Block 1 - Google Gemini Chat Model
- Type / Role
- @n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
This n8n workflow template implements an intelligent research paper monitoring system that automatically tracks new publications in ArXiv's Artificial Intelligence category, filters them for releva...
@n8n/n8n-nodes-langchain.lmchatgooglegemini, @n8n/n8n-nodes-langchain.outputparserstructured, n8n-nodes-base.emailsend, n8n-nodes-base.stopanderror, n8n-nodes-base.scheduletrigger, n8n-nodes-base.code, n8n-nodes-base.httprequest, n8n-nodes-base.xml
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Maxim Osipovs.
Original n8n.io sourceThe system uses a three-stage pipeline architecture:
This eliminates the need to manually browse ArXiv daily while ensuring you only receive summaries of papers genuinely relevant to your research interests.
š Academic researchers tracking AI developments in their field š¼ ML practitioners and data scientists staying current with new techniques š§ AI enthusiasts who want curated, digestible research updates š¢ Technical teams needing regular competitive intelligence on emerging approaches
ā Automates daily ArXiv monitoring, saving 60+ minutes of manual research time ā Uses AI to pre-filter papers, reducing information overload by 80-90% ā Delivers structured, readable summaries instead of raw abstracts ā Fully customizable relevance criteria to match your specific interests ā Professional HTML formatting makes digests easy to scan and share ā Eliminates the risk of missing important papers in your field
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
| Workflow | Monitor AI research papers with Gemini-powered filtering and email summaries |
|---|---|
| Complexity | advanced |
| Nodes | 23 |
| Categories | Market Research, AI Summarization |
| Author | Maxim Osipovs |
| Published | 18 Oct 2025 |
Use the JSON export at /data/workflows/9859/9859.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
This n8n workflow template implements an intelligent research paper monitoring system that automatically tracks new publications in ArXiv's Artificial Intelligence category, filters them for releva...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Market Research, AI Summarization use case.