNN model caused by removing a node.
• Introducing User Feedback-based Counterfactual Explanations (UFCE)
  26 Feb 2024 1 repository listed
  However, current CE algorithms usually operate within the entire feature space when optimizing changes to turn over an undesired outcome, overlooking the identification of key contributors to the outcome and…
• Generating Survival Interpretable Trajectories and Data
  19 Feb 2024 1 repository listed
  A new model for generating survival trajectories and data based on applying an autoencoder of a specific structure is proposed.
• Generating Likely Counterfactuals Using Sum-Product Networks
  25 Jan 2024 1 repository listed
  To achieve that, we propose an MIO formulation of an SPN, which can be of independent interest.
• Distributional Counterfactual Explanations With Optimal Transport
  23 Jan 2024 1 repository listed
  Counterfactual explanations (CE) are the de facto method for providing insights into black-box decision-making models by identifying alternative inputs that lead to different outcomes.

Syntology lines on 7 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.