knowledge graphs
30 articles about knowledge graphs in AI news
Alibaba AVA-Encoder Maps Films to Knowledge Graphs, +20.7 Fidelity
Alibaba Qwen's AVA-Encoder maps films to editable knowledge graphs, boosting reconstruction fidelity by 20.7 points. The graph-based approach could enable semantic video editing, but details are sparse.
Neo4j's agent-memory: Open-source unified memory for AI agents via knowledge graphs
Neo4j releases agent-memory, an open-source unified memory layer for AI agents using knowledge graphs, enabling persistent structured recall.
Graphify: Open-Source Tool Builds Knowledge Graphs from Code & Docs in One Command
Developer shipped Graphify, an open-source tool that builds queryable knowledge graphs from code, docs, and images in one command. It uses a two-pass pipeline with tree-sitter and Claude subagents, achieving 71.5x fewer tokens per query versus reading raw files.
Multimodal Knowledge Graphs Unlock Next-Generation AI Training Data
Researchers have developed MMKG-RDS, a novel framework that synthesizes high-quality reasoning training data by mining multimodal knowledge graphs. The system addresses critical limitations in existing data synthesis methods and improves model reasoning accuracy by 9.2% with minimal training samples.
EpisTwin: A Neuro-Symbolic Framework for Personal AI Using Knowledge Graphs
Researchers propose EpisTwin, a neuro-symbolic architecture that builds a Personal Knowledge Graph from fragmented user data to enable complex, verifiable reasoning. It addresses limitations of standard RAG by capturing semantic topology and temporal dependencies.
GitNexus Revolutionizes Code Exploration: Browser-Based AI Transforms GitHub Repositories into Interactive Knowledge Graphs
A new tool called GitNexus transforms any GitHub repository into an interactive knowledge graph with AI chat capabilities, running entirely in the browser without backend infrastructure. This breakthrough enables developers to visualize and query complex codebases through intuitive graph interfaces and natural language conversations.
Graphify Turns Codebases Into Queryable Graphs Without Vectors or LLMs
Graphify maps codebases into local knowledge graphs using tree-sitter AST parsing, no LLMs or vector stores. At 82k+ stars, it supports 40+ languages and 20+ AI assistants.
HG-RAG Beats Flat Retrieval on Graph Queries Across 800-Node Worlds
HG-RAG uses graph-traversal over knowledge graphs for RAG, beating flat retrieval on hierarchical and multi-hop queries across worlds up to 800 nodes.
Graph-Based Recommendations for E-Commerce: A Technical Primer
An overview of how graph-based recommendation systems work, using knowledge graphs to connect users, items, and attributes for more accurate and explainable product suggestions in e-commerce.
Beyond Vector Search: How Core-Based GraphRAG Unlocks Deeper Customer Intelligence for Luxury Brands
A new GraphRAG method using k-core decomposition creates deterministic, hierarchical knowledge graphs from customer data. This enables superior 'global sensemaking'—connecting disparate insights across reviews, transcripts, and CRM notes to build a unified, actionable view of the client and market.
MIRAGE AI Framework Bridges Critical Gap in Alzheimer's Diagnosis by Synthesizing MRI Insights from Health Records
Researchers have developed MIRAGE, a novel AI framework that uses knowledge graphs to synthesize diagnostic MRI information from electronic health records, potentially revolutionizing Alzheimer's disease assessment in resource-limited settings by bridging the missing-modality gap.
Neo4j-backed course teaches agentic knowledge graph construction
Neo4j and Andreas Kollegger released a free course on agentic knowledge graph construction using Google's ADK, promising better grounding than RAG. The course teaches parallel processing of CSV and text into a linked graph.
FORGE Benchmark Reveals Domain Knowledge
Researchers introduced FORGE, a multimodal dataset with 2D/3D data and fine-grained annotations for manufacturing. Evaluating 18 MLLMs revealed domain knowledge, not visual grounding, is the key bottleneck, with fine-tuning offering a clear path forward.
Developer Ships LLM-Powered Knowledge Graph Days After Karpathy Tweet
Following a tweet by Andrej Karpathy, a developer rapidly built and released a working implementation of an LLM-powered knowledge graph on GitHub, showcasing the speed of open-source AI development.
K-CARE: A New Framework Grounds LLMs in External Knowledge to Fix
K-CARE combines Symmetrical Contextual Anchoring (behavior data) and Analogical Prototype Reasoning (expert examples) to resolve e-commerce search relevance issues that pure LLM reasoning can't fix. Proven in offline and online A/B tests on a leading platform.
