Papers by Reyhaneh Jabbarvand

1 papers
LETI: Learning to Generate from Textual Interactions (2024.findings-naacl)

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Challenge: Existing techniques fine-tune on input-output pairs or with numerical rewards that gauge the output quality are not effective.
Approach: They propose to fine-tune pre-trained language models with binary labels and a Python interpreter to get textual feedback from the inputs.
Outcome: The proposed model outperforms the base model on unseen problems and achieves comparable or better performance on humanEval.

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