Quantized open-weight LMs on consumer hardware match closed-source API accuracy for LM-enhanced relational operators while delivering 390x lower cost and 3.8x lower latency in the BlendSQL framework.
arXiv:2510.25506 (2025)
2 Pith papers cite this work. Polarity classification is still indexing.
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Reproducibility study of Vul-RAG confirms original findings in a fully local open-weights setting but identifies a persistent performance plateau at approximately 0.30 pairwise accuracy across diverse recent open-weight LLMs.
citing papers explorer
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Large Databases Need Small, Open-Weight Language Models
Quantized open-weight LMs on consumer hardware match closed-source API accuracy for LM-enhanced relational operators while delivering 390x lower cost and 3.8x lower latency in the BlendSQL framework.
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Revisiting Vul-RAG: Reproducibility and Replicability of RAG-based Vulnerability Detection with Open-Weight Models
Reproducibility study of Vul-RAG confirms original findings in a fully local open-weights setting but identifies a persistent performance plateau at approximately 0.30 pairwise accuracy across diverse recent open-weight LLMs.