Selected from arXiv Authors: Andrea Banino et al. Compiled by Machine Heart Editors: Chen Ping, Du Wei Researchers from DeepMind proposed the CoBERL agent for reinforcement learning, which combines a new contrastive loss with a hybrid LSTM-transformer architecture to improve data processing efficiency. Experiments show that CoBERL can continuously improve performance across the entire Atari … Read more
Research on Land Subsidence Intelligent Prediction Method Based on LSTM and Transformer: A Case Study of Shanghai PENG Wenxiang1,2,3,4,5，ZHANG Deying1,2,3,4,5 1. Shanghai Institute of Geological Survey, Shanghai 200072, China; 2. Shanghai Institute of Geological Exploration Technology, Shanghai 200072, China; 3. Key Laboratory of Land Subsidence Monitoring and Prevention, Ministry of Natural Resources of China, Shanghai … Read more
Deep learning is an important branch of artificial intelligence that has made significant progress in recent years. Among them, RNN, CNN, Transformer, BERT, and GPT are five commonly used deep learning models that have achieved important breakthroughs in fields such as computer vision and natural language processing. This article will briefly introduce these five models … Read more
Long Ge’s Message: On the path to excellence, only through continuous exploration can we create the future. Paper TitleARWKV: Pretrain is not what we need, an RNN-Attention-Based Language Model Born from Transformer Publication DateJanuary 2025 AuthorsLin Yueyu, Li Zhiyuan, Peter Yue, Liu Xiao AffiliationUnknown Original Linkhttps://arxiv.org/pdf/2501.15570 Open Source Code Linkhttps://github.com/yynil/RWKVInside Demo Linkhttps://huggingface.co/RWKV-Red-Team/ARWKV-7B-Preview-0.1 Introduction In recent … Read more
Source: Intelligent Learning and Thinking Distributed Laboratory This article is about 6100 words long, and it is recommended to read it in 9 minutes. This article analyzes the key points and main innovations behind the core paper of ChatGPT. Origin By inputting a few simple keywords, AI can help you generate a short story or … Read more
Click the above “Beginner’s Guide to Vision” and choose to add “Star” or “Pin“ Important insights delivered at the first moment Scan the QR code below to join the cutting-edge academic paper exchange group!Get the latest top conference/journal paper idea interpretations and PDF interpretations!And materials from beginner to advanced in CV, and the most cutting-edge … Read more
MLNLP community is a well-known machine learning and natural language processing community in China and abroad, covering NLP master’s and doctoral students, university teachers, and industry researchers.The vision of the community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning, especially for beginners. Reproduced from … Read more
Introduction Using PyTorch to implement the ViT model code from scratch, training the ViT model on the CIFAR-10 dataset for image classification. Architecture of ViT The architecture of ViT is inspired by BERT, which is an encoder-only transformer model typically used for supervised learning tasks in NLP such as text classification or named entity recognition. … Read more
Click the blue text Follow us The three fundamental elements of artificial intelligence: data, computing power, and algorithms are interdependent and mutually supportive, jointly promoting the rapid development of artificial intelligence. This article will outline the current development status of cutting-edge artificial intelligence from the perspective of algorithms and models. ｜Current Status of Algorithm and … Read more
MLNLP community is a well-known machine learning and natural language processing community in China and abroad, covering NLP master’s and doctoral students, university teachers, and corporate researchers.The community’s vision is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning, especially for beginners. Reprinted from | Quantum … Read more