Multi-Agent Procedural Graph Extraction with Structural and Logical Refinement | ScienceToStartup | ScienceToStartup

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References (34)

[1]

Data-Efficient Symbolic Regression via Foundation Model Distillation

2025Wangyang Ying, Jinghan Zhang et al.

[2]

Efficient Post-Training Refinement of Latent Reasoning in Large Language Models

2025Xinyuan Wang, Dongjie Wang et al.

[3]

CT-PatchTST: Channel-Time Patch Time-Series Transformer for Long-Term Renewable Energy Forecasting

Founder's Pitch

"A multi-agent framework for extracting procedural graphs from natural language with improved structural and logical accuracy."

Agents•Score: 4•View PDF ↗

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2.5

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2.5

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Multi-Agent Procedural Graph Extraction with Structural and Logical Refinement

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References (34)

Founder's Pitch

"A multi-agent framework for extracting procedural graphs from natural language with improved structural and logical accuracy."

Commercial Viability Breakdown

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Multi-Agent Procedural Graph Extraction with Structural and Logical Refinement

BUILDER'S SANDBOX

Build This Paper

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References (34)

Founder's Pitch

"A multi-agent framework for extracting procedural graphs from natural language with improved structural and logical accuracy."

Commercial Viability Breakdown

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