mlsanityData to 7 Oct 2026

fact check AI at SemEval-2025 Task 7: Multilingual and Crosslingual Fact-checked Claim Retrieval

arXiv 2508.03475 ↗First posted 5 Aug 2025cs.CL cs.AI cs.IRcited by 0

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Abstract (arXiv)

SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrieval is approached as a Learning-to-Rank task using a bi-encoder model fine-tuned from a pre-trained transformer optimized for sentence similarity. Training used both the source languages and their English translations for multilingual retrieval and only English translations for cross-lingual retrieval. Using lightweight models with fewer than 500M parameters and training on Kaggle T4 GPUs, the method achieved 92% Success@10 in multilingual and 80% Success@10 in 5th in crosslingual and 10th in multilingual tracks.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 5 of its 8 references that are in the map. First posted on arXiv 5 Aug 2025.

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5 of 8 references.

References · 5

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  2. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  3. 2017Efficient Natural Language Response Suggestion for Smart Replycited by 228
  4. 2023Multilingual Previously Fact-Checked Claim Retrievalcited by 32
  5. 2025SemEval-2025 Task 7: Multilingual and Crosslingual Fact-Checked Claim Retrievalcited by 11

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