mlsanityData to 14 Oct 2026

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

arXiv 2507.10522 ↗First posted 14 Jul 2025cs.AI cs.CL cs.MAcited by 1

On the map: LLM agents and tool use → Web, search, and research agents

Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Placed in Web, search, and research agents, one of 16 directions in LLM agents and tool use. Builds on 14 of its 18 references that are in the map. First posted on arXiv 14 Jul 2025.

Builds on

14 of 18 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024Chain of Ideas: Revolutionizing Research Via Novel Idea Development with LLM Agents17 Oct
  2. 2024Language agents achieve superhuman synthesis of scientific knowledge10 Sep
  3. 2023PaperQA: Retrieval-Augmented Generative Agent for Scientific Research8 Dec

Other references · 11

  1. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,297
  2. 2024The AI Scientist: Towards Fully Automated Open-Ended Scientific Discoverycited by 1,071
  3. 2021Retrieval Augmentation Reduces Hallucination in Conversationcited by 692
  4. 2024Large Legal Fictions: Profiling Legal Hallucinations in Large Language Modelscited by 150
  5. 2024Nova: An Iterative Planning and Search Approach to Enhance Novelty and Diversity of LLM Generated Ideascited by 57
  6. 2024IdeaSynth: Iterative Research Idea Development Through Evolving and Composing Idea Facets with Literature-Grounded Feedbackcited by 42
  7. 2024Human-LLM Compound System for Scientific Ideation through Facet Recombination and Novelty Evaluationcited by 41
  8. 2025YESciEval: Robust LLM-as-a-Judge for Scientific Question Answeringcited by 16
  9. 2024LLMs4Synthesis: Leveraging Large Language Models for Scientific Synthesiscited by 13
  10. 2024ORKG ASK: a Neuro-symbolic Scholarly Search and Exploration Systemcited by 3
  11. 2024Semantic Navigation for AI-assisted Ideationcited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

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Close in wording, no citation either way

  1. 2025Deep Research: A Survey of Autonomous Research Agents
  2. 2026DeepResearch-9K: A Challenging Benchmark Dataset of Deep-Research Agent
  3. 2025DeepResearchGym: A Free, Transparent, and Reproducible Evaluation Sandbox for Deep Research
  4. 2026SciResearcher: Scaling Deep Research Agents for Frontier Scientific Reasoning
  5. 2025From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents
  6. 2025SQuAI: Scientific Question-Answering with Multi-Agent Retrieval-Augmented Generation
  7. 2026VecTree-RAG: An Agentic Retrieval-Augmented Generation Framework Combining Vector and Tree Retrieval for Efficiency and Accuracy
  8. 2026DeepEra: A Deep Evidence Reranking Agent for Scientific Retrieval-Augmented Generated Question Answering