📌 Typed-Centrality Grounding for Agentic GraphRAG: A Symbolic Approach for Agentic Reasoning
Rosario Napoli et al.
#arXiv #cs.AI
Rosario Napoli et al.
#arXiv #cs.AI
Typed-Centrality Grounding for Agentic GraphRAG: A Symbolic Approach for Agentic Reasoning
Knowledge Graphs (KGs) and Large Language Models (LLMs) represent two approaches for knowledge representation and reasoning over heterogeneous data. Recent research has explored their integration through Graph Retrieval-Augmented Generation (GraphRAG) systems, which use KGs to provide structured co…
arxiv.org
November 9, 2026 at 8:03 AM
Building a knowledge graph is the easy part. Keeping it current without duplicates, stale relationships, or accidental deletions is harder. This walkthrough shows how content hashes, provenance, and scoped retraction make incremental GraphRAG indexing practical.
www.falkordb.com/reference/gr...
www.falkordb.com/reference/gr...
Keeping GraphRAG Fresh Without Full Rebuilds | FalkorDB
Keep GraphRAG fresh without full rebuilds. Idempotent graph updates, change detection, and a working FalkorDB and CocoIndex implementation.
www.falkordb.com
November 6, 2026 at 1:03 PM
Building a knowledge graph is the easy part. Keeping it current without duplicates, stale relationships, or accidental deletions is harder. This walkthrough shows how content hashes, provenance, and scoped retraction make incremental GraphRAG indexing practical.
www.falkordb.com/reference/gr...
www.falkordb.com/reference/gr...
📌 Typed-Centrality Grounding for Agentic GraphRAG: A Symbolic Approach for Agentic Reasoning
Rosario Napoli et al.
#arXiv #cs.AI
Rosario Napoli et al.
#arXiv #cs.AI
Typed-Centrality Grounding for Agentic GraphRAG: A Symbolic Approach for Agentic Reasoning
Knowledge Graphs (KGs) and Large Language Models (LLMs) represent two approaches for knowledge representation and reasoning over heterogeneous data. Recent research has explored their integration through Graph Retrieval-Augmented Generation (GraphRAG) systems, which use KGs to provide structured co…
arxiv.org
November 9, 2026 at 11:04 AM
ナレッジグラフとかGraphRAGとかやるか
November 8, 2026 at 2:31 AM
ナレッジグラフとかGraphRAGとかやるか
Differentially Private GraphRAG: Protecting Relation Connectivity and Semantics
Jie Fu, Yuan Hong, Yue Ning, Wendy Hui Wang
http://arxiv.org/abs/2611.09658
Jie Fu, Yuan Hong, Yue Ning, Wendy Hui Wang
http://arxiv.org/abs/2611.09658
November 9, 2026 at 4:54 AM
Differentially Private GraphRAG: Protecting Relation Connectivity and Semantics
Jie Fu, Yuan Hong, Yue Ning, Wendy Hui Wang
http://arxiv.org/abs/2611.09658
Jie Fu, Yuan Hong, Yue Ning, Wendy Hui Wang
http://arxiv.org/abs/2611.09658
GraphRAG入門 ― ベクトル検索が苦手な「関係性」の質問に、グラフで答える | Johnny Ponta #zenn
https://zenn.dev/johnny1024/articles/e60c15eb622d3b
https://zenn.dev/johnny1024/articles/e60c15eb622d3b
GraphRAG入門 ― ベクトル検索が苦手な「関係性」の質問に、グラフで答える
zenn.dev
November 9, 2026 at 3:03 AM
GraphRAG入門 ― ベクトル検索が苦手な「関係性」の質問に、グラフで答える | Johnny Ponta #zenn
https://zenn.dev/johnny1024/articles/e60c15eb622d3b
https://zenn.dev/johnny1024/articles/e60c15eb622d3b
Opinion: GraphRAG and classic RAG address different retrieval problems rather than one outperforming the other.
November 8, 2026 at 4:17 PM
Opinion: GraphRAG and classic RAG address different retrieval problems rather than one outperforming the other.
Article: Your Hybrid GraphRAG Fails Silently: When a Broken Retriever Looks Like an Empty Answer
November 8, 2026 at 12:26 PM
Article: Your Hybrid GraphRAG Fails Silently: When a Broken Retriever Looks Like an Empty Answer
Neo4j's GraphRAG Python package now defaults to CPU-only PyTorch wheels. Less installation overhead for applications that don't need GPU inference. Sometimes the best developer experience improvement is removing dependencies.
github.com/neo4j/neo4j-...
github.com/neo4j/neo4j-...
GitHub - neo4j/neo4j-graphrag-python: Neo4j GraphRAG for Python
Neo4j GraphRAG for Python. Contribute to neo4j/neo4j-graphrag-python development by creating an account on GitHub.
github.com
November 3, 2026 at 1:02 PM
Neo4j's GraphRAG Python package now defaults to CPU-only PyTorch wheels. Less installation overhead for applications that don't need GPU inference. Sometimes the best developer experience improvement is removing dependencies.
github.com/neo4j/neo4j-...
github.com/neo4j/neo4j-...
