agentic-retrieval

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#agentic-retrieval

NVIDIA Nemotron 3 Embed Ranks #1 Overall on RTEB, Advancing Agentic Retrieval

Hugging Face Blog · 3d ago Cached

NVIDIA releases Nemotron 3 Embed, a collection of open embedding models that top the RTEB leaderboard, featuring an 8B flagship model and efficient 1B variants for production-scale retrieval.

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#agentic-retrieval

@jerryjliu0: We've created a comprehensive Retrieval Harness for modern agentic retrieval in 2026. The harness provides a persistent…

X AI KOLs Timeline · 2026-07-04 Cached

LlamaIndex has created a Retrieval Harness for modern agentic retrieval, providing a persistent data pipeline for connecting, indexing, and querying large knowledge bases with tools like semantic search and regex grep, allowing agents to autonomously navigate knowledge bases.

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#agentic-retrieval

@barrowjoseph: https://x.com/barrowjoseph/status/2065423284343050314

X AI KOLs Timeline · 2026-06-12 Cached

A blog post revisits the concept of 'Slow Search' in the context of agentic retrieval, arguing that per-query latency can be traded for better retrieval quality to reduce overall task time and cost for AI agents.

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#agentic-retrieval

Infini Memory: Maintainable Topic Documents for Long-Term LLM Agent Memory

arXiv cs.AI · 2026-06-10 Cached

Introduces Infini Memory, a maintainable text-based persistent memory architecture for LLM agents that uses topic-structured documents and iterative retrieval to improve long-term memory usage, achieving 64.7% on MemoryAgentBench.

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#agentic-retrieval

MemDreamer: Decoupling Perception and Reasoning for Long Video Understanding via Hierarchical Graph Memory and Agentic Retrieval Mechanism

Hugging Face Daily Papers · 2026-06-05 Cached

MemDreamer decouples perception and reasoning for long video understanding using hierarchical graph memory and agentic retrieval, achieving state-of-the-art performance with reduced computational overhead.

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#agentic-retrieval

Mini-JEPA Foundation Model Fleet Enables Agentic Hydrologic Intelligence

arXiv cs.LG · 2026-05-15 Cached

This paper introduces a fleet of five sensor-specialized Mini-JEPA foundation models for hydrologic intelligence, achieving high reconstruction accuracy (R² up to 0.97) and outperforming the Google AlphaEarth generalist on physics-matched tasks when routed via an LLM agent.

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