Papers with claim generation

3 papers
Toward Stance-based Personas for Opinionated Dialogues (2020.findings-emnlp)

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Challenge: chit-chat neural models lacking specificity and coherence, argues a new study on stance-based personas . stancebased personal representations lack generalization capability, allowing agents to sustain personal points of view both within the same conversation and across different discussions.
Approach: They propose to investigate stance-based persona representations and their impact on claim generation by using a conversational dataset.
Outcome: The proposed dataset shows that stance-based personas grasp abstract and profound aspects of the author persona.
Enriching Patent Claim Generation with European Patent Dataset (2025.findings-emnlp)

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Challenge: Existing work on large language models to assist inventors in writing patent claims relies on datasets from the United States Patent and Trademark Office.
Approach: They propose a European patent dataset that provides rich textual data and structured metadata to support multiple patent-related tasks.
Outcome: The proposed dataset outperforms existing datasets and GPT-4o in claim quality and cross-domain generalization.
Unknown Claims: Generation of Fact-Checking Training Examples from Unstructured and Structured Data (2024.emnlp-main)

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Challenge: Existing methods for fact-checking are labor-intensive and time-consuming.
Approach: They propose a framework that generates training instances for FC systems automatically using textual and tabular content.
Outcome: The proposed framework generates training instances for FC systems using textual and tabular content.

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