17 citations · 18 across the 6 of their papers we have counts for
6 papers
RTLRepoCoder: Repository-Level RTL Code Completion through the Combination of Fine-Tuning and Retrieval Augmentation
Peiyang Wu, Nan Guo, Junliang Lv +2
As an essential part of modern hardware design, manually writing Register Transfer Level (RTL) code such as Verilog is often labor-intensive. Following the tremendous success of la…
ITERTL: An Iterative Framework for Fine-tuning LLMs for RTL Code Generation
Peiyang Wu, Nan Guo, Xiao Xiao +3
Recently, large language models (LLMs) have demonstrated excellent performance, inspiring researchers to explore their use in automating register transfer level (RTL) code generati…
Video Face Recognition System: RetinaFace-mnet-faster and Secondary Search
Qian Li, Nan Guo, Xiaochun Ye +2
Face recognition is widely used in the scene. However, different visual environments require different methods, and face recognition has a difficulty in complex environments. There…
Top-Related Meta-Learning Method for Few-Shot Object Detection
Qian Li, Nan Guo, Xiaochun Ye +3
Many meta-learning methods are proposed for few-shot detection. However, previous most methods have two main problems, poor detection APs, and strong bias because of imbalance and…
Pixel-Semantic Revise of Position Learning A One-Stage Object Detector with A Shared Encoder-Decoder
Qian Li, Nan Guo, Xiaochun Ye +2
Recently, many methods have been proposed for object detection. They cannot detect objects by semantic features, adaptively. In this work, according to channel and spatial attentio…
Utilizing the Instability in Weakly Supervised Object Detection
Yan Gao, Boxiao Liu, Nan Guo +4
Weakly supervised object detection (WSOD) focuses on training object detector with only image-level annotations, and is challenging due to the gap between the supervision and the o…