LIVE PULSE
4.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.2 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.0 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src1.8 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.4 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.1 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.1 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.1 Study examines issue bias in LLMs used as writing assistants before Swedish 2026 election — 1 src1.1 Study Audits Misalignment in Multi-Modal World Models — 1 src1.1 Retrieval-Grounded Reasoning Approach Proposed for Universal Multimodal Embeddings — 1 src4.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.2 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.0 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src1.8 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.4 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.1 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.1 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.1 Study examines issue bias in LLMs used as writing assistants before Swedish 2026 election — 1 src1.1 Study Audits Misalignment in Multi-Modal World Models — 1 src1.1 Retrieval-Grounded Reasoning Approach Proposed for Universal Multimodal Embeddings — 1 src
HEATPULSEAI MAGAZINES
FLIP · FOLLOW · SAVE
Log inSign up
papersSEP 12 04:00 UTC

EXYGEN framework enables conversational access to large knowledge graphs

Researchers present EXYGEN, an engine designed to let users query knowledge graphs through natural conversation rather than manual query languages. The work examines how well large language models translate ordinary text into SPARQL, the standard query language for graph databases, and then looks at applying those queries across large-scale graphs. The paper is a preprint posted to arXiv and has not yet been peer reviewed.

arXivEXYGENSPARQLknowledge graphslarge-language-models

COVERAGE · 2 REPORTS · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.LGEnabling Knowledge Graph Understanding at Scale with the EXplore Your Graphs ENgine (EXYGEN) ↗SEP 11 04:00 UTC
arXiv cs.AIEnabling Knowledge Graph Understanding at Scale with the EXplore Your Graphs ENgine (EXYGEN) ↗SEP 12 04:00 UTC

MORE LIKE THIS

papersPaper Argues Controlled Semantics Improve LLM Knowledge Graph Query Executionheat 1.1
papersFramework Lets LLMs Turn Natural Language into Metadata Queriesheat 0.1
papersMOSAIC proposes query-aware exploration policies for GraphRAG retrievalheat 0.1
papersVikingRAG: Token-efficient retrieval-augmented generation for structured documentsheat 0.1