46 citations · 112 across the 10 of their papers we have counts for
12 papers
HALO: A Physics-Aware LLM Agent Framework for Nanophotonic Design
Yubo Zhang, Jinlin Xiang, Zijun Zhao +3
Language models have recently been applied to nanophotonic design, but it remains unclear whether they can reliably translate optical objectives into simulation-ready designs, exec…
Advantages of Broadband Metalenses for Generalizable Image Classification
Yubo Zhang, Johannes Fröch, Jinlin Xiang +6
Optical neural networks (ONNs) are gaining increasing attention to accelerate machine learning tasks. In particular, static meta-optical encoders designed for task-specific pre-pro…
Neural Tangent Knowledge Distillation for Optical Convolutional Networks
Jinlin Xiang, Minho Choi, Yubo Zhang +3
Hybrid Optical Neural Networks (ONNs, typically consisting of an optical frontend and a digital backend) offer an energy-efficient alternative to fully digital deep networks for re…
SAVVY: Spatial Awareness via Audio-Visual LLMs through Seeing and Hearing
Mingfei Chen, Zijun Cui, Xiulong Liu +4
3D spatial reasoning in dynamic, audio-visual environments is a cornerstone of human cognition yet remains largely unexplored by existing Audio-Visual Large Language Models (AV-LLM…
Transferable polychromatic optical encoder for neural networks
Minho Choi, Jinlin Xiang, Anna Wirth-Singh +3
Artificial neural networks (ANNs) have fundamentally transformed the field of computer vision, providing unprecedented performance. However, these ANNs for image processing demand…
Compressed Meta-Optical Encoder for Image Classification
Anna Wirth-Singh, Jinlin Xiang, Minho Choi +5
Optical and hybrid convolutional neural networks (CNNs) recently have become of increasing interest to achieve low-latency, low-power image classification and computer vision tasks…
Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation
Chenyu You, Jinlin Xiang, Kun Su +5
Many medical datasets have recently been created for medical image segmentation tasks, and it is natural to question whether we can use them to sequentially train a single model th…
A Cross-City Federated Transfer Learning Framework: A Case Study on Urban Region Profiling
Gaode Chen, Yijun Su, Xinghua Zhang +6
Data insufficiency problems (i.e., data missing and label scarcity) caused by inadequate services and infrastructures or imbalanced development levels of cities have seriously affe…
TKIL: Tangent Kernel Approach for Class Balanced Incremental Learning
Jinlin Xiang, Eli Shlizerman
When learning new tasks in a sequential manner, deep neural networks tend to forget tasks that they previously learned, a phenomenon called catastrophic forgetting. Class increment…
Exploring Periodicity and Interactivity in Multi-Interest Framework for Sequential Recommendation
Gaode Chen, Xinghua Zhang, Yanyan Zhao +2
Sequential recommendation systems alleviate the problem of information overload, and have attracted increasing attention in the literature. Most prior works usually obtain an overa…
Knowledge Distillation Circumvents Nonlinearity for Optical Convolutional Neural Networks
Jinlin Xiang, Shane Colburn, Arka Majumdar +1
In recent years, Convolutional Neural Networks (CNNs) have enabled ubiquitous image processing applications. As such, CNNs require fast runtime (forward propagation) to process hig…
BI-MAML: Balanced Incremental Approach for Meta Learning
Yang Zheng, Jinlin Xiang, Kun Su +1
We present a novel Balanced Incremental Model Agnostic Meta Learning system (BI-MAML) for learning multiple tasks. Our method implements a meta-update rule to incrementally adapt i…