Our unsupervised approaches leverage long short-term memory (LSTM) encoder-decoder models to embed the graph sequences into a continuous vector space. We then represent a graph by aggregating its graph sequence representations. Our supervised architecture uses an attention mechanism to collect ...
1. Language Modeling Loss:语言模型损失主要用于衡量模型生成一个文本序列的概率。通常，LM任务预测给定上...
Toward an End-to-End Framework for Modeling, Monitoring and Anomaly Detection for Scientific Workflows Modern science is often conducted on large scale, distributed, heterogeneous and high-performance computing infrastructures. Increasingly, the scale and co... A Mandal,P Ruth,I Baldin,... - IEEE...
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where the goal is to reformulate the conversational query into a search engine friendly query in order to satisfy users’ information needs in conversational settings. Such context-aware query reformulation problem lends itself to sequence to sequence modeling. We present a large scale open ...
《Residual Flows for Invertible Generative Modeling》(CoRR 2019) GitHub: O网页链接《VisualBERT: A Simple and Performant Baseline for Vision and Language》GitHub:O网页链接《SCARLET-NAS: Bridging the gap Between Scalability and Fairness in Neural Architecture Search》GitHub:O网页链接...
Modeling text in a numerical representation is a prime task for any Natural Language Processing downstream task such as text classification. This paper att... S Modha,P Majumder,T Mandl - 《Journal of Experimental & Theoretical Artificial Intelligence》 被引量: 0发表: 2022年 ...
Xu, "A comparison of modeling units in sequence-to-sequence speech recognition with the trans- former on mandarin chinese," arXiv preprint arXiv:1805.06239, 2018.S. Zhou, L. Dong, S. Xu, and B. Xu, "Syllable-Based Sequence- to-Sequence Speech Recognition with the Transformer in Man- ...
--Transformation TPS --FeatureExtraction ResNet --SequenceModeling BiLSTM --Prediction Attnto define architecture. --saved_modelto provide a path to a pre-trained model. In case oftrain.pyit will be used as a starting point in fine-tuning and in the case oftest.pyit will be used for pre...
Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language modeling and other text generation tasks. We provide reference implementations of various sequence modeling papers: ...