2026-05-26原文

Multi-Persona Debate System for Automated Scientific Hypothesis Generation

This paper presents the Multi-Persona Debate System (MPDS), a literature-grounded framework that automates scientific hypothesis generation by combining retrieval, long-context LLM reasoning, corpus-driven persona induction, and structured multi-agent debate. Evaluated on battery materials design, MPDS constructs literature snapshots of up to 500 papers, conducts three-round citation-aware debate, and produces mechanistically explicit proposals. It outperforms baselines in cross-perspective integration and shows promise as a diagnostic aid for identifying workflow bottlenecks.

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Key points

MPDS automates hypothesis generation through multi-persona debate over literature snapshots, addressing fragmentation in scientific knowledge.
The system uses up to 500 papers, three rounds of citation-aware debate, and moderator synthesis with evidence traceability.
In battery materials case studies, MPDS recovered experimentally validated design logics and generated more detailed proposals than baselines.
Laboratory follow-up suggests MPDS can serve as a diagnostic tool to identify practical bottlenecks in research workflows.

Why it matters

This matters because MPDS automates hypothesis generation through multi-persona debate over literature snapshots, addressing fragmentation in scientific knowledge.

Technical impact

May affect model selection, inference cost, product capability, and evaluation benchmarks.

[2605.23917] Multi-Persona Debate System for Automated Scientific Hypothesis Generation

[Submitted on 14 Apr 2026]

Title:Multi-Persona Debate System for Automated Scientific Hypothesis Generation

View a PDF of the paper titled Multi-Persona Debate System for Automated Scientific Hypothesis Generation, by Jaeha Oh and 4 other authors

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Abstract:Modern scientific discovery is bottlenecked not by data scarcity, but by the inability to synthesize fragmented knowledge into actionable hypotheses. This challenge is especially acute in battery materials research, where electrochemical performance, interfacial behavior, and manufacturing feasibility must be optimized simultaneously. Here, we present the Multi-Persona Debate System (MPDS), a literature-grounded framework for automated scientific hypothesis generation that combines literature retrieval, long-context large language model reasoning, corpus-driven persona induction, and structured multi-agent debate. MPDS constructs literature snapshots of up to 500 papers, grounds agents in role-specific evidence pools, and conducts a three-round citation-aware debate followed by moderator synthesis, enabling negotiation between personas while preserving evidence traceability. We evaluate MPDS using a temporally controlled protocol excluding direct access to target papers, including two held-out battery-materials case studies and a blinded comparison across 30 matched cases. In sodium-ion anode and all-solid-state battery cathode design tasks, MPDS recovered design logics aligned with experimentally validated solution spaces and generated more mechanistically explicit, process-aware proposals than simpler baselines. To assess the impact of personas and debate, we introduce Integrative Hypothesis Quality scoring. In ablation studies, MPDS achieved the highest mean score among five conditions, with its largest advantage in cross-perspective integration. A laboratory follow-up suggests utility as a diagnostic aid for identifying practical bottlenecks in workflows. These results indicate that structured debate over literature snapshots improves hypothesis formation under coupled engineering constraints and provides a reusable workflow for text-intensive scientific discovery.

Comments: 31 pages with 7 main figures, 4 supplementary figures and 1 supplementary table

Subjects:

Computation and Language (cs.CL)

Cite as: arXiv:2605.23917 [cs.CL]

(or arXiv:2605.23917v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2605.23917

arXiv-issued DOI via DataCite

Submission history

From: Ju Li [view email] [v1] Tue, 14 Apr 2026 16:57:12 UTC (1,605 KB)

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View a PDF of the paper titled Multi-Persona Debate System for Automated Scientific Hypothesis Generation, by Jaeha Oh and 4 other authors

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