Explainable Models

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 53 papers with code (128 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.

• TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron Provenance
  21 Dec 2023 2 repositories listed
  We introduce TraceFL, a fine-grained neuron provenance capturing mechanism that identifies clients responsible for a global model's prediction by tracking the flow of information from individual clients to the global…
• Discovery of Nonlinear Dynamical Systems using a Runge-Kutta Inspired Dictionary-based Sparse Regression Approach
  11 May 2021 2 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  Discovering dynamical models to describe underlying dynamical behavior is essential to draw decisive conclusions and engineering studies, e.
• BioX-CPath: Biologically-driven Explainable Diagnostics for Multistain IHC Computational Pathology
  26 Mar 2025 1 repository listed
  The development of biologically interpretable and explainable models remains a key challenge in computational pathology, particularly for multistain immunohistochemistry (IHC) analysis.
• ExDDV: A New Dataset for Explainable Deepfake Detection in Video
  18 Mar 2025 1 repository listed
  Our results show that text and click supervision are both required to develop robust explainable models for deepfake videos, which are able to localize and describe the observed artifacts.
• Prompt-CAM: A Simpler Interpretable Transformer for Fine-Grained Analysis
  16 Jan 2025 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  We present a simple usage of pre-trained Vision Transformers (ViTs) for fine-grained analysis, aiming to identify and localize the traits that distinguish visually similar categories, such as different bird species or…
• Constructing and explaining machine learning models for chemistry: example of the exploration and design of boron-based Lewis acids
  2 Jan 2025 1 repository listed
  The integration of machine learning (ML) into chemistry offers transformative potential in the design of molecules with targeted properties.
• Explainable fault and severity classification for rolling element bearings using Kolmogorov-Arnold networks
  2 Dec 2024 1 repository listed
  By training shallow network architectures and minimizing the number of selected features, the framework produces lightweight models that deliver explainable results through feature attribution and symbolic…
• Medical Slice Transformer: Improved Diagnosis and Explainability on 3D Medical Images with DINOv2
  24 Nov 2024 1 repository listed
  We introduce the Medical Slice Transformer (MST) framework to adapt 2D self-supervised models for 3D medical image analysis.
• Reproducibility study of "LICO: Explainable Models with Language-Image Consistency"
  17 Oct 2024 1 repository listed
  The growing reproducibility crisis in machine learning has brought forward a need for careful examination of research findings.
• CaBRNet, an open-source library for developing and evaluating Case-Based Reasoning Models
  25 Sep 2024 1 repository listed
  In the field of explainable AI, a vibrant effort is dedicated to the design of self-explainable models, as a more principled alternative to post-hoc methods that attempt to explain the decisions after a model opaquely…
• 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.
• HEARTS: A Holistic Framework for Explainable, Sustainable and Robust Text Stereotype Detection
  17 Sep 2024 1 repository listed
  Stereotypes are generalised assumptions about societal groups, and even state-of-the-art LLMs using in-context learning struggle to identify them accurately.
• Benchmarking the Attribution Quality of Vision Models
  16 Jul 2024 1 repository listed Syntology ran 5 of 14 samples · 9 unverified
  Attribution maps are one of the most established tools to explain the functioning of computer vision models.
• FreqRISE: Explaining time series using frequency masking
  19 Jun 2024 1 repository listed
  In this paper, we argue that the salient information of a number of time series is more likely to be localized in the frequency domain.
• ProtoS-ViT: Visual foundation models for sparse self-explainable classifications
  14 Jun 2024 1 repository listed Syntology ran 9 of 13 samples · 4 unverified
  Prototypical networks aim to build intrinsically explainable models based on the linear summation of concepts.
• Accurate Explanation Model for Image Classifiers using Class Association Embedding
  12 Jun 2024 1 repository listed
  Recombining the individual code of a given sample with altered class-associated code leads to a synthetic real-looking sample with preserved individual characters but modified class-associated features and possibly…
• Data Science Principles for Interpretable and Explainable AI
  17 May 2024 1 repository listed
  Society's capacity for algorithmic problem-solving has never been greater.
• Large Language Models for Cyber Security: A Systematic Literature Review
  8 May 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified
  Overall, our survey provides a comprehensive overview of the current state-of-the-art in LLM4Security and identifies several promising directions for future research.
• Prototype-based Interpretable Breast Cancer Prediction Models: Analysis and Challenges
  29 Mar 2024 1 repository listed
  Specifically, we apply three state-of-the-art prototype-based models, ProtoPNet, BRAIxProtoPNet++ and PIP-Net on mammography images for breast cancer prediction and evaluate these models w.
• Pantypes: Diverse Representatives for Self-Explainable Models
  14 Mar 2024 1 repository listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  Prototypical self-explainable classifiers have emerged to meet the growing demand for interpretable AI systems.
• Gaussian Process Neural Additive Models
  19 Feb 2024 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  Deep neural networks have revolutionized many fields, but their black-box nature also occasionally prevents their wider adoption in fields such as healthcare and finance, where interpretable and explainable models are…
• Prototypical Self-Explainable Models Without Re-training
  13 Dec 2023 1 repository listed
  Explainable AI (XAI) has unfolded in two distinct research directions with, on the one hand, post-hoc methods that explain the predictions of a pre-trained black-box model and, on the other hand, self-explainable models…
• Explaining black boxes with a SMILE: Statistical Model-agnostic Interpretability with Local Explanations
  13 Nov 2023 1 repository listed
  Machine learning is currently undergoing an explosion in capability, popularity, and sophistication.
• Prototype-based Interpretable Graph Neural Networks
  16 Nov 2022 1 repository listed
  We then evaluate the explanations of the interpretable models by comparing them with post-hoc approaches and self-explainable models.
• Towards Human-centered Explainable AI: A Survey of User Studies for Model Explanations
  20 Oct 2022 1 repository listed
  A better understanding of the needs of XAI users, as well as human-centered evaluations of explainable models are both a necessity and a challenge.
• Sim2Word: Explaining Similarity with Representative Attribute Words via Counterfactual Explanations
  8 Sep 2022 1 repository listed
  Different from existing models, in this paper, we propose a new interpretation method that explains the image similarity models by salience maps and attribute words.
• UKP-SQuARE v2: Explainability and Adversarial Attacks for Trustworthy QA
  19 Aug 2022 1 repository listed
  In this paper, we introduce SQuARE v2, the new version of SQuARE, to provide an explainability infrastructure for comparing models based on methods such as saliency maps and graph-based explanations.
• Smoothing Entailment Graphs with Language Models
  30 Jul 2022 1 repository listed
  The diversity and Zipfian frequency distribution of natural language predicates in corpora leads to sparsity in Entailment Graphs (EGs) built by Open Relation Extraction (ORE).
• dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification
  25 Jul 2022 1 repository listed
  Convolutional neural networks perform well for the data series classification task; though, the explanations provided by this type of algorithm are poor for the specific case of multivariate data series.
• Explaining Chest X-ray Pathologies in Natural Language
  9 Jul 2022 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Most deep learning algorithms lack explanations for their predictions, which limits their deployment in clinical practice.

Syntology lines on 8 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.