mlsanityData to 14 Oct 2026

Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification

arXiv 2112.02690 ↗First posted 5 Dec 2021cs.AIcited by 67

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Abstract (arXiv)

State-of-the-art brain-to-text systems have achieved great success in decoding language directly from brain signals using neural networks. However, current approaches are limited to small closed vocabularies which are far from enough for natural communication. In addition, most of the high-performing approaches require data from invasive devices (e.g., ECoG). In this paper, we extend the problem to open vocabulary Electroencephalography(EEG)-To-Text Sequence-To-Sequence decoding and zero-shot sentence sentiment classification on natural reading tasks. We hypothesis that the human brain functions as a special text encoder and propose a novel framework leveraging pre-trained language models (e.g., BART). Our model achieves a 40.1% BLEU-1 score on EEG-To-Text decoding and a 55.6% F1 score on zero-shot EEG-based ternary sentiment classification, which significantly outperforms supervised baselines. Furthermore, we show that our proposed model can handle data from various subjects and sources, showing great potential for a high-performance open vocabulary brain-to-text system once sufficient data is available

Key facts. Cited by 67 papers in the map (data through 14 Oct 2026). Builds on 16 of its 53 references that are in the map. First posted on arXiv 5 Dec 2021.

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16 of 53 references.

References · 16

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  3. 2020Language Models are Few-Shot Learnerscited by 32,419
  4. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  5. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
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  10. 2019ZuCo 2.0: A Dataset of Physiological Recordings During Natural Reading and Annotationcited by 66
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  12. 2019CogniVal: A Framework for Cognitive Word Embedding Evaluationcited by 27
4 more
  1. 2021Decoding EEG Brain Activity for Multi-Modal Natural Language Processingcited by 13
  2. 2018Does the brain represent words? An evaluation of brain decoding studies of language understandingcited by 9
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 10; 2024: 23; 2025: 21; 2026: 12.

67 papers.

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  1. 2024Large Language Models for Time Series: A Surveycited by 114
  2. 2024Are EEG-to-Text Models Working?cited by 32
  3. 2023Understanding Emergent In-Context Learning from a Kernel Regression Perspectivecited by 24
  4. 2025Multi-modal Time Series Analysis: A Tutorial and Surveycited by 24
  5. 2023UniCoRN: Unified Cognitive Signal ReconstructioN bridging cognitive signals and human languagecited by 22
  6. 2023Through their eyes: multi-subject Brain Decoding with simple alignment techniquescited by 21
  7. 2024The Brain's Bitter Lesson: Scaling Speech Decoding With Self-Supervised Learningcited by 21
  8. 2024EEG2TEXT: Open Vocabulary EEG-to-Text Decoding with EEG Pre-Training and Multi-View Transformercited by 20
  9. 2024Large Language Models Meet Text-Centric Multimodal Sentiment Analysis: A Surveycited by 16
  10. 2024Enhancing EEG-to-Text Decoding through Transferable Representations from Pre-trained Contrastive EEG-Text Masked Autoencodercited by 15
  11. 2024MAD: Multi-Alignment MEG-to-Text Decodingcited by 15
  12. 2025Unlocking Non-Invasive Brain-to-Textcited by 15
38 more
  1. 2022Can Brain Signals Reveal Inner Alignment with Human Languages?cited by 12
  2. 2024BTS: Bridging Text and Sound Modalities for Metadata-Aided Respiratory Sound Classificationcited by 12
  3. 2024NeuSpeech: Decode Neural signal as Speechcited by 11
  4. 2023Large Transformers are Better EEG Learnerscited by 10
  5. 2024Unveiling Thoughts: A Review of Advancements in EEG Brain Signal Decoding into Textcited by 10
  6. 2024BELT-2: Bootstrapping EEG-to-Language representation alignment for multi-task brain decodingcited by 10
  7. 2023Deep Representation Learning for Open Vocabulary Electroencephalography-to-Text Decodingcited by 9
  8. 2024Open-vocabulary Auditory Neural Decoding Using fMRI-prompted LLMcited by 9
  9. 2024NeuGPT: Unified multi-modal Neural GPTcited by 7
  10. 2024SEE: Semantically Aligned EEG-to-Text Translationcited by 6
  11. 2025Enhancing Listened Speech Decoding from EEG via Parallel Phoneme Sequence Predictioncited by 6
  12. 2025WaveMind: Towards a Conversational EEG Foundation Model Aligned to Textual and Visual Modalitiescited by 6
  13. 2023Semantic-aware Contrastive Learning for Electroencephalography-to-Text Generation with Curriculum Learningcited by 5
  14. 2023BELT:Bootstrapping Electroencephalography-to-Language Decoding and Zero-Shot Sentiment Classification by Natural Language Supervisioncited by 5
  15. 2025Learning Interpretable Representations Leads to Semantically Faithful EEG-to-Text Generationcited by 5
  16. 2025Embracing Trustworthy Brain-Agent Collaboration as Paradigm Extension for Intelligent Assistive Technologiescited by 5
  17. 2026HyFI: Hyperbolic Feature Interpolation for Brain-Vision Alignmentcited by 5
  18. 2024Towards Linguistic Neural Representation Learning and Sentence Retrieval from Electroencephalogram Recordingscited by 4
  19. 2024BrainECHO: Semantic Brain Signal Decoding through Vector-Quantized Spectrogram Reconstruction for Whisper-Enhanced Text Generationcited by 4
  20. 2025Neural Spelling: A Spell-Based BCI System for Language Neural Decodingcited by 4
  21. 2025Pretraining Large Brain Language Model for Active BCI: Silent Speechcited by 4
  22. 2025EEG2TEXT-CN: An Exploratory Study of Open-Vocabulary Chinese Text-EEG Alignment via Large Language Model and Contrastive Learning on ChineseEEGcited by 4
  23. 2025Foundation Models for Cross-Domain EEG Analysis Application: A Surveycited by 4
  24. 2026Neural Signals Generate Clinical Notes in the Wildcited by 4
  25. 2023Rethinking Cross-Subject Data Splitting for Brain-to-Text Decodingcited by 3
  26. 2024AI for Biomedicine in the Era of Large Language Modelscited by 3
  27. 2024A Survey of Spatio-Temporal EEG data Analysis: from Models to Applicationscited by 3
  28. 2025On Creating A Brain-To-Text Decodercited by 3
  29. 2025A Survey on Bridging EEG Signals and Generative AI: From Image and Text to Beyondcited by 3
  30. 2025Bridging Brain Signals and Language: A Deep Learning Approach to EEG-to-Text Decodingcited by 3
  31. 2025Large Language models for Time Series Analysis: Techniques, Applications, and Challengescited by 3
  32. 2025ETS: Open Vocabulary Electroencephalography-To-Text Decoding and Sentiment Classificationcited by 3
  33. 2026What Are We Actually Decoding? Source Attribution for Non-Invasive Brain-to-Language Retrievalcited by 3
  34. 2026BrainAgent: A Large Language Model-Driven Multi-Agent Framework for Autonomous Brain Signal Understandingcited by 3
  35. 2023Do self-supervised speech and language models extract similar representations as human brain?cited by 2
  36. 2024Non-invasive Neural Decoding in Source Reconstructed Brain Spacecited by 2
  37. 2024Query Augmentation by Decoding Semantics from Brain Signalscited by 1
  38. 2024Decoding Linguistic Representations of Human Braincited by 1

50 most cited of 67 All 67 (JSON)