Papers by Salena Ashton

1 papers
When and Where Did it Happen? An Encoder-Decoder Model to Identify Scenario Context (2024.findings-emnlp)

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Challenge: a relatively small fine-tuned encoder-decoder model performs better than out-of-the-box LLMs and semantic role labeling parsers to accurately predict the relevant scenario information.
Approach: They propose a neural architecture finetuned for the task of scenario context generation . they use a curated dataset of time and location annotations to train an encoder-decoder architecture .
Outcome: The proposed model performs better than out-of-the-box LLMs and semantic role labeling parsers to accurately predict the relevant scenario information of a particular entity or event.

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