Papers by Mattia Panni

1 papers
What Are You Token About? Differentiable Perturbed Top-k Token Selection for Scientific Document Summarization (2024.findings-acl)

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Challenge: Existing datasets suffer from a deficiency in source heterogeneity, hindering effective model training and generalizability.
Approach: They propose a dataset that includes technical and lay summaries from multiple journals . they propose 'prinepert' transformer-based model that prunes irrelevant tokens in end-to-end learning.
Outcome: The proposed model achieves a 2x speed-up compared to a state-of-the-art linear transformer, remaining comparable in effectiveness.

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