mlsanityData to 7 Oct 2026

Exploring the Landscape of Natural Language Processing Research

arXiv 2307.10652 ↗First posted 20 Jul 2023cs.CLcited by 7

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Abstract (arXiv)

As an efficient approach to understand, generate, and process natural language texts, research in natural language processing (NLP) has exhibited a rapid spread and wide adoption in recent years. Given the increasing research work in this area, several NLP-related approaches have been surveyed in the research community. However, a comprehensive study that categorizes established topics, identifies trends, and outlines areas for future research remains absent. Contributing to closing this gap, we have systematically classified and analyzed research papers in the ACL Anthology. As a result, we present a structured overview of the research landscape, provide a taxonomy of fields of study in NLP, analyze recent developments in NLP, summarize our findings, and highlight directions for future work.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 75 of its 125 references that are in the map. First posted on arXiv 20 Jul 2023.

Builds on

75 of 125 references.

References · 75

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38 more
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50 most cited of 75 All 75 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 2; 2026: 1.

7 papers.

  1. 2025LLMEval-Med: A Real-world Clinical Benchmark for Medical LLMs with Physician Validationcited by 29
  2. 2024Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classescited by 3
  3. 2024NLP-KG: A System for Exploratory Search of Scientific Literature in Natural Language Processingcited by 2
  4. 2024Is there really a Citation Age Bias in NLP?cited by 1
  5. 2024Conversational Exploratory Search of Scholarly Publications Using Knowledge Graphscited by 0
  6. 2025The Statistical Validation of Innovation Lenscited by 0
  7. 2026MADE: A Living Benchmark for Multi-Label Text Classification with Uncertainty Quantification of Medical Device Adverse Eventscited by 0