Code-Review-Graph Cuts Claude Token Usage 8.2x with Local Knowledge Graph
A developer released 'code-review-graph,' an open-source tool that uses Tree-sitter to build a persistent structural map of a codebase. This allows Claude to read only relevant files, cutting average token usage by 8.2x across six real repositories.
Graph Engineering Survey Proposes System-Level Intelligence
Survey proposes Graph Engineering using dynamic graphs to coordinate LLM agents, targeting System Intelligence beyond individual agents. No empirical benchmarks yet.
K12-KGraph: Chinese Textbook KG Beats Gemini-3-Flash at 57%
K12-KGraph, a 10,685-node knowledge graph from Chinese textbooks, includes a 23,640-question benchmark where Gemini-3-Flash scores 57%.
GBrain: Garry Tan's Agent Memory Uses Markdown as System of Record
GBrain is Garry Tan's agent memory system using markdown as the system of record, with a self-wiring knowledge graph and overnight dream cycle.
Five MCP Servers That Cut Claude Code Blind-Edits from 33.7% to Near Zero
A five-MCP-server cold-start routine for Claude Code cuts blind-edit rates from 33.7% to near zero, using memory, codebase graphs, web search, and live docs.
OmniSch Benchmark Exposes Major Gaps in LMMs for PCB Schematic Understanding
Researchers introduced OmniSch, a benchmark with 1,854 real PCB schematics, to evaluate LMMs on converting diagrams to netlist graphs. Results show current models have unreliable grounding, brittle parsing, and inconsistent connectivity reasoning for engineering artifacts.
ReXInTheWild Benchmark Reveals VLMs Struggle with Medical Photos: Gemini-3 Leads at 78%, MedGemma Trails at 37%
Researchers introduced ReXInTheWild, a benchmark of 955 clinician-verified questions based on 484 real medical photographs. Leading multimodal models show wide performance gaps, with Gemini-3 scoring 78% accuracy while the specialized MedGemma model achieved only 37%.
Building a Smart Learning Path Recommendation System Using Graph Neural Networks
A technical article outlines how to build a learning path recommendation system using Graph Neural Networks (GNNs). It details constructing a knowledge graph and applying GNNs for personalized course sequencing, a method with clear parallels to retail product discovery.
EMBRAG Framework Achieves SOTA on KGQA Benchmarks via Embedding-Space Rule Generation
Researchers propose EMBRAG, a framework that uses LLMs to generate logical rules from a query, then performs multi-hop reasoning in knowledge graph embedding space. It sets new state-of-the-art on two KGQA benchmarks.
How Godogen's Claude Code Skills Solve LLM Game Development
A developer built two Claude Code skills that generate complete Godot games by solving three key LLM bottlenecks: GDScript knowledge, build-time/runtime state, and visual QA.
How Non-Developers Can Use `claude --resume` and CLAUDE.md to Save Hours
Stop losing your work and repeating yourself. Use `claude --resume` to recover sessions and CLAUDE.md as a permanent knowledge base for any project.
Tuning-Free LLM Framework IKGR Builds Strong Recommender by Extracting Explicit User Intent
Researchers propose IKGR, a novel LLM-based recommender that constructs an intent-centric knowledge graph without model fine-tuning. It explicitly links users and items to extracted intents, showing strong performance on cold-start and long-tail items.
Beyond RAG: How AI Memory Systems Are Creating Truly Adaptive Agents
AI development is shifting from static retrieval systems to dynamic memory architectures that enable continual learning. This evolution from RAG to agent memory represents a fundamental change in how AI systems accumulate and utilize knowledge over time.
DiffGraph: An Agent-Driven Graph Framework for Automated Merging of Online Text-to-Image Expert Models
Researchers propose DiffGraph, a framework that automatically organizes and merges specialized online text-to-image models into a scalable graph. It dynamically activates subgraphs based on user prompts to combine expert capabilities without manual intervention.
CLI vs MCP: Hands-On Experiments Show 250 Tokens vs Over 2,000 for the Same Task
An AI developer ran three experiments comparing CLI and MCP for AI agents. CLI used 250 tokens for file ops and Git; MCP used over 2,000 due to tool schema overhead, but MCP won for web fetching (250 tokens vs 2,000+ for CLI).