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Related Articles from SNS
PIPE-Cypher: Automatic Enterprise Benchmark Generation for Text-to-Cypher Systems
arXiv:2606.08481v1 Announce Type: new Abstract: Enterprise property graphs vary widely in schema structure, internal terminology, domain assumptions, governance constraints, and user interaction patterns. A deployment-relevant Text2Cypher benchmark therefore reflects the questions users and agents actually ask of that graph. Creating such a benchmark is difficult because schemas and values are unique, and graph structure changes over time.
CYGNET: Cypher Gate for Neural Execution Triage and Cost Containment
new Abstract: Language models acting as agents over knowledge graphs generate Cypher queries that fail structurally (crashing at the database) or semantically (executing but returning wrong results). We place a pre-execution gate between query generation and a production Neo4j database. The gate validates structure through a four-backend chain culminating in execution against a mirror graph at 5.6 ms median latency.
NGDBench: Towards Neural Graph Data Management
Announce Type: replace Abstract: Data critical to real-world decision-making is increasingly found within organizations. Such data is heterogeneous, constantly evolving, and only imperfectly captured. However, current data management systems remain largely passive, retrieving what is explicitly stored while offering limited support for uncovering implicit structure or reasoning under noise, incompleteness, and continuous updates.
2027 recruiting class rankings: Miami surges into ...
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Stepwise Reasoning Enhancement for LLMs via External Subgraph Generation
Announce Type: new Abstract: Large language models have shown strong performance in natural language generation and downstream reasoning tasks, but they still struggle with logical consistency, factual grounding, and interpretability in complex multi-step reasoning. To address these limitations, this paper proposes SGR, a stepwise reasoning enhancement framework that integrates large language models with external knowledge graphs through query-relevant subgraph generation. Given an input...
King Charles shares emotional glimpse into late Queen’s final days in Balmoral tribute
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Knowledge Graphs as the Missing Data Layer for LLM-Based Industrial Asset Operations
Announce Type: replace Abstract: LLM-based agents for industrial asset operations show limited accuracy when reasoning over flat document stores. AssetOpsBench (KDD 2026) establishes that GPT-4 agents achieve 65% on 139 industrial maintenance scenarios, and compares LLM orchestration paradigms (Agent-As-Tool vs. Plan-Execute) on a fixed data layer. We ask the orthogonal question: how much does the data model behind the tools matter?
Ask Safely: Privacy-Aware LLM Query Generation for Knowledge Graphs
Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly used to query knowledge graphs (KGs) due to their strong semantic understanding and extrapolation capabilities compared to traditional approaches. However, when KGs contain sensitive information and users lack local access to generative models, privacy becomes a critical concern. To address this issue, we propose a privacy-aware query generation approach for KGs.
London Pride 2026: Parade route, stage line-ups and performers in full
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Neo4j plots Palantir alternative with GraphAware acquisition
"The no-kill-switch kind of thing? It's increasingly becoming a requirement," says Neo4j CEO Emil Eifrem. This is one of the reasons behind the company's decision to buy GraphAware, an intelligence analysis software platform built on the graph database, which is positioning itself as an alternative to Palantir, the controversial US spy-tech biz.