{"ID":5676061,"CreatedAt":"2026-07-03T01:40:09.565152011Z","UpdatedAt":"2026-07-05T01:25:09.323207391Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2607.01584","arxiv_id":"2607.01584","title":"EO-Agents: A Three-Agent LLM Pipeline for Earth Observation Hypothesis Generation","abstract":"Large language models have recently been explored for scientific hypothesis generation, but most prior work relies on unstructured literature and free-form textual claims. We present a pipeline for Earth observation that grounds hypothesis generation directly in the NASA Earth Observation Knowledge Graph. A heterogeneous graph neural network trained on historical co-usage relations ranks candidate dataset pairings, and a three-agent LLM pipeline filters, generates, and evaluates structured research hypotheses. Applied to 1,475 NASA datasets, the system produces 160 hypotheses spanning multiple Earth-science domains, including ecohydrology, glaciology, aerosol--cloud interactions, vegetation phenology, and stratospheric chemistry. Model-predicted novel dataset pairings are rated nearly as plausible as held-out real co-usages from the literature, indicating that the pipeline surfaces scientifically coherent yet unexplored combinations. A 2*2*2 factorial experiment across GPT-5.2 and Claude Sonnet 4.6 shows that hypothesis rankings remain stable, while absolute scores depend strongly on judge identity, highlighting limitations of single-judge LLM evaluation.","short_abstract":"Large language models have recently been explored for scientific hypothesis generation, but most prior work relies on unstructured literature and free-form textual claims. We present a pipeline for Earth observation that grounds hypothesis generation directly in the NASA Earth Observation Knowledge Graph. A heterogeneo...","url_abs":"https://arxiv.org/abs/2607.01584","url_pdf":"https://arxiv.org/pdf/2607.01584v1","authors":"[\"Mahyar Ghazanfari\",\"Amin Tabrizian\",\"Armin Mehrabian\",\"Peng Wei\"]","published":"2026-07-02T01:31:18Z","proceeding":"cs.AI","tasks":"[\"cs.AI\"]","methods":"[\"Graph Neural Network\",\"Large Language Model\",\"Language Model\"]","has_code":false}