Embedding coverage.

Mellum & Granite Embedding models are ready on llama.cpp

Embeddings Aren’t Magic: The Predictable Failure Modes of RAG Retrieval

Enterprise Document Intelligence [Vol. 1 #2] Why the same vector search that handles synonyms and paraphrase silently fails on negation, exact identifiers, and your company’s acron…

Extract Plain Text from Medium Posts for RAG and Search Indexes

Chunk clean article content for embeddings, summarization, and full-text search—skip nav, clap bars,...…

What lies outside the "regular" embeddings space of an LLM?

DinoV3 Embedding inference and visualization with Rust, ort and egui!

Planning Neural Dynamics with Lie Group Embedding through Supervised Projective Manifold Learning

We propose Lie group embedded dynamical neural networks (LieEDNN) and the corresponding learning algorithms based on gradient descent and metric projection on smooth manifold, wher…

RAG - Sparse Embedding

Sparse means thinly spread, scattered, or not dense. In sparse embeddings, chunks are converted into...…

SK Hynix is embedding cooling into HBM memory to stop AI chips from overheating

SK Hynix has introduced iHBM, a high-bandwidth memory packaging solution that changes how and where heat is managed inside the package. Rather than relying on conventional methods.…

BoxLitE: A Faithful Knowledge Base Embedding Based on Convex Optimization

Knowledge base (KB) embeddings aim at combining the capability of classical knowledge graph embeddings to generalize the information present in facts, the ABox, with conceptual kno…

Understanding and Improving Noisy Embedding Techniques in Instruction Finetuning

Recent advancements in instructional fine-tuning have injected noise into embeddings, with NEFTune (Jain et al., 2024) setting benchmarks using uniform noise. Despite NEFTune's emp…

Tested chunking + embeddings data from 3 production websites. [P]

From Manual RAG to Real Retrieval — Embedding-Based RAG with NVIDIA NIM

Replace hardcoded context with real retrieval using NVIDIA's nv-embedqa-e5-v5 embedding model. Cosine similarity, the query vs passage input distinction most beginners get wrong, n…

Building Context-Aware Search in Python with LLM Embeddings and Metadata

In this article, you will learn how to build a context-aware semantic search engine in Python that combines embedding-based similarity with structured metadata filtering.…

High Quality Embeddings for Horn Logic Reasoning

Neural networks can be trained to rank the choices made by logical reasoners, resulting in more efficient searches for answers. A key step in this process is creating useful embedd…

DIVE: Embedding Compression via Self-Limiting Gradient Updates

High-dimensional embeddings from large language models impose significant storage and computational costs on vector search systems. Recent embedding compression methods, including …

Evolutionary Data Making – How to train embedding models

We present an evolutionary search system that uses frontier language models to generate high-quality retrieval training data, guided by constitutional quality principles.…

Embedding by Elicitation: Dynamic Representations for Bayesian Optimization of System Prompts

System prompts are a central control mechanism in modern AI systems, shaping behavior across conversations, tasks, and user populations. Yet they are difficult to tune when feedbac…

Automated Big Data Quality Assessment using Knowledge Graph Embeddings

Automated data quality assessment is crucial for managing big data, but existing solutions face challenges in achieving accurate context-aware assessment. This paper presents a nov…

Chunking in RAG: why your splitter matters more than your embedding model

Why semantic chunkers rarely beat tuned recursive splitters, and how Anthropic's contextual retrieval cuts failed lookups by 35-67%.…

Domain-Independent Game Abstraction using Word Embedding Techniques

Many games of interest in the real world are often intractably large, thereby necessitating the use of game abstraction to shrink them in size, typically by many magnitudes. Over t…

RAG- Understanding of Embedding

What is Embedding? After text is split into chunks, the next process is called embedding....…

I built a vector embedding cache that makes stale hits structurally impossible

Wrote up the design behind embcache, a GPU-native two-tier cache for embeddings and KV states. The...…

What Is JEPA? Joint Embedding Predictive Architecture Framework Prediction

TLDR:Learn about Jepa (Joint Embedding Predictive Architecture), Yann LeCun’s framework for stable AI predictions in latent space without……

85. Embeddings and Vector Search: Memory for Language Models

A language model has no memory. You ask it a question. It generates an answer from its pretrained...…

Fastembed – Lightweight Python Embedding Library

Fast, Accurate, Lightweight Python library to make State of the Art Embedding - qdrant/fastembed…

We Don't Know the 2nd Circuit's Position on Embedding and Copyright Infringement

This case involves two videos: a video of basketball legend Michael Jordan breaking up a fight, and a video interview with rapper Melle Mel. Videographer Delray Richardson owned th…