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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2505.13246 |
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| _version_ | 1866917461660532736 |
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| author | Pugliese, Roberto Kourousias, George Venier, Francesco Costa, Grazia Garlatti |
| author_facet | Pugliese, Roberto Kourousias, George Venier, Francesco Costa, Grazia Garlatti |
| contents | Purpose: This paper introduces the concept of "Agentic Publication," a novel LLM-driven framework designed to complement traditional scientific publishing by transforming papers into interactive knowledge systems that address challenges created by exponential growth in scientific literature. Design/methodology/approach: Our architecture integrates structured data (knowledge graphs, metadata) with unstructured content (text, multimedia) through retrieval-augmented generation and multi-agent verification. The system provides interfaces for humans and artificial agents, offering narrative explanations alongside machine-readable outputs. Implementation leverages vector databases for semantic search, knowledge graphs for structured reasoning, and collaborative verification agents. Findings: Our proof-of-concept demonstration showcases multilingual interaction, API accessibility, continuous knowledge flow, and structured knowledge representation. The framework enables dynamic updating of knowledge, synthesis of new findings, and customizable detail levels. Originality: The Agentic Publication represents a transformative approach to scientific communication by creating responsive knowledge synthesis systems while maintaining scientific rigor. Integrating multi-agent verification with traditional publishing pathways creates a more efficient, accessible, and collaborative research ecosystem, particularly valuable in interdisciplinary fields. Practical implications: The system is a powerful companion for researchers navigating complex knowledge landscapes, offering tailored information access across disciplines while addressing ethical considerations through automated validation, expert oversight, and transparent governance. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_13246 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Agentic publications: redesigning scientific publishing in the age of thinking large language models Pugliese, Roberto Kourousias, George Venier, Francesco Costa, Grazia Garlatti Artificial Intelligence Human-Computer Interaction Purpose: This paper introduces the concept of "Agentic Publication," a novel LLM-driven framework designed to complement traditional scientific publishing by transforming papers into interactive knowledge systems that address challenges created by exponential growth in scientific literature. Design/methodology/approach: Our architecture integrates structured data (knowledge graphs, metadata) with unstructured content (text, multimedia) through retrieval-augmented generation and multi-agent verification. The system provides interfaces for humans and artificial agents, offering narrative explanations alongside machine-readable outputs. Implementation leverages vector databases for semantic search, knowledge graphs for structured reasoning, and collaborative verification agents. Findings: Our proof-of-concept demonstration showcases multilingual interaction, API accessibility, continuous knowledge flow, and structured knowledge representation. The framework enables dynamic updating of knowledge, synthesis of new findings, and customizable detail levels. Originality: The Agentic Publication represents a transformative approach to scientific communication by creating responsive knowledge synthesis systems while maintaining scientific rigor. Integrating multi-agent verification with traditional publishing pathways creates a more efficient, accessible, and collaborative research ecosystem, particularly valuable in interdisciplinary fields. Practical implications: The system is a powerful companion for researchers navigating complex knowledge landscapes, offering tailored information access across disciplines while addressing ethical considerations through automated validation, expert oversight, and transparent governance. |
| title | Agentic publications: redesigning scientific publishing in the age of thinking large language models |
| topic | Artificial Intelligence Human-Computer Interaction |
| url | https://arxiv.org/abs/2505.13246 |