4 papers
TRON: Trainable, architecture-reconfigurable random optical neural networks
Ziao Wang, Fei Xia, Logan G. Wright +5
Deep learning has triggered explosive growth in the demand for specialized hardware processors, thus motivating the development of scalable and reconfigurable computing substrates.…
Training deep physical neural networks with local physical information bottleneck
Hao Wang, Ziao Wang, Xiangpeng Liang +8
Deep learning has revolutionized modern society but faces growing energy and latency constraints. Deep physical neural networks (PNNs) are interconnected computing systems that dir…
Optical Computing with Spectrally Multiplexed Features in Complex Media
Xue Dong, Kai Lion, Fei Xia +4
Artificial intelligence (AI) has rapidly evolved into a critical technology; however, electrical hardware struggles to keep pace with the exponential growth of AI models. Free spac…
Nexus: An Omni-Perceptive And -Interactive Model for Language, Audio, And Vision
Che Liu, Yingji Zhang, Dong Zhang +13
This work proposes an industry-level omni-modal large language model (LLM) pipeline that integrates auditory, visual, and linguistic modalities to overcome challenges such as limit…