Hierarchical Deep Research with Local-Web RAG: Toward Automated System-Level Materials Discovery

• URL: http://arxiv.org/abs/2511.18303v1
• Date: Sun, 23 Nov 2025 05:57:42 GMT
• Title: Hierarchical Deep Research with Local-Web RAG: Toward Automated System-Level Materials Discovery
• Authors: Rui Ding, Rodrigo Pires Ferreira, Yuxin Chen, Junhong Chen,
• Abstract summary: Long-horizon, hierarchical deep research (DR) agent designed for complex materials and device discovery problems.<n>Our framework instantiates a locally deployable DR instance that integrates local retrieval-augmented generation with large language model reasoners.<n>We systematically evaluate across 27 nanomaterials/device topics using a large language model (LLM)-as-judge with five web-enabled state-of-the-art models as jurors.
• Score: 16.491889842339617
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We present a long-horizon, hierarchical deep research (DR) agent designed for complex materials and device discovery problems that exceed the scope of existing Machine Learning (ML) surrogates and closed-source commercial agents. Our framework instantiates a locally deployable DR instance that integrates local retrieval-augmented generation with large language model reasoners, enhanced by a Deep Tree of Research (DToR) mechanism that adaptively expands and prunes research branches to maximize coverage, depth, and coherence. We systematically evaluate across 27 nanomaterials/device topics using a large language model (LLM)-as-judge rubric with five web-enabled state-of-the-art models as jurors. In addition, we conduct dry-lab validations on five representative tasks, where human experts use domain simulations (e.g., density functional theory, DFT) to verify whether DR-agent proposals are actionable. Results show that our DR agent produces reports with quality comparable to--and often exceeding--those of commercial systems (ChatGPT-5-thinking/o3/o4-mini-high Deep Research) at a substantially lower cost, while enabling on-prem integration with local data and tools.

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