mlsanityData to 7 Oct 2026

Intent Detection and Entity Extraction from BioMedical Literature

arXiv 2404.03598 ↗First posted 4 Apr 2024cs.CLcited by 6

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Abstract (arXiv)

Biomedical queries have become increasingly prevalent in web searches, reflecting the growing interest in accessing biomedical literature. Despite recent research on large-language models (LLMs) motivated by endeavours to attain generalized intelligence, their efficacy in replacing task and domain-specific natural language understanding approaches remains questionable. In this paper, we address this question by conducting a comprehensive empirical evaluation of intent detection and named entity recognition (NER) tasks from biomedical text. We show that Supervised Fine Tuned approaches are still relevant and more effective than general-purpose LLMs. Biomedical transformer models such as PubMedBERT can surpass ChatGPT on NER task with only 5 supervised examples.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 25 of its 49 references that are in the map. First posted on arXiv 4 Apr 2024.

Builds on

25 of 49 references.

References · 25

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  2. 2020Language Models are Few-Shot Learnerscited by 32,199
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  8. 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,935
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13 more
  1. 2023One Small Step for Generative AI, One Giant Leap for AGI: A Complete Survey on ChatGPT in AIGC Eracited by 55
  2. 2018Zero-shot User Intent Detection via Capsule Neural Networkscited by 54
  3. 2021Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and Systemcited by 30
  4. 2022Optimizing Bi-Encoder for Named Entity Recognition via Contrastive Learningcited by 24
  5. 2020A BERT based Sentiment Analysis and Key Entity Detection Approach for Online Financial Textscited by 21
  6. 2016Classification under Streaming Emerging New Classes: A Solution using Completely Random Treescited by 17
  7. 2021Natural Language Processing for Smart Healthcarecited by 14
  8. 2024MatSciRE: Leveraging Pointer Networks to Automate Entity and Relation Extraction for Material Science Knowledge-base Constructioncited by 11
  9. 2020MatScIE: An automated tool for the generation of databases of methods and parameters used in the computational materials science literaturecited by 10
  10. 2023Intent Identification and Entity Extraction for Healthcare Queries in Indic Languagescited by 9
  11. 2022Fine-grained Intent Classification in the Legal Domaincited by 8
  12. 2023Novel Intent Detection and Active Learning Based Classification (Student Abstract)cited by 6
  13. 2017Bringing Semantic Structures to User Intent Detection in Online Medical Queriescited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 5; 2026: 1.

6 papers.

  1. 2025Do LLMs Surpass Encoders for Biomedical NER?cited by 6
  2. 2025Text Takes Over: A Study of Modality Bias in Multimodal Intent Detectioncited by 6
  3. 2025CodeSCM: Causal Analysis for Multi-Modal Code Generationcited by 2
  4. 2025Introducing Spotlight: A Novel Approach for Generating Captivating Key Information from Documentscited by 1
  5. 2025IDALC: A Semi-Supervised Framework for Intent Detection and Active Learning based Correctioncited by 0
  6. 2026Domain-Adaptive Pretraining Enhances Water Treatment Semantic Representation for Large-Scale Structured Literature Miningcited by 0