mlsanityData to 7 Oct 2026

Interpretability of Machine Learning: Recent Advances and Future Prospects

arXiv 2305.00537 ↗First posted 30 Apr 2023cs.MM cs.CY cs.LGcited by 12

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Abstract (arXiv)

The proliferation of machine learning (ML) has drawn unprecedented interest in the study of various multimedia contents such as text, image, audio and video, among others. Consequently, understanding and learning ML-based representations have taken center stage in knowledge discovery in intelligent multimedia research and applications. Nevertheless, the black-box nature of contemporary ML, especially in deep neural networks (DNNs), has posed a primary challenge for ML-based representation learning. To address this black-box problem, the studies on interpretability of ML have attracted tremendous interests in recent years. This paper presents a survey on recent advances and future prospects on interpretability of ML, with several application examples pertinent to multimedia computing, including text-image cross-modal representation learning, face recognition, and the recognition of objects. It is evidently shown that the study of interpretability of ML promises an important research direction, one which is worth further investment in.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 42 of its 103 references that are in the map. First posted on arXiv 30 Apr 2023.

Builds on

42 of 103 references.

References · 42

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30 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 2; 2024: 3; 2025: 5; 2026: 2.

12 papers.

  1. 2024Towards Guaranteed Safe AI: A Framework for Ensuring Robust and Reliable AI Systemscited by 94
  2. 2023Learning Concept-Based Causal Transition and Symbolic Reasoning for Visual Planningcited by 2
  3. 2025Building Trustworthy AI for Materials Discovery: From Autonomous Laboratories to Z-scorescited by 2
  4. 2026Interpreting Agentic Systems: Beyond Model Explanations to System-Level Accountabilitycited by 2
  5. 2023FACADE: A Framework for Adversarial Circuit Anomaly Detection and Evaluationcited by 1
  6. 2024Moments of Clarity: Streamlining Latent Spaces in Machine Learning using Moment Poolingcited by 0
  7. 2024Enhancing Diagnostic Reliability of Foundation Model with Uncertainty Estimation in OCT Imagescited by 0
  8. 2025Visualizing Machine Learning Models for Enhanced Financial Decision-Making and Risk Managementcited by 0
  9. 2025Fuzzy Rule-based Differentiable Representation Learningcited by 0
  10. 2025Detecting underdetermination in parameterized quantum circuitscited by 0
  11. 2025AI-ming backwards: Vanishing archaeological landscapes in Mesopotamia and automatic detection of sites on CORONA imagerycited by 0
  12. 2026KEMP-PIP: A Feature-Fusion Based Approach for Pro-inflammatory Peptide Predictioncited by 0