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Scientific Discovery

18 items

RESEARCHarXiv CS.CL·14d ago

Multi-Persona Debate System for Automated Scientific Hypothesis Generation

The Multi-Persona Debate System (MPDS) is a literature-grounded framework designed to automate scientific hypothesis generation, specifically addressing the challenge of synthesizing fragmented knowledge in areas like battery materials research. It combines literature retrieval, large language model reasoning, and multi-agent debate to enable negotiation between personas while preserving evidence traceability.

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RESEARCHarXiv CS.CL·4/16/2026

Mathematical Reasoning Enhanced LLM for Formula Derivation: A Case Study on Fiber NLI Modellin

This research introduces a mathematical reasoning-enhanced generative AI approach for deriving optical communication formulas, specifically for fiber nonlinear interference modelling. By guiding an LLM with structured prompts, the study successfully reconstructed known expressions and derived a novel approximation, demonstrating both physical consistency and practical accuracy.

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RESEARCHarXiv CS.AI·22d ago

NIMO Controller: a self-driving laboratory orchestrator based on the Model Context Protocol

This paper introduces the NIMO Controller, a self-driving laboratory orchestrator based on the Model Context Protocol (MCP), designed to enhance accessibility and accelerate scientific discovery. It provides a unified interface for both human users via visual programming and AI agents, streamlining experimental workflow design without coding.

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RESEARCHarXiv CS.LG·14d ago

LLM-AutoSciLab: Closed-Loop Scientific Discovery via Active Experimentation with LLMs

LLM-AutoSciLab proposes a closed-loop framework for scientific discovery, moving beyond static inference by actively coupling hypothesis generation with experiment selection and mechanism refinement. It iteratively suggests plausible hypotheses, selects informative experiments to distinguish or refine them, and updates its state using the resulting evidence.

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RESEARCHarXiv CS.AI·4/8/2026

PaperOrchestra: A Multi-Agent Framework for Automated AI Research Paper Writing

PaperOrchestra é um framework multiagente para escrita automatizada de artigos de pesquisa em IA, transformando materiais brutos em manuscritos LaTeX com síntese de literatura e visuais. Avaliado com o novo benchmark PaperWritingBench, ele supera significativamente as linhas de base autônomas em avaliações humanas.

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RESEARCHarXiv CS.AI·19d ago

AgentCo-op: Retrieval-Based Synthesis of Interoperable Multi-Agent Workflows

AgentCo-op is a retrieval-based synthesis framework that composes interoperable multi-agent workflows from reusable skills, tools, and external agents. It applies bounded self-guided local repair to components upon execution failure and has been demonstrated in genomics case studies to coordinate specialized agents for collaborative discovery.

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ARTICLEMIT Tech Review AI·4/21/2026

Artificial scientists

AI companies justify their existence by promising AI-enabled scientific discoveries, such as curing cancer or solving climate change. Large Language Models are already proving helpful to scientists in various tasks.

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