AIC CTU@AVerImaTeC: Revolutionizing Fact-Checking with Dual-Retriever RAG

research #rag 🔬 Research|Analyzed: Feb 18, 2026 05:02•

Published: Feb 18, 2026 05:00

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1 min read

Analysis

This research introduces a fascinating new system for image-text fact-checking, leveraging a dual-retriever Retrieval-Augmented Generation (RAG) approach. The system's competitive performance is especially impressive given its simplicity and low cost, demonstrating a clear path towards accessible and efficient fact-checking models.

Key Takeaways

•The system combines textual and image retrieval for enhanced fact-checking.
•It achieves competitive performance using a single Large Language Model (LLM) call per check.
•The system's low operational cost of $0.013 per check is highly attractive.

Reference / Citation

View Original

"Our system delivers competitive performance with a single multimodal LLM call per fact-check at just $0.013 on average using GPT5.1 via OpenAI Batch API."

ArXiv NLPFeb 18, 2026 05:00

* Cited for critical analysis under Article 32.

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