# OptoGPT: A Foundation Model for Inverse Design in Optical Multilayer Thin Film Structures

arXiv: https://arxiv.org/abs/2304.10294 · HTML: https://mlsanity.com/paper/2304.10294/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- Builds on 11 of its 53 references that are in the map.
- First posted on arXiv 20 Apr 2023.

## Builds on (most cited first, 11 of 11)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale](https://mlsanity.com/paper/2010.11929/) (2020)
- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [On the Opportunities and Risks of Foundation Models](https://mlsanity.com/paper/2108.07258/) (2021)
- [The Curious Case of Neural Text Degeneration](https://mlsanity.com/paper/1904.09751/) (2019)
- [PaLM-E: An Embodied Multimodal Language Model](https://mlsanity.com/paper/2303.03378/) (2023)
- [A Generalist Agent](https://mlsanity.com/paper/2205.06175/) (2022)
- [Galactica: A Large Language Model for Science](https://mlsanity.com/paper/2211.09085/) (2022)
- [Foundation Models for Decision Making: Problems, Methods, and Opportunities](https://mlsanity.com/paper/2303.04129/) (2023)
- [Global optimization of dielectric metasurfaces using a physics-driven neural network](https://mlsanity.com/paper/1906.04157/) (2019)

## Built on by (most cited first, 13 of 13)

- [A multi-agentic framework for real-time, autonomous freeform metasurface design](https://mlsanity.com/paper/2503.20479/) (2025)
- [Learning Electromagnetic Metamaterial Physics With ChatGPT](https://mlsanity.com/paper/2404.15458/) (2024)
- [Foundation Models for Scientific Discovery: From Paradigm Enhancement to Paradigm Transition](https://mlsanity.com/paper/2510.15280/) (2025)
- [A Self-Evolving Agentic Framework for Metasurface Inverse Design](https://mlsanity.com/paper/2604.01480/) (2026)
- [Data driven approaches in nanophotonics: A review of AI-enabled metadevices](https://mlsanity.com/paper/2510.00283/) (2025)
- [OL-Transformer: A Fast and Universal Surrogate Simulator for Optical Multilayer Thin Film Structures](https://mlsanity.com/paper/2305.11984/) (2023)
- [CoSP: Reconfigurable Multi-State Metamaterial Inverse Design via Contrastive Pretrained Large Language Model](https://mlsanity.com/paper/2511.16135/) (2025)
- [MOCLIP: A Foundation Model for Large-Scale Nanophotonic Inverse Design](https://mlsanity.com/paper/2511.18980/) (2025)
- [Inverse Design of Optical Multilayer Thin Films using Robust Masked Diffusion Models](https://mlsanity.com/paper/2604.01106/) (2026)
- [PRISM: Position-encoded Regressive Inverse Spectral Model for Multilayer Thin-Film Design](https://mlsanity.com/paper/2605.26502/) (2026)
- [Interpretable inverse design of optical multilayer thin films based on extended neural adjoint and regression activation mapping](https://mlsanity.com/paper/2507.18644/) (2025)
- [VortexChat: An agentic framework for autonomous multi-objective integrated photonic design](https://mlsanity.com/paper/2608.20688/) (2026)
- [Towards a universal meta-optics solver via large language models](https://mlsanity.com/paper/2608.26417/) (2026)

## Abstract (arXiv)

Optical multilayer thin film structures have been widely used in numerous photonic applications. However, existing inverse design methods have many drawbacks because they either fail to quickly adapt to different design targets, or are difficult to suit for different types of structures, e.g., designing for different materials at each layer. These methods also cannot accommodate versatile design situations under different angles and polarizations. In addition, how to benefit practical fabrications and manufacturing has not been extensively considered yet. In this work, we introduce OptoGPT (Opto Generative Pretrained Transformer), a decoder-only transformer, to solve all these drawbacks and issues simultaneously.