כתבה
arXiv cs.CL ·
מודל Pleias-RAG לניתוח וציטוט
Even Small Reasoners Should Quote Their Sources: Introducing the Pleias-RAG Model Family
מודלים חדשים Pleias-RAG-350m ו-Pleias-RAG-1B משפרים את היכולת לניתוח וציטוט מקורות. הם תומכים בשפות רבות ומתחרים במודלים גדולים יותר כמו Llama ו-Qwen.
תקציר מקורי באנגליתarXiv:2504.18225v2 Announce Type: replace Abstract: We introduce a new generation of small reasoning models for RAG, search, and source summarization. Pleias-RAG-350m and Pleias-RAG-1B are mid-trained on a large synthetic dataset emulating the retrieval of a wide variety of multilingual open sources from the Common Corpus. They provide native support for citation and grounding with literal quotes and reintegrate multiple features associated with RAG workflows, such as query routing, query reformulation, and source reranking. Pleias-RAG-350m and Pleias-RAG-1B outperform SLMs below 4 billion parameters on standardized RAG benchmarks (HotPotQA, 2wiki) and are competitive with popular larger models, including Qwen-2.5-7B, Llama-3.1-8B, and Gemma-3-4B. They are the only SLMs to date maintaining
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arxiv.org
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