Llama-Embed-Nemotron-8B Collection State-of-the-Art Text Embedding Model • 3 items • Updated 6 days ago • 4
KoViDoRe Benchmark (BEIR) v2 Collection Korean Vision Document Retrieval Benchmark • 6 items • Updated 12 days ago • 5
view article Article Small Yet Mighty: Improve Accuracy In Multimodal Search and Visual Document Retrieval with Llama Nemotron RAG Models 20 days ago • 20
Omni-Embed-Nemotron: A Unified Multimodal Retrieval Model for Text, Image, Audio, and Video Paper • 2510.03458 • Published Oct 3, 2025 • 2
Llama-Embed-Nemotron-8B: A Universal Text Embedding Model for Multilingual and Cross-Lingual Tasks Paper • 2511.07025 • Published Nov 10, 2025 • 13
ViDoRe Benchmark V3 Collection ViDoRe V3 is our latest benchmark, engineered to set a new industry gold standard for multi-modal, enterprise document retrieval evaluation. • 8 items • Updated 12 days ago • 17
view article Article ViDoRe V3: a comprehensive evaluation of retrieval for enterprise use-cases Nov 5, 2025 • 58
Nemotron RAG Collection Set of tools to build retrieval-augmented generation (RAG) systems, improve search and ranking accuracy, and extract structured data from complex do • 11 items • Updated 6 days ago • 64
view article Article Llama‑Embed‑Nemotron‑8B Text Embedding Model Ranks First on Multilingual MTEB Leaderboard Oct 21, 2025 • 14