Advances in Multilingual Fact-Checking

The field of fact-checking is moving towards addressing the challenges of multilingual settings and low-resource languages. Researchers are exploring innovative approaches to improve the accuracy and efficiency of fact-checking systems, including the use of multi-agent frameworks, evidence boosting, and synthetic data fine-tuning. Noteworthy papers in this area include UrduFactCheck, which introduces a comprehensive fact-checking framework for Urdu, and EMULATE, which proposes a novel claim verification system that emulates human actions. Additionally, VeriFastScore demonstrates a significant speedup in long-form factuality evaluation, achieving a 6.6x overall speedup over existing methods.

Sources

SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrieval

UrduFactCheck: An Agentic Fact-Checking Framework for Urdu with Evidence Boosting and Benchmarking

EMULATE: A Multi-Agent Framework for Determining the Veracity of Atomic Claims by Emulating Human Actions

VeriFastScore: Speeding up long-form factuality evaluation

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