mlsanityData to 14 Oct 2026

Artificial Intuition: Efficient Classification of Scientific Abstracts

arXiv 2407.06093 ↗First posted 8 Jul 2024cs.AIcited by 2

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Abstract (arXiv)

It is desirable to coarsely classify short scientific texts, such as grant or publication abstracts, for strategic insight or research portfolio management. These texts efficiently transmit dense information to experts possessing a rich body of knowledge to aid interpretation. Yet this task is remarkably difficult to automate because of brevity and the absence of context. To address this gap, we have developed a novel approach to generate and appropriately assign coarse domain-specific labels. We show that a Large Language Model (LLM) can provide metadata essential to the task, in a process akin to the augmentation of supplemental knowledge representing human intuition, and propose a workflow. As a pilot study, we use a corpus of award abstracts from the National Aeronautics and Space Administration (NASA). We develop new assessment tools in concert with established performance metrics.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 16 of its 41 references that are in the map. First posted on arXiv 8 Jul 2024.

Builds on

16 of 41 references.

References · 16

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  3. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  4. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  5. 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,414
  6. 2021BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-modelscited by 1,245
  7. 2022Galactica: A Large Language Model for Sciencecited by 744
  8. 2020SPECTER: Document-level Representation Learning using Citation-informed Transformerscited by 430
  9. 2019Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approachcited by 308
  10. 2016Recurrent Neural Network for Text Classification with Multi-Task Learningcited by 144
  11. 2022Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddingscited by 75
  12. 2020PECOS: Prediction for Enormous and Correlated Output Spacescited by 50
4 more
  1. 2016Sequential Short-Text Classification with Recurrent and Convolutional Neural Networkscited by 28
  2. 2023Weakly-Supervised Scientific Document Classification via Retrieval-Augmented Multi-Stage Trainingcited by 8
  3. 2020Segmenting Scientific Abstracts into Discourse Categories: A Deep Learning-Based Approach for Sparse Labeled Datacited by 5
  4. 2023Weakly Supervised Multi-Label Classification of Full-Text Scientific Paperscited by 4

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Using Artificial Intuition in Distinct, Minimalist Classification of Scientific Abstracts for Management of Technology Portfolioscited by 0
  2. 2026AutoTail-BSFGM: Class-Balance-Aware Fine-Tuning for Chinese Scholarly Text Classificationcited by 0