6 citations · 15 across the 12 of their papers we have counts for
12 papers
Mathematical Reasoning Enhanced LLM for Formula Derivation: A Case Study on Fiber NLI Modellin
Yao Zhang, Yuchen Song, Xiao Luo +4
Recent advances in large language models (LLMs) have demonstrated strong capabilities in code generation and text synthesis, yet their potential for symbolic physical reasoning in…
Large language models for optical network O&M: Agent-embedded workflow for automation
Shengnan Li, Yidi Wang, Fubin Wang +7
With the continuous expansion of optical networks and the increasing diversity of services, existing operation and maintenance (O&M) approaches are increasingly challenged to meet…
Generative AI-Driven Hierarchical Multi-Agent Framework for Zero-Touch Optical Networks
Yao Zhang, Yuchen Song, Shengnan Li +5
The rapid development of Generative Artificial Intelligence (GenAI) has catalyzed a transformative technological revolution across all walks of life. As the backbone of wideband co…
FiberKAN: Kolmogorov-Arnold Networks for Nonlinear Fiber Optics
Xiaotian Jiang, Min Zhang, Xiao Luo +3
Scientific discovery and dynamic characterization of the physical system play a critical role in understanding, learning, and modeling the physical phenomena and behaviors in vario…
Physics-Informed Machine Learning for EDFA: Parameter Identification and Gain Estimation
Xiaotian Jiang, Jiawei Dong, Yuchen Song +3
As the key component that facilitates long-haul transmission in optical fiber communications by increasing capacity and reducing costs, accurate characterization and gain settings…
Synergistic Interplay of Large Language Model and Digital Twin for Autonomous Optical Networks: Field Demonstrations
Yuchen Song, Yao Zhang, Anni Zhou +6
The development of large language models (LLM) has revolutionized various fields and is anticipated to drive the advancement of autonomous systems. In the context of autonomous opt…
When Large Language Models Meet Optical Networks: Paving the Way for Automation
Danshi Wang, Yidi Wang, Xiaotian Jiang +3
Since the advent of GPT, large language models (LLMs) have brought about revolutionary advancements in all walks of life. As a superior natural language processing (NLP) technology…
A Review of Machine Learning-based Failure Management in Optical Networks
Danshi Wang, Chunyu Zhang, Wenbin Chen +3
Failure management plays a significant role in optical networks. It ensures secure operation, mitigates potential risks, and executes proactive protection. Machine learning (ML) is…
Physics-Informed Neural Operator for Fast and Scalable Optical Fiber Channel Modelling in Multi-Span Transmission
Yuchen Song, Danshi Wang, Qirui Fan +3
We propose efficient modelling of optical fiber channel via NLSE-constrained physics-informed neural operator without reference solutions. This method can be easily scalable for di…
Physics-informed Neural Network for Nonlinear Dynamics in Fiber Optics
Xiaotian Jiang, Danshi Wang, Qirui Fan +3
A physics-informed neural network (PINN) that combines deep learning with physics is studied to solve the nonlinear Schrödinger equation for learning nonlinear dynamics in fiber op…
Role of Digital Twin in Optical Communication: Fault Management, Hardware Configuration, and Transmission Simulation
Danshi Wang, Zhiguo Zhang, Min Zhang +5
Optical communication is developing rapidly in the directions of hardware resource diversification, transmission system flexibility, and network function virtualization. Its prolif…
Wavelength Controllable Forward Prediction and Inverse Design of Nanophotonic Devices Using Deep Learning
Yuchen Song, Danshi Wang, Han Ye +2
A deep learning-based wavelength controllable forward prediction and inverse design model of nanophotonic devices is proposed. Both the target time-domain and wavelength-domain inf…