mlsanityData to 7 Oct 2026

El Agente: An Autonomous Agent for Quantum Chemistry

arXiv 2505.02484 ↗First posted 5 May 2025cs.AI cs.LG cs.MAcited by 43

On the map: LLM agents and tool use → Medical and scientific domain agents

Abstract (arXiv)

Computational chemistry tools are widely used to study the behaviour of chemical phenomena. Yet, the complexity of these tools can make them inaccessible to non-specialists and challenging even for experts. In this work, we introduce El Agente Q, an LLM-based multi-agent system that dynamically generates and executes quantum chemistry workflows from natural language user prompts. The system is built on a novel cognitive architecture featuring a hierarchical memory framework that enables flexible task decomposition, adaptive tool selection, post-analysis, and autonomous file handling and submission. El Agente Q is benchmarked on six university-level course exercises and two case studies, demonstrating robust problem-solving performance (averaging >87% task success) and adaptive error handling through in situ debugging. It also supports longer-term, multi-step task execution for more complex workflows, while maintaining transparency through detailed action trace logs. Together, these capabilities lay the foundation for increasingly autonomous and accessible quantum chemistry.

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use. Builds on 55 of its 171 references that are in the map. First posted on arXiv 5 May 2025.

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55 of 171 references.

Closest ancestors · 4

Same direction, newest first

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Other references · 51

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50 most cited of 51 All 51 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 16; 2026: 27.

43 papers.

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  11. 2025Towards autonomous quantum physics research using LLM agents with access to intelligent toolscited by 7
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