CVPR2020-Papers-with-Code.md add CVPR 2020【点云语义分割】Weakly Supervised Semantic Point Cloud Segmentat… Mar 4, 2021 CVPR2021-Papers-with-Code.md add 5 Paper【NeRF】【3D】【CLIP】 Mar 2, 2022 CVPR2022-Papers-with-Code.md 添加:CVPR 2023 Feb 27, 2023 CVer学术交流群.png 添加2 Papers...
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Code:https://github.com/eric8607242/SGNAS OPANAS: One-Shot Path Aggregation Network Architecture Search for Object Detection Paper:https://arxiv.org/abs/2103.04507 Code:https://github.com/VDIGPKU/OPANAS Inception Convolution with Efficient Dilation Search ...
https:///amusi/CVPR2021-Papers-with-Code Backbone NAS GAN Visual Transformer 自监督(Self-Supervised) 目标检测(Object Detection) 实例分割(Instance Segmentation) 全景分割(Panoptic Segmentation) 视频理解/行为识别(Video Understanding) 人脸识别(Face Recognition) ...
A valid JSON file is a list ofTaskobjects. You can see examples in thedata/tasksfolder. Task ATaskconsists of the following fields: task- name of the task (string) description- short description of the task, in markdown (string)
There has been a growing effort to replace manual extraction of data from research papers with automated data extraction based on natural language processing, language models, and recently, large language models (LLMs). Although these methods enable effi
Learning to Represent Programs with Graphs. ICLR 2018. paper Miltiadis Allamanis, Marc Brockschmidt, Mahmoud Khademi. Open Vocabulary Learning on Source Code with a Graph-Structured Cache. ICML 2019. paper Milan Cvitkovic, Badal Singh, Anima Anandkumar. Devign: Effective Vulnerability Identification by...
examples over state-of-the-art large language models (LLM) like GPT3.5. We quantitatively evaluate 60 single and 25 multi-API queries from 6 popular Python libraries and show that across-the-board CodeScholar generates more realistic, diverse, and concise examples. In addition, we show that ...
Code Language Models are Few-Shot Learners ggml-org/llama.cpp• •NeurIPS 2020 By contrast, humans can generally perform a new language task from only a few examples or from simple instructions - something which current NLP systems still largely struggle to do. ...
in Simultaneous Translation. (from Tie-Yan Liu) 6. Contextualized Code Representation Learning for Commit Message Generation. (from Yang Liu) 7. Modeling Voting for System Combination in Machine Translation. (from Yang Liu) 8. LogiQA: A Challenge Dataset for Machine Reading Comprehension with ...