HERMES: a multi-agent framework for structured knowledge extraction from ultra-long documents in geoscience
Summary
HERMES is a scalable multi-agent framework for extracting structured knowledge from ultra-long scientific documents in geoscience, achieving high accuracy and sixfold efficiency improvement over manual methods.
View Cached Full Text
Cached at: 08/17/26, 09:52 AM
# HERMES: a multi-agent framework for structured knowledge extraction from ultra-long documents in geoscience Source: [https://arxiv.org/abs/2608.14055](https://arxiv.org/abs/2608.14055) Authors:[Ziqi Song](https://arxiv.org/search/cs?searchtype=author&query=Song,+Z),[Zongyuan Xiang](https://arxiv.org/search/cs?searchtype=author&query=Xiang,+Z),[James G\. Ogg](https://arxiv.org/search/cs?searchtype=author&query=Ogg,+J+G),[Bruce S\. Lieberman](https://arxiv.org/search/cs?searchtype=author&query=Lieberman,+B+S),[Gabi Ogg](https://arxiv.org/search/cs?searchtype=author&query=Ogg,+G),[Natalia López Carranza](https://arxiv.org/search/cs?searchtype=author&query=Carranza,+N+L),[Wen Du](https://arxiv.org/search/cs?searchtype=author&query=Du,+W),[Yufei Ye](https://arxiv.org/search/cs?searchtype=author&query=Ye,+Y),[Shuan Li](https://arxiv.org/search/cs?searchtype=author&query=Li,+S),[Zhong Peng](https://arxiv.org/search/cs?searchtype=author&query=Peng,+Z),[Shaoqi Yu](https://arxiv.org/search/cs?searchtype=author&query=Yu,+S),[Juye Wei](https://arxiv.org/search/cs?searchtype=author&query=Wei,+J),[Ying Zhou](https://arxiv.org/search/cs?searchtype=author&query=Zhou,+Y),[Jieping Ye](https://arxiv.org/search/cs?searchtype=author&query=Ye,+J),[Jiang Yang](https://arxiv.org/search/cs?searchtype=author&query=Yang,+J) [View PDF](https://arxiv.org/pdf/2608.14055) > Abstract:Authoritative scientific knowledge in geoscience remains largely trapped in legacy monographs and historical literature, where unstructured text and complex layouts hinder computational access\. We introduce HERMES, a scalable multi\-agent framework that extracts structured data from ultra\-long scientific documents\. Using a coordinating large language model, HERMES integrates domain constraints, validation rules and evidence tracing within a unified document\-level extraction process that incorporates parsed text, tables, figures and captions\. Applied to the 55\-volume Treatise on Invertebrate Paleontology, the system produced a structured database of 32,277 fossil taxonomic entities and 451,878 attributes, released online at[this https URL](https://treatise.geolex.org/)\. Extraction performance remained stable across fossil groups \(average F1 scores of approximately 0\.90 for entities and 0\.91 for attributes\), improving per\-volume efficiency approximately sixfold relative to the tested fully manual baseline\. Evaluation in palaeomagnetism and geochemistry, conducted without additional model training, demonstrated transfer across distinct geoscience domains\. This work provides a practical pathway to transform historical scientific literature into FAIR\-oriented structured data, offering a sustainable infrastructure for data\-intensive disciplines and large\-scale knowledge integration\. ## Submission history From: Zongyuan Xiang \[[view email](https://arxiv.org/show-email/1754d96a/2608.14055)\] **\[v1\]**Fri, 14 Aug 2026 07:59:58 UTC \(3,857 KB\)
Similar Articles
NousResearch/hermes-agent
Hermes Agent is an open-source, self-improving AI agent framework by Nous Research featuring a closed learning loop, cross-platform deployment, and compatibility with hundreds of LLMs. It provides a terminal interface, persistent memory, automated scheduling, and research-ready tooling for scaling AI workflows.
@tavilyai: Hermes Agent is a glimpse into where agents are heading. It learns from every session, writes its own skills, and build…
Hermes Agent by Nous Research is an open-source, self-improving autonomous agent that learns from every session and builds persistent memory over time. Tavily integrates as its web search backend to improve search quality and prevent bad data from compounding into the agent's long-term memory and skills.
@rlaope: Want to level up your (@NousResearch) Hermes Agent's intelligence? Meet oh-my-hermes. It’s the ultimate all-in-one suit…
oh-my-hermes is an all-in-one suite for Hermes Agent that adds memory management, coding orchestration, wiki building, and more, simplifying agent workflows and reducing the need for multiple plugins.
@rlaope: hermes agent memory system and oh-my-hermes agent memory system L0~L2 (hermes-agent fure) L2~L3 and pruning, dreaming, …
Oh-my-hermes (OMH) is a tool that enhances Hermes Agent with a stronger operating layer, adding planning, research, creation, coding handoffs, operations, and project memory with explicit evidence boundaries. It is open-source and installable with a single command.
@rayoo_eth: Hermes' Profile is a lifesaver for context management. When Hermes runs for a long time, the coding Agent, research Agent, and personal affairs Agent all share the same memory and configuration. This leads to research notes mixing into coding tasks, work rules intruding into personal conversations, and cron jobs crammed into a single document.
Hermes' Profile feature allows different AI agents (e.g., coding, research, personal affairs) to have independent configuration, memory, and tasks, achieving identity isolation and solving context confusion in long-running operations.