Papers by Afra Akyürek

1 papers
DUnE: Dataset for Unified Editing (2023.emnlp-main)

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Challenge: Existing models are susceptible to errors necessitating a comprehensive retraining process.
Approach: They propose to define an edit as any natural language expression that solicits a change in the model’s outputs.
Outcome: The proposed editing benchmarks show that retrieval-augmented language modeling outperforms specialized editing techniques and neither set of approaches has fully solved the generalized editing problem covered by the proposed benchmark.

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