mlsanityData to 7 Oct 2026

Natural Language Processing: State of The Art, Current Trends and Challenges

arXiv 1708.05148 ↗First posted 17 Aug 2017cs.CLcited by 114

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Abstract (arXiv)

Natural language processing (NLP) has recently gained much attention for representing and analysing human language computationally. It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc. The paper distinguishes four phases by discussing different levels of NLP and components of Natural Language Generation (NLG) followed by presenting the history and evolution of NLP, state of the art presenting the various applications of NLP and current trends and challenges.

Key facts. Cited by 114 papers in the map (data through 7 Oct 2026). First posted on arXiv 17 Aug 2017.

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Citing papers per year: 2021: 4; 2022: 10; 2023: 27; 2024: 42; 2025: 25; 2026: 6.

114 papers.

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  10. 2021Question Answering Survey: Directions, Challenges, Datasets, Evaluation Matricescited by 17
  11. 2024CLIP-AGIQA: Boosting the Performance of AI-Generated Image Quality Assessment with CLIPcited by 14
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38 more
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  6. 2024Automated Review Generation Method Based on Large Language Modelscited by 7
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  11. 2024Beyond Labels: Aligning Large Language Models with Human-like Reasoningcited by 6
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  18. 2025Persona-Based Synthetic Data Generation Using Multi-Stage Conditioning with Large Language Models for Emotion Recognitioncited by 5
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  27. 2024Multi-Agents Based on Large Language Models for Knowledge-based Visual Question Answeringcited by 3
  28. 2026GhanaNLP Parallel Corpora: Comprehensive Multilingual Resources for Low-Resource Ghanaian Languagescited by 3
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  30. 2021A Dimensionality Reduction Approach for Convolutional Neural Networkscited by 2
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  38. 2024MLP-KAN: Unifying Deep Representation and Function Learningcited by 2

50 most cited of 114 All 114 (JSON)