Papers by Italo Silva

1 papers
Weak Reward Model Transforms Generative Models into Robust Causal Event Extraction Systems (2024.emnlp-main)

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Challenge: Existing evaluation metrics that reflect the performance of causal event extraction tasks are poorly reflecting the inherent ambiguity of cause and effect boundaries.
Approach: They propose to use a weak-to-strong supervision method to train an evaluation model while still achieving high performance in training an RL model.
Outcome: The proposed method achieves high agreement with human-annotated data while still achieving high performance in training an RL model.

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