mlsanityData to 7 Oct 2026

Extraction of Salient Sentences from Labelled Documents

arXiv 1412.6815 ↗First posted 21 Dec 2014cs.CL cs.IR cs.LGcited by 50

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Abstract (arXiv)

We present a hierarchical convolutional document model with an architecture designed to support introspection of the document structure. Using this model, we show how to use visualisation techniques from the computer vision literature to identify and extract topic-relevant sentences. We also introduce a new scalable evaluation technique for automatic sentence extraction systems that avoids the need for time consuming human annotation of validation data.

Key facts. Cited by 50 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Dec 2014.

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Citing papers per year: 2021: 7; 2022: 13; 2023: 11; 2024: 9; 2025: 7; 2026: 3.

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  1. 2023Dissecting Recall of Factual Associations in Auto-Regressive Language Modelscited by 512
  2. 2022Towards Faithful Model Explanation in NLP: A Surveycited by 129
  3. 2022XAI for Transformers: Better Explanations through Conservative Propagationcited by 100
  4. 2022Interpreting Language Models with Contrastive Explanationscited by 91
  5. 2024A Primer on the Inner Workings of Transformer-based Language Modelscited by 83
  6. 2021"Will You Find These Shortcuts?" A Protocol for Evaluating the Faithfulness of Input Salience Methods for Text Classificationcited by 66
  7. 2022Measuring the Mixing of Contextual Information in the Transformercited by 63
  8. 2023Large Language Models are Visual Reasoning Coordinatorscited by 58
  9. 2022PINTO: Faithful Language Reasoning Using Prompt-Generated Rationalescited by 56
  10. 2023Explaining How Transformers Use Context to Build Predictionscited by 42
  11. 2021Evaluating Saliency Methods for Neural Language Modelscited by 37
  12. 2021UNIREX: A Unified Learning Framework for Language Model Rationale Extractioncited by 32
38 more
  1. 2021Rationales for Sequential Predictionscited by 26
  2. 2023Tailoring Self-Rationalizers with Multi-Reward Distillationcited by 21
  3. 2022Learning to Scaffold: Optimizing Model Explanations for Teachingcited by 20
  4. 2021Interpreting Deep Learning Models in Natural Language Processing: A Reviewcited by 19
  5. 2023Do Large Language Models Pay Similar Attention Like Human Programmers When Generating Code?cited by 13
  6. 2024Latent Concept-based Explanation of NLP Modelscited by 13
  7. 2025Training a Utility-based Retriever Through Shared Context Attribution for Retrieval-Augmented Language Modelscited by 13
  8. 2024ReAGent: A Model-agnostic Feature Attribution Method for Generative Language Modelscited by 12
  9. 2024Attention Meets Post-hoc Interpretability: A Mathematical Perspectivecited by 11
  10. 2022FRAME: Evaluating Rationale-Label Consistency Metrics for Free-Text Rationalescited by 10
  11. 2025A Close Look at Decomposition-based XAI-Methods for Transformer Language Modelscited by 10
  12. 2024Detecting Hallucination and Coverage Errors in Retrieval Augmented Generation for Controversial Topicscited by 9
  13. 2022GPT-D: Inducing Dementia-related Linguistic Anomalies by Deliberate Degradation of Artificial Neural Language Modelscited by 8
  14. 2023Evaluating Neuron Interpretation Methods of NLP Modelscited by 8
  15. 2021SalKG: Learning From Knowledge Graph Explanations for Commonsense Reasoningcited by 7
  16. 2022ER-Test: Evaluating Explanation Regularization Methods for Language Modelscited by 6
  17. 2024Interactive Prompt Debugging with Sequence Saliencecited by 6
  18. 2024Unveiling and Manipulating Prompt Influence in Large Language Modelscited by 6
  19. 2022ReX: A Framework for Incorporating Temporal Information in Model-Agnostic Local Explanation Techniquescited by 5
  20. 2022Controlling the Focus of Pretrained Language Generation Modelscited by 4
  21. 2023Using Logic Programming and Kernel-Grouping for Improving Interpretability of Convolutional Neural Networkscited by 4
  22. 2023REFER: An End-to-end Rationale Extraction Framework for Explanation Regularizationcited by 4
  23. 2025Explanations of Large Language Models Explain Language Representations in the Braincited by 4
  24. 2025Noiser: Bounded Input Perturbations for Attributing Large Language Modelscited by 4
  25. 2021On the Post-hoc Explainability of Deep Echo State Networks for Time Series Forecasting, Image and Video Classificationcited by 3
  26. 2023A Novel Counterfactual Data Augmentation Method for Aspect-Based Sentiment Analysiscited by 3
  27. 2024Counterfactuals As a Means for Evaluating Faithfulness of Attribution Methods in Autoregressive Language Modelscited by 3
  28. 2022Understanding Text Classification Data and Models Using Aggregated Input Saliencecited by 2
  29. 2023NeSyFOLD: Neurosymbolic Framework for Interpretable Image Classificationcited by 2
  30. 2024Can Input Attributions Explain Inductive Reasoning in In-Context Learning?cited by 2
  31. 2023Evaluating Explanation Methods for Vision-and-Language Navigationcited by 1
  32. 2025DePass: Unified Feature Attributing by Simple Decomposed Forward Passcited by 1
  33. 2026Contrastive Attribution in the Wild: An Interpretability Analysis of LLM Failures on Realistic Benchmarkscited by 1
  34. 2022Easy to Decide, Hard to Agree: Reducing Disagreements Between Saliency Methodscited by 0
  35. 2025Global explainability of a deep abstaining classifiercited by 0
  36. 2025NLP4Neuro: Sequence-to-sequence learning for neural population decodingcited by 0
  37. 2026Evaluating Explainable AI Attribution Methods in Neural Machine Translation via Attention-Guided Knowledge Distillationcited by 0
  38. 2026Layer-wise Target Propagation: Efficient Component Attribution through Target Centric Propagationcited by 0