Learning to repair: Repairing model output errors after deployment using a dynamic memory of feedback

Association for Computational Linguistics 2022, Clark, Peter, Madaan, Aman, Tandon, Niket, Yang, Yiming

DOI: 10.48448/f6tw-gj14
Published: 2022
Container: Not recorded
Publisher: Underline Science Inc.
Open access: no

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limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

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Cite this work

BibTeX

@article{allodium:10.48448/f6tw-gj14,
  title = {Learning to repair: Repairing model output errors after deployment using a dynamic memory of feedback},
  author = {Association for Computational Linguistics 2022 and Clark, Peter and Madaan, Aman and Tandon, Niket and Yang, Yiming},
  year = {2022},
  doi = {10.48448/f6tw-gj14},
  url = {https://doi.org/10.48448/f6tw-gj14}
}

RIS

TY  - JOUR
TI  - Learning to repair: Repairing model output errors after deployment using a dynamic memory of feedback
AU  - Association for Computational Linguistics 2022
AU  - Clark, Peter
AU  - Madaan, Aman
AU  - Tandon, Niket
AU  - Yang, Yiming
PY  - 2022
DO  - 10.48448/f6tw-gj14
UR  - https://doi.org/10.48448/f6tw-gj14
ER  -

APA

2022, A. F. C. L., Peter, C., Aman, M., Niket, T., & Yiming, Y. (2022). Learning to repair: Repairing model output errors after deployment using a dynamic memory of feedback. https://doi.org/10.48448/f6tw-gj14

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datacite · retrieved 2026-11-09T12:33:25.330Z