GLOW@WWW'26: Graph-enhanced LLMs for trustwOrthy Web data management The ACM Web Conference (WWW ’26) - GLOW Workshop Dubai, UAE, April 13-14, 2026

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Call for Papers

1st Workshop on Graph-enhanced LLMs for trustwOrthy Web data management (GLOW)

April 13-14 2026, held as part of the ACM Web Conference (WWW'26)

https://glow-workshop.github.io/www2026/

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Workshop Description 

The recent growth of LLMs has expanded possibilities in data management, enabling powerful natural language access, reasoning, and decision support. However, reliability and trustworthiness remain major challenges when deploying LLMs in sensitive domains. Graph-based representations of knowledge and data (e.g., knowledge graphs and property graphs) provide a promising avenue to address these challenges.

LLMs generate fluent responses but often struggle with factuality, bias, hallucinations, and a lack of explainability. Graphs, on the other hand, provide structured, interconnected representations that can serve as grounding and validation layers for LLM-based systems. Exploring the synergies between LLMs and graphs is critical to building data-driven applications where correctness and accountability are necessary.

We invite submissions that address, but are not limited to, the following themes:

• Graph-based retrieval and reasoning for verifiable LLM responses.
• Detection and mitigation of hallucinations, bias, and misinformation in LLMs using graph-based techniques.
• Graph databases and LLMs for explainability, accountability, and provenance in data management.
• Property graphs as a foundation for profiling, reliability, and LLM-grounded reasoning.
• Querying property graphs with natural language interfaces powered by LLMs.
• LLMs as assistants for constructing and validating reliable knowledge graphs.
• Graph-based prompting and retrieval-augmented generation (RAG) strategies for reliability and robustness.
• Evaluation benchmarks and metrics for reliability and trustworthiness in graph-enhanced LLMs.
• Applications of graph-enhanced LLMs in domains such as Web data management, scientific knowledge, and enterprise data.
• Agentic AI for structured reasoning and decision-making over graph-based knowledge.

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Paper Submission Procedure

• Originality: submissions must be original (i.e., not submitted to or accepted to other venues); however, we welcome extensions or revisions of published papers. Also, we encourage submitting early-stage work or position papers.
• Anonymity: submissions are not required to be anonymous (single-blind).
• Paper Formatting: submissions must be written in English and submitted in PDF format. Short papers may be up to 4 pages in length, plus up to 4 additional pages for references and clearly marked appendices. Full papers may be up to 8 pages in length, plus up to 2 additional pages for references and clearly marked appendices. All submissions must follow the ACM SIG Proceedings Templates. Suitable LaTeX, Word, and Overleaf templates are available at: https://www.acm.org/publications/proceedings-template
• Submission Link: all papers must be submitted using EasyChair through the following link: https://easychair.org/my2/conference?conf=glowwww26

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Important dates

- Submission deadline: December 18, 2025 (AoE)

- Author notification: January 13, 2026 (AoE)

- Camera-ready deadline: February 2, 2026 (AoE)

- Workshop: April 13-14, 2026

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Organization

• Gianluca Bonifazi, Marche Polytechnic University
• Stefano Cirillo, University of Salerno
• Eliana Pastor, Polytechnic University of Turin
• Luca Virgili, Marche Polytechnic University