Recently, there has been a lot of research on differentpre-trainingobjectives for transformer-based encoder-decoder models,e.g.T5, Bart, Pegasus, ProphetNet, Marge,etc..., but the model architecture has stayed largely the same. The goal of the blog post is to give anin-detailexplanation of...
The results of the evaluation show that the proposed architecture outperforms existing deep learning models such as U-Net with a Dice Similarity Coefficient of 82.82% and 81.66% on both datasets.doi:10.3390/diagnostics13081406Chandra Sekhara Rao Annavarapu...
The decoder is also an RNN that takes in the output of the encoder and generates an output sequence one element at a time. At each time step, the decoder updates its hidden state based on the previous output and the current hidden state. The output of the decoder is then used as the ...
both procedures being instances of data-based model intervention. In this work, we present a preliminary study investigating rank-one editing as a direct intervention method for behavior deletion requests in encoderdecoder transformer models. We propose four editing tasks for NMT and show that...
Google 发表的使用Seq2Seq做语音识别的论文《A Comparison of Sequence-to-Sequence Models for Speech Recognition》 图像描述生成(图片 – 文本) 通俗的讲就是“看图说话”,机器提取图片特征,然后用文字表达出来。这个应用是计算机视觉和 NLP 的结合。
CodeT5: The Code-aware Encoder-Decoder based Pre-trained Programming Language Models Explore related content by topic TL; DR: Introducing CodeT5 — the first code-aware, encoder-decoder-based pre-trained programming language model, which enables a wide range of code intelligence applications ...
accuracyof93.4%,whichisbetterthanseveralexistingnetworkmodels.Inthesegmentation task,thispaperevaluatedtheperformanceofthePCRTnetworkontheShapeNetandS3DIS datasetsandcompareditwithexistingpointcloud-baseddeeplearningmodels.Theexperimen- talresultsrevealedthatthePCRTnetworkcanachievemeanintersectionoverunionof86.3% onthe...
Typically, in the space of model behaviors, behavior deletion requests are addressed through model retrainings whereas model finetuning is done to address behavior addition requests, both procedures being instances of data-based model intervention. In this work, we present a preliminary study ...
Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models". machine-learninguncertainty-quantificationmanifold-learningencoder-decoder-modelsurrogate-modellingpolynomial-chaos-expansion UpdatedJun 14, 2022
We propose a new simple network architecture, theTransformer, based solely onattention mechanisms, dispensing with recurrence and convolutions entirely. Reference: Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, Ł., Polosukhin, I. (2017). Attent...