Oct 15, 2025 · Artificial Intelligence

REFRAG: Using Tiny Models to Compress RAG for Faster, Smarter AI

Meta’s new REFRAG framework lets a lightweight encoder compress retrieved text into semantic tags, enabling large language models to answer queries with far fewer tokens, lower latency, and higher throughput, while preserving core meaning and allowing flexible placement of compressed information within prompts.

LLM efficiencyRAGmodel compression

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REFRAG: Using Tiny Models to Compress RAG for Faster, Smarter AI

58 Tech

Aug 10, 2021 · Artificial Intelligence

Active Learning and Model Enhancements for Semantic Tag Mining in 58.com Voice Data

This article presents a comprehensive study on extracting semantic tags from 58.com voice data, detailing the use of active learning to address cold‑start problems, comparing keyword matching, XGBoost, TextCNN, CRNN, and an improved Wide&Deep model, and demonstrating significant reductions in labeling effort and superior F1 scores across multiple experiments.

CRNNactive learningmodel comparison

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Active Learning and Model Enhancements for Semantic Tag Mining in 58.com Voice Data