OriGen:Enhancing RTL Code Generation with Code-to-Code Augmentation and Self-Reflection

1 code implementation • 23 Jul 2024 • Fan Cui, Chenyang Yin, Kexing Zhou, Youwei Xiao, Guangyu Sun, Qiang Xu, Qipeng Guo, Demin Song, Dahua Lin, Xingcheng Zhang, Yun, Liang

While open-source LLMs offer solutions to these concerns, they typically underperform commercial models in RTL code generation tasks, primarily due to the scarcity of high-quality open-source RTL datasets.

Code Generation Knowledge Distillation

Exploring Representation Learning for Small-Footprint Keyword Spotting

no code implementations • 20 Mar 2023 • Fan Cui, Liyong Guo, Quandong Wang, Peng Gao, Yujun Wang

To address those challenges, we explore representation learning for KWS by self-supervised contrastive learning and self-training with pretrained model.

Contrastive Learning Representation Learning +1

Relate auditory speech to EEG by shallow-deep attention-based network

no code implementations • 20 Mar 2023 • Fan Cui, Liyong Guo, Lang He, Jiyao Liu, Ercheng Pei, Yujun Wang, Dongmei Jiang

Electroencephalography (EEG) plays a vital role in detecting how brain responses to different stimulus.

Data Augmentation Deep Attention +1

Improving Weakly Supervised Sound Event Detection with Causal Intervention

no code implementations • 10 Mar 2023 • Yifei Xin, Dongchao Yang, Fan Cui, Yujun Wang, Yuexian Zou

Existing weakly supervised sound event detection (WSSED) work has not explored both types of co-occurrences simultaneously, i. e., some sound events often co-occur, and their occurrences are usually accompanied by specific background sounds, so they would be inevitably entangled, causing misclassification and biased localization results with only clip-level supervision.

Event Detection Sound Event Detection

Predicting Multi-Codebook Vector Quantization Indexes for Knowledge Distillation

1 code implementation • 31 Oct 2022 • Liyong Guo, Xiaoyu Yang, Quandong Wang, Yuxiang Kong, Zengwei Yao, Fan Cui, Fangjun Kuang, Wei Kang, Long Lin, Mingshuang Luo, Piotr Zelasko, Daniel Povey

Although on-the-fly teacher label generation tackles this issue, the training speed is significantly slower as the teacher model has to be evaluated every batch.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +3

Robust Protection of III-V Nanowires in Water Splitting by a Thin Compact TiO$_2$ Layer

no code implementations • 16 Dec 2020 • Fan Cui, Yunyan Zhang, H. Aruni Fonseka, Premrudee Promdet, Ali Imran Channa, Mingqing Wang, Xueming Xia, Sanjayan Sathasivam, Hezhuang Liu, Ivan P. Parkin, Hui Yang, Ting Li, Kwang-Leong Choy, Jiang Wu, Chris Blackman, Ana M. Sanchez, Huiyun Liu

Working as a photocathode for water splitting, they exhibited a 45% larger photocurrent density compared with un-protected counterparts and a high Faraday efficiency of 91%, and can also maintain a record-long highly-stable performance among narrow-bandgap III-V NW photoelectrodes; after 67 hours photoelectrochemical stability test reaction in strong acid electrolyte solution (pH = 1), they show no apparent indication of corrosion, which is in stark contrast to the un-protected NWs that are fully failed after 35-hours.

Mesoscale and Nanoscale Physics Chemical Physics

Cross-model convolutional neural network for multiple modality data representation

no code implementations • 19 Nov 2016 • Yanbin Wu, Li Wang, Fan Cui, Hongbin Zhai, Baoming Dong, Jim Jing-Yan Wang

A novel data representation method of convolutional neural net- work (CNN) is proposed in this paper to represent data of different modalities.