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Found 3 papers, 2 papers with code
Data is all you need: Finetuning LLMs for Chip Design via an Automated design-data augmentation framework
Our 13B model (ChipGPT-FT) has a pass rate improvement compared with GPT-3. 5 in Verilog generation and outperforms in EDA script (i. e., SiliconCompiler) generation with only 200 EDA script data.
Short-length SSVEP data extension by a novel generative adversarial networks based framework
This study substantiates the feasibility of the proposed method to extend the data length for short-time SSVEP signals for developing a high-performance BCI system.
A Transformer-based deep neural network model for SSVEP classification
The proposed model validates the feasibility of deep learning models based on Transformer structure for SSVEP classification task, and could serve as a potential model to alleviate the calibration procedure in the practical application of SSVEP-based BCI systems.
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