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GLOW@ISWC 2026 : Graph-enhanced LLMs for trustwOrthy Web data management

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Link: https://glow-workshop.github.io/iswc2026/
 
When Oct 25, 2026 - Oct 26, 2026
Where Bari, Italy
Submission Deadline Jul 14, 2026
Notification Due Aug 11, 2026
Categories    artificial intelligence   computer science   data management   internet
 

Call For Papers

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GLOW Workshop @ ISWC'26 - Call for Papers
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2nd Workshop on Graph-enhanced LLMs for trustwOrthy Web data management (GLOW)

October 25-26 2026, held as part of the The International Semantic Web Conference (ISWC'26)

https://glow-workshop.github.io/iswc2026/

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** Workshop Description **

Large Language Models (LLMs) are increasingly used in Web and data management applications, but issues such as hallucinations, bias, and limited explainability still affect their reliability. Graph-based representations, including knowledge graphs and property graphs, can help address these challenges by providing structured knowledge that supports validation and reasoning.

The Graph-Enhanced LLMs for Trustworthy Web Data Management (GLOW) workshop explores how graph and Semantic Web technologies can improve the trustworthiness of LLM-based systems, fostering research at the intersection of Semantic Web, Knowledge Graphs, and LLM-driven data-centric AI.

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

- Detection and mitigation of hallucinations, bias, and misinformation in LLMs using graph-based techniques.
- 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.
- Agentic AI for structured reasoning and decision-making over graph-based knowledge.
- Semantic Web standards for grounding and verifying LLM-generated outputs.
- Ontology-based reasoning and neuro-symbolic approaches for trustworthy LLM-driven systems.
- Integration of Knowledge Graphs for retrieval-augmented generation and fact-checking.
- Applications of LLMs combined with Semantic Web technologies for reliable Web-scale data management, scientific knowledge representation, and enterprise knowledge graphs.
- Evaluation benchmarks and metrics for reliability and trustworthiness in graph-enhanced LLMs.

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** Paper Submission Procedure **

We invite research, industry, application contributions, and software demonstration submissions. Regular papers presenting original work are solicited. Moreover, discussion papers containing descriptions of results already published are also welcomed. There are two submission formats:

- Regular papers (up to 12 pages + references). Original research works. Regular papers must be original and not simultaneously submitted to another journal or conference.
- Discussion papers (up to 8 pages + references). Results and ideas of interest to the workshop audience, including extended abstracts of recent authors’ publications, papers currently under submission, position papers, system and application descriptions, and presentations of preliminary results.

Paper selection will be based on originality, clarity, and technical quality. Submissions of papers must be in English, in PDF format, and formatted following the new CEUR-ART 1-column style, which is the style requested for the camera-ready preparation (Overleaf template). Accepted papers will be included in the proceedings. Proceedings will be published on CEUR-WS.org and indexed in Scopus. After acceptance, authors are required to re-submit the final PDF.

Submission Link: all papers must be submitted using EasyChair through the following link: https://easychair.org/conferences/?conf=glowiswc26

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** Important dates **

- Submission deadline: July 14, 2026 (AoE)
- Author notification: August 11, 2026 (AoE)
- Camera-ready deadline: TBD (AoE)
- Workshop: October 25-26, 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

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