Papers by Jane Arleth Dela Cruz

1 papers
Evaluating Large Language Models for Confidence-based Check Set Selection (2025.findings-acl)

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Challenge: Large language models have shown promise in automating high-labor data tasks, but their tendency to answer despite uncertainty and their difficulty handling long input contexts robustly are key challenges for adoption.
Approach: They propose to use LLMs to prioritize information needing human judgment to identify low-confidence outputs for human review through "check set selection" using social media monitoring, they define the "check sets" as a list of tweets escalated to the disaster manager when the LLM has the least confidence.
Outcome: The proposed approach outperforms random-sample check set selection in disaster tweet classification.

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