Evaluation Of Text Generation

Evaluation of Text Generation is a scholarly methodological framework that systematizes the assessment of generated textual outputs by establishing criteria, metrics, and benchmarks to determine fidelity, coherence, relevance, and quality relative to human language expectations.

551

Publications

37.6K

Citations

1.8K

Authors

517

Institutions

Publications per year

2017–2026

395

Authors

1.8K

  1. AB
    Anja Belz

    University of Brighton, United Kingdom

    13 publications · 902 citations

    12

    h-index

  2. NA
    Noah A. Smith

    Carnegie Mellon University, United States

    11 publications · 572 citations

    11

    h-index

  3. YC
    Yejin Choi

    University of Washington, United States

    12 publications · 2.2K citations

    11

    h-index

  4. AG
    Albert Gatt

    University of Aberdeen, United Kingdom

    11 publications · 1.6K citations

    10

    h-index

  5. EK
    Emiel Krahmer

    Tilburg University, Netherlands

    10 publications · 1.5K citations

    10

    h-index

1–5 of 1.8K

Venues

  1. arXiv (Cornell University)

    Repository · 97 publications · 8.1K citations

    36

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 9 publications · 449 citations

    9

    h-index

  3. Computational Linguistics

    9 publications · 856 citations

    9

    h-index

  4. 9

    h-index

  5. Natural Language Engineering

    6 publications · 724 citations

    6

    h-index

1–5