LLMs advance nanophotonics design beyond traditional deep learning

A review explores the application of Large Language Models (LLMs) in nanophotonics, moving beyond traditional deep learning methods. LLMs are being integrated into numerical nanophotonic workflows to provide semantic interfaces, generate code, and orchestrate simulations. The paper categorizes LLM applications into two modes: using them as surrogate models for structure-spectrum mapping and as agentic systems for code generation and optimization. The review also touches upon LLM uses in materials science and wireless communications, envisioning future multimodal foundation models with physical perception capabilities that could act as active collaborators in scientific discovery. AI

IMPACT LLMs are poised to become active collaborators in scientific discovery, moving beyond passive tools in fields like nanophotonics.

RANK_REASON The item is a review paper discussing the application of LLMs in a specific scientific field. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

• Agentic Systems
• artificial intelligence
• deep learning
• foundation model
• Large Language Models
• materials science
• Nanophotonics
• Neural Networks
• surrogate models
• Transformer-based Models
• wireless communication

• paper
• model release

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