mlsanityData to 7 Oct 2026

Advancing NLP with Cognitive Language Processing Signals

arXiv 1904.02682 ↗First posted 4 Apr 2019cs.CLcited by 18

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Abstract (arXiv)

When we read, our brain processes language and generates cognitive processing data such as gaze patterns and brain activity. These signals can be recorded while reading. Cognitive language processing data such as eye-tracking features have shown improvements on single NLP tasks. We analyze whether using such human features can show consistent improvement across tasks and data sources. We present an extensive investigation of the benefits and limitations of using cognitive processing data for NLP. Specifically, we use gaze and EEG features to augment models of named entity recognition, relation classification, and sentiment analysis. These methods significantly outperform the baselines and show the potential and current limitations of employing human language processing data for NLP.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Apr 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 5; 2023: 4; 2024: 2; 2025: 1; 2026: 2.

18 papers.

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  1. 2022Reasoning with Language Model Prompting: A Surveycited by 251
  2. 2023Getting aligned on representational alignmentcited by 142
  3. 2021Multilingual Language Models Predict Human Reading Behaviorcited by 29
  4. 2023Synthesizing Human Gaze Feedback for Improved NLP Performancecited by 16
  5. 2021Decoding EEG Brain Activity for Multi-Modal Natural Language Processingcited by 13
  6. 2022Can Brain Signals Reveal Inner Alignment with Human Languages?cited by 12
  7. 2021CogAlign: Learning to Align Textual Neural Representations to Cognitive Language Processing Signalscited by 11
  8. 2024Seeing Eye to AI: Human Alignment via Gaze-Based Response Rewards for Large Language Modelscited by 11
  9. 2022Connecting Neural Response measurements & Computational Models of language: a non-comprehensive guidecited by 6
  10. 2023WebQAmGaze: A Multilingual Webcam Eye-Tracking-While-Reading Datasetcited by 6
  11. 2025OASST-ETC Dataset: Alignment Signals from Eye-tracking Analysis of LLM Responsescited by 3
  12. 2022A Comparative Study on Textual Saliency of Styles from Eye Tracking, Annotations, and Language Modelscited by 2
6 more
  1. 2024Teaching Human Behavior Improves Content Understanding Abilities Of LLMscited by 2
  2. 2026Utilizing Cognitive Signals Generated during Human Reading to Enhance Keyphrase Extraction from Microblogscited by 2
  3. 2021Leveraging recent advances in Pre-Trained Language Models forEye-Tracking Predictioncited by 0
  4. 2022Team 'UFAL at CMCL 2022 Shared Task: Figuring out the correct recipe for predicting Eye-Tracking features using Pretrained Language Modelscited by 0
  5. 2023Can humans help BERT gain "confidence"?cited by 0
  6. 2026Leveraging Human Reading Behavior for Keyphrase Extraction: A Webcam-based Eye-tracking Corpuscited by 0