RAG News

This feed includes only recent releases, roughly from the last 12 months, not the full historical archive. That is why a long-established product may have only a few news items.

4 news

RAG
Papers with Code: hybrid search across 110k+ papers via HF Inference/Jobs/Buckets

A production RAG infrastructure example: PostgreSQL full-text plus semantic search with Qwen3-Embedding-0.6B (256-dimensional Matryoshka vectors), corpus embedding in batches on HF Jobs (L4, about 75 articles/sec), Storage Buckets as a versioned layer between compute and the database, and merging via Reciprocal Rank Fusion with a lexical-only fallback on timeout.

here batch jobs are used instead of streaming - offline reindexing, not a real-time pipeline Apache Kafka →
RAG
Sentence Transformers v6.0: multi-vector (late interaction) encoders

The new MultiVectorEncoder class brings ColBERT-like late interaction on top of dense/sparse models, already in the library. It is more precise on nuances (token-to-token MaxSim instead of compressing into a single vector), but the index is orders of magnitude heavier: 311.5 MB vs 7.5 MB dense on 4,874 Natural Questions passages. 40+ open checkpoints (LateOn, mLateOn, ColBERT, ColPali) are available on HF Hub.

RAG
Sentence Transformers v5.4: Multimodal Embeddings and Rerankers

A unified API for encoding and comparing text, images, audio, and video with a single model; rerankers have also become multimodal (Qwen3-VL, BAAI BGE-VL, NVIDIA Nemotron—all with open weights). The retrieve-and-rerank pattern now works with mixed content, enabling RAG for visual documents and screenshots, not just text.

RAG
EmbeddingGemma: Google's compact embedding model for RAG

EmbeddingGemma-300M (open weights, Apache 2.0) ranks at the top of multilingual MTEB among models under 500M, with a 2,048-token context and Matryoshka embeddings truncated from 768 dimensions. In the medical domain, fine-tuning outperformed the larger Qwen3-Embedding-0.6B: 0.8862 versus 0.8493 NDCG@10.

Discuss RAG News

Enter your email or phone number so we can get back to you.

Send via: