This AI Breakthrough Solves Multilingual RAG’s Biggest Problem
Автор: CollapsedLatents
Загружено: 2025-11-09
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Описание:
🚀 *Struggling with multilingual AI hallucinations?* Discover **QTT-RAG**, a breakthrough in multilingual RAG that preserves factual integrity by turning translation quality into actionable intelligence.
🔍 **You’ll learn**:
✅ Why document translation boosts accuracy—but rewriting causes hallucinations
✅ The **rewriting paradox**: fixing fluency breaks truth
✅ How *QTT-RAG* uses LLMs to score translations on **semantic equivalence, grammar, and fluency**—without changing the text
✅ Up to *12.6% gains* on Korean & Finnish benchmarks (XOR-TyDi QA, MKQA), outperforming CrossRAG & DKM-RAG
✅ Why **soft filtering beats hard filtering**—preserving rare cross-lingual evidence
✅ Real failures: fabricated entities, missing sections, misrendered titles—*all flagged*
📌 Ideal for **AI researchers, RAG devs, and NLP engineers**. No black-box translation—just transparent, trustable reasoning.
🔗 **Code & Paper**: [GitHub.com/HoyeonM/QTT-RAG](https://github.com/HoyeonM/QTT-RAG) | Open Access
💬 **Like, Subscribe, and comment**: What’s your biggest multilingual AI challenge?
#MultilingualAI #RAG #LLM #AIResearch #NLP #MachineLearning #Translation #Factuality #QTT-RAG #OpenSourceAI
Read more on arxiv by searching for this paper: 2510.23070v1.pdf
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