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Evaluating AI-based Scientific Knowledge Synthesis with Epidemiological Systematic Reviews

AgentSLR evaluates LLMs on epidemiological systematic reviews, revealing sub-task specialization, poor structured extraction (F1 < 0.67), and unreliable unsupervised deployment.

Shreyansh Padarha, Ryan Othniel Kearns, Tristan M Naidoo, Lingyi Yang and 12 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 9 on Hugging Face · Code ★ 25

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17/20 AI panelreviewers recommend it

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 8/10
strict 4/5
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Faithful Embeddings of Irregular and Asynchronous Data for Online Log-NCDEs

Online Log-NCDEs use a continuous, injective increment-based embedding to build log-signatures directly from irregular asynchronous observations without interpolation, achieving universal approximation with online efficiency and robustness.

Benjamin Walker, Alexandre Bloch, Lingyi Yang, Sam Morley and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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11/20 AI panelreviewers recommend it

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AI panel: 11 of 20 reviewers recommend it
lenient 2/5
medium 7/10
strict 2/5