Papers by Chris Samarinas

2 papers
Improving Evidence Retrieval for Automated Explainable Fact-Checking (2021.naacl-demos)

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Challenge: Automated fact-checking on a large scale is time consuming and intractable.
Approach: They propose a three-stage automated fact-checking system using evidence retrieval and selection methods to improve evidence recall in a noisy environment.
Outcome: The proposed system can verify open-domain claims using results from web search engines.
Beyond Factual Accuracy: Evaluating Coverage of Diverse Factual Information in Long-form Text Generation (2025.findings-acl)

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Challenge: Existing evaluation frameworks for large language models focus on isolated aspects like * Equal contribution.
Approach: They evaluate ICAT, an evaluation framework for measuring coverage of diverse factual information in long-form text generation.
Outcome: The evaluation framework is based on three implementations with different assumptions on availability of aspects and alignment method.

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