Chaos Cypher v0.7.2: chat searches by tag. A tag the assistant picks only narrows: a scoped chat stays in scope, and tags matching nothing return nothing, never everything. https://chaoscypher.com/docs/about/changelog#v072-2026-11-06 #GraphRAG #selfhosted
November 9, 2026 at 2:43 PM
Chaos Cypher v0.7.2: chat searches by tag. A tag the assistant picks only narrows: a scoped chat stays in scope, and tags matching nothing return nothing, never everything. https://chaoscypher.com/docs/about/changelog#v072-2026-11-06 #GraphRAG #selfhosted
Istituto Nazionale di Fisica Nucleare is hiring:
Research Technologist (Level 1) in High-Dimensional Biostatistics and GraphRAG for Clinical Evidence Verification
#computerscience #medicine
Research Technologist (Level 1) in High-Dimensional Biostatistics and GraphRAG for Clinical Evidence Verification
#computerscience #medicine
November 8, 2026 at 5:59 PM
Istituto Nazionale di Fisica Nucleare is hiring:
Research Technologist (Level 1) in High-Dimensional Biostatistics and GraphRAG for Clinical Evidence Verification
#computerscience #medicine
Research Technologist (Level 1) in High-Dimensional Biostatistics and GraphRAG for Clinical Evidence Verification
#computerscience #medicine
Building enterprise AI on your documents? On Nov 19 we compare RAG, GraphRAG and LAKEer on three things that matter: how they retrieve, how trustworthy the answers are, and what each costs per query.
Free webinar, 9am PT:
us06web.zoom.us/webinar/regi...
Free webinar, 9am PT:
us06web.zoom.us/webinar/regi...
Welcome! You are invited to join a webinar: RAG to GraphRAG to LAKEer. After registering, you will receive a confirmation email about joining the webinar.
How RAG, GraphRAG and LAKEer differ in how they retrieve information, how trustworthy their answers are, and what they cost per query, and why it matters for enterprise AI applications.
us06web.zoom.us
November 9, 2026 at 3:27 PM
Building enterprise AI on your documents? On Nov 19 we compare RAG, GraphRAG and LAKEer on three things that matter: how they retrieve, how trustworthy the answers are, and what each costs per query.
Free webinar, 9am PT:
us06web.zoom.us/webinar/regi...
Free webinar, 9am PT:
us06web.zoom.us/webinar/regi...
📦 tapiruslab/tapirusdb v1.0.2
PHP HTTP client for the TapirusDB SQL, vector and GraphRAG daemon APIs
🔗 https://github.com/tapiruslab/TapirusDB
PHP HTTP client for the TapirusDB SQL, vector and GraphRAG daemon APIs
🔗 https://github.com/tapiruslab/TapirusDB
November 7, 2026 at 9:59 AM
📦 tapiruslab/tapirusdb v1.0.2
PHP HTTP client for the TapirusDB SQL, vector and GraphRAG daemon APIs
🔗 https://github.com/tapiruslab/TapirusDB
PHP HTTP client for the TapirusDB SQL, vector and GraphRAG daemon APIs
🔗 https://github.com/tapiruslab/TapirusDB
A GraphRAG system can produce the correct answer using the wrong evidence. GraphRAGProv tracks which extracted facts and relationships actually contributed to an answer. Across 400 research cases, that visibility exposed errors final-answer scoring could miss.
arxiv.org/abs/2610.37237
arxiv.org/abs/2610.37237
GraphRAGProv: GraphRAG Meets How-Provenance
GraphRAG systems often use knowledge graphs to retrieve relevant context for an LLM that produces the final answer. That makes answers more inscrutable and therefore less appealing for domains where…
arxiv.org
November 7, 2026 at 5:00 AM
A GraphRAG system can produce the correct answer using the wrong evidence. GraphRAGProv tracks which extracted facts and relationships actually contributed to an answer. Across 400 research cases, that visibility exposed errors final-answer scoring could miss.
arxiv.org/abs/2610.37237
arxiv.org/abs/2610.37237
Jie Fu, Yuan Hong, Yue Ning, Wendy Hui Wang: Differentially Private GraphRAG: Protecting Relation Connectivity and Semantics https://arxiv.org/abs/2611.09658 https://arxiv.org/pdf/2611.09658 https://arxiv.org/html/2611.09658
November 9, 2026 at 6:39 AM
Jie Fu, Yuan Hong, Yue Ning, Wendy Hui Wang: Differentially Private GraphRAG: Protecting Relation Connectivity and Semantics https://arxiv.org/abs/2611.09658 https://arxiv.org/pdf/2611.09658 https://arxiv.org/html/2611.09658
Day 7/60 of Applied AI Engineering covers Advanced RAG Optimization: Parent Document retrieval, HyDE, GraphRAG integration, RAGAS metrics, and HNSW vs IVF vector indexing.
