Papers by Aditya Pillai

1 papers
Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkers (2024.findings-emnlp)

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Challenge: Large language models generate naturally sounding answers over a broad range of human inquiries, but they often generate answers that contradict real-world facts.
Approach: They propose a framework for annotating and evaluating the factuality of large language models . they propose 'factcheck-bench' which provides a multi-stage annotation scheme .
Outcome: The proposed framework outperforms several popular LLM fact-checkers in claim, sentence, and document levels.

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