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bioRxiv · 10.1101/2025.07.14.664755

DeepResearch_Eco: A Recursive Agentic Workflow for Complex Scientific Question Answering in Ecology

D'Souza, J.·Sander, E. K.·Aioanei, A.
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Abstract

We introduce DeepResearchEco, a novel agentic LLM-based system for automated scientific synthesis that supports recursive, depth- and breadth-controlled exploration of original research questions--enhancing search diversity and nuance in the retrieval of relevant scientific literature. Unlike conventional retrieval-augmented generation pipelines, DeepResearch enables user-controllable synthesis with transparent reasoning and parameter-driven configurability, facilitating high-throughput integration of domain-specific evidence while maintaining analytical rigor. Applied to 49 ecological research questions, DeepResearch achieves up to a 21-fold increase in source integration and a 14.9-fold rise in sources integrated per 1,000 words. High-parameter settings yield expert-level analytical depth and contextual diversity. Source code available at: https://github.com/sciknoworg/deep-research.

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D'Souza, J., Sander, E. K., Aioanei, A.. 2025-07-18. DeepResearch_Eco: A Recursive Agentic Workflow for Complex Scientific Question Answering in Ecology. https://doi.org/10.1101/2025.07.14.664755

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