SciToolAgent: A Knowledge Graph-Driven Scientific Agent for Multi-Tool Integration
Scientific research increasingly relies on specialized computational tools, yet effectively utilizing these tools demands substantial domain expertise. While Large Language Models (LLMs) show promise in tool automation, they struggle to seamlessly integrate and orchestrate multiple tools for complex scientific workflows. Here, we present SciToolAgent, an LLM-powered agent that automates hundreds of scientific tools across biology, chemistry, and materials science. At its core, SciToolAgent leverages a scientific tool knowledge graph that enables intelligent tool selection and execution through graph-based retrieval-augmented generation. The agent also incorporates a comprehensive safety-checking module to ensure responsible and ethical tool usage. Extensive evaluations on a curated benchmark demonstrate that SciToolAgent significantly outperforms existing approaches. Case studies in protein engineering, chemical reactivity prediction, chemical synthesis, and metal-organic framework screening further demonstrate SciToolAgent's capability to automate complex scientific workflows, making advanced research tools accessible to both experts and non-experts.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Agentic Publications: An LLM-Driven Framework for Interactive Scientific Publishing, Supplementing Traditional Papers with AI-Powered Knowledge Systems
The exponential growth of scientific literature presents significant challenges for researchers navigating the complex knowledge landscape. We propose "Agentic Publications", a novel LLM-driven framework complementing tr…
Knowledge GraphsRetrieval-augmented GenerationEl Agente Gráfico: Structured Execution Graphs for Scientific Agents
Large language models (LLMs) are increasingly used to automate scientific workflows, yet their integration with heterogeneous computational tools remains ad hoc and fragile. Current agentic approaches often rely on unstr…
Knowledge GraphsThe Discovery Engine: A Framework for AI-Driven Synthesis and Navigation of Scientific Knowledge Landscapes
The prevailing model for disseminating scientific knowledge relies on individual publications dispersed across numerous journals and archives. This legacy system is ill suited to the recent exponential proliferation of p…
Knowledge GraphsNavigateRewarding Explainability in Drug Repurposing with Knowledge Graphs
Knowledge graphs (KGs) are powerful tools for modelling complex, multi-relational data and supporting hypothesis generation, particularly in applications like drug repurposing. However, for predictive methods to gain acc…
Reinforcement LearningKnowledge GraphsLink PredictionAgents-K1: Towards Agent-native Knowledge Orchestration
Current LLM-based research agents have advanced through agent orchestration, yet largely overlook scientific knowledge orchestration. Existing works often reduce papers to abstracts, surface mentions, and flat \texttt{ci…
Information ExtractionKnowledge Graphs