November 9, 2026 at 11:24 AM
Day 7/60 of Applied AI Engineering covers Advanced RAG Optimization: Parent Document retrieval, HyDE, GraphRAG integration, RAGAS metrics, and HNSW vs IVF vector indexing.
Job ID: 29279/2026
Extract: Research Technologist role in integrating biostatistics with Knowledge Grounded GraphRAG for clinical evidence verification using Python, statistics, NLP, and machine learning libraries.
Extract: Research Technologist role in integrating biostatistics with Knowledge Grounded GraphRAG for clinical evidence verification using Python, statistics, NLP, and machine learning libraries.
November 8, 2026 at 5:59 PM
Job ID: 29279/2026
Extract: Research Technologist role in integrating biostatistics with Knowledge Grounded GraphRAG for clinical evidence verification using Python, statistics, NLP, and machine learning libraries.
Extract: Research Technologist role in integrating biostatistics with Knowledge Grounded GraphRAG for clinical evidence verification using Python, statistics, NLP, and machine learning libraries.
Rosario Napoli, Antonio Celesti, Massimo Villari, Maria Fazio: Typed-Centrality Grounding for Agentic GraphRAG: A Symbolic Approach for Agentic Reasoning https://arxiv.org/abs/2611.09414 https://arxiv.org/pdf/2611.09414 https://arxiv.org/html/2611.09414
November 9, 2026 at 6:39 AM
Rosario Napoli, Antonio Celesti, Massimo Villari, Maria Fazio: Typed-Centrality Grounding for Agentic GraphRAG: A Symbolic Approach for Agentic Reasoning https://arxiv.org/abs/2611.09414 https://arxiv.org/pdf/2611.09414 https://arxiv.org/html/2611.09414
Article examines node identity issues in GraphRAG, including cases where distinct documents are merged in a graph without clear indication.
November 5, 2026 at 6:55 PM
Article examines node identity issues in GraphRAG, including cases where distinct documents are merged in a graph without clear indication.
Building Open Intelligence Infrastructure: GraphRAG, Neo4j, and Decentralized GPUs on Nosana #nosana
Building Open Intelligence Infrastructure: GraphRAG, Neo4j, and Decentralized GPUs on Nosana
hackernoon.com
November 4, 2026 at 7:32 AM
Building Open Intelligence Infrastructure: GraphRAG, Neo4j, and Decentralized GPUs on Nosana #nosana
The graph you built on one machine is invisible to the assistant you use on another. One config line fixes that: chaoscypher mount serves a .ccx package over MCP, citations included. https://chaoscypher.com/blog/build-once-mount-anywhere #GraphRAG #selfhosted
November 6, 2026 at 2:43 PM
The graph you built on one machine is invisible to the assistant you use on another. One config line fixes that: chaoscypher mount serves a .ccx package over MCP, citations included. https://chaoscypher.com/blog/build-once-mount-anywhere #GraphRAG #selfhosted
Most GraphRAG schemas live inside prompts or Python dictionaries. Neo4j's open ontology spec moves them into versioned YAML with JSON Schema validation and JVM, TypeScript, and Go support. Early, but a useful step toward making extraction schemas reviewable.
github.com/neo4j/ontolo...
github.com/neo4j/ontolo...
GitHub - neo4j/ontology-graph-spec: Neo4j ontologies format with libraries for JVM, JS/TS and Go.
Neo4j ontologies format with libraries for JVM, JS/TS and Go. - neo4j/ontology-graph-spec
github.com
November 10, 2026 at 12:00 AM
Most GraphRAG schemas live inside prompts or Python dictionaries. Neo4j's open ontology spec moves them into versioned YAML with JSON Schema validation and JVM, TypeScript, and Go support. Early, but a useful step toward making extraction schemas reviewable.
github.com/neo4j/ontolo...
github.com/neo4j/ontolo...
Before picking RAPTOR (tree of chunks/summaries), GraphRAG (entity-relation graph), or HippoRAG (associative memory), check: Does your data have hierarchy? Need entity links? Questions spanning documents? How should retrieval combine the info?
November 8, 2026 at 3:32 PM
Before picking RAPTOR (tree of chunks/summaries), GraphRAG (entity-relation graph), or HippoRAG (associative memory), check: Does your data have hierarchy? Need entity links? Questions spanning documents? How should retrieval combine the info?
RepoGraph turns any GitHub repo into a knowledge graph for tracing dependencies and visualizing architecture via GraphRAG and Gemini. Run locally with docker compose up.
November 5, 2026 at 3:33 PM
RepoGraph turns any GitHub repo into a knowledge graph for tracing dependencies and visualizing architecture via GraphRAG and Gemini. Run locally with docker compose up.
Opinion: entity nodes in a knowledge graph should function as caches, not sources of truth. A GraphRAG SDK now stores each chunk's text on the mention edge so deleting a document removes only its contribution.
November 6, 2026 at 4:19 PM
Opinion: entity nodes in a knowledge graph should function as caches, not sources of truth. A GraphRAG SDK now stores each chunk's text on the mention edge so deleting a document removes only its contribution.