Language Models as Knowledge Bases?

Transformer-XL: Attentive Language Models beyond a Fixed ...

⌧+1= Transformer-Layer(q n,kn ⌧+1,v n). where the function SG(·) stands for stop-gradient, the notation [hu hv] indicates the concatenation of two hidden sequences along the length dimen-sion, and W· denotes model parameters. Com-pared to the standard Transformer, the critical dif-ference lies in that the key kn ⌧+1 and value v n ⌧+1

  Transformers

Improving Multimodal Named Entity Recognition via Entity ...

with cross-modal attention mechanism to produce an image-aware word representation and a word-aware visual representation for each input word, respectively. Finally, to largely eliminate the bias of the visual context, we propose to leverage text-based entity span detection as an auxiliary task, and design a unified neural architecture based on

  Span, Attention

Entity, Relation, and Event Extraction with Contextualized ...

Span enumeration Event propagation Coreference Auxiliary Sentence Sentence É É Sentence Figure 1: Overview of our framework: DYGIE++. Shared span representations are constructed by refin-ing contextualized word embeddings via span graph updates, then passed to scoring functions for three IE tasks. Mitchell,2016;Li and Ji,2014) and neural scor-

  Span

CH-SIMS: A Chinese Multimodal Sentiment Analysis Dataset ...

Sentiment analysis is an important research area in Natural Language Processing (NLP). It has wide applications for other NLP tasks, such as opinion mining, dialogue generation, and user behavior analysis. Previous study (Pang et al.,2008;Liu and Zhang,2012) mainly focused on text sentiment analysis and achieved impressive results. However,

  Analysis, Sentiment, Sentiment analysis

Recurrent Attention Network on Memory for Aspect …

tic analysis (Socher et al.,2010) and sentence sen-timent analysis (Socher et al.,2013). (Dong et al., 2014;Nguyen and Shirai,2015) adopted Rec-NN for aspect sentiment classication, by converting the opinion target as the tree root and propagating the sentiment of targets depending on the context and syntactic relationships between them. How-

  Analysis, Sentiment, Mitten, Sen timent analysis

A Joint Neural Model for Information Extraction with ...

Entity Extraction aims to identify entity men-tions in text and classify them into pre-defined en-tity types. A mention can be a name, nominal, or pronoun. For example, “Kashmir region” should be recognized as a location (LOC) named entity mention in Figure2. Relation Extraction is the task of assigning a

  Information, Model, Texts, Extraction, Neural, Neural model for information extraction

Exploring Pre-trained Language Models for Event Extraction ...

3 Extraction Model This section describes our approach to extract events that occur in plain text. We consider event extraction as a two-stage task, which includes trig-ger extraction and argument extraction, and pro-pose a Pre-trained Language Model based Event Extractor (PLMEE). Figure3illustrates the archi-tecture of PLMEE.

  Texts, Extraction

BLEU: a Method for Automatic Evaluation of Machine …

tor and a standard (poor) machine translation system using 4 reference translations for each of 127 source sentences. The average precision results are shown in Figure 1. Figure 1: Distinguishing Human from Machine ˘ ˇ ˆ The strong signal differentiating human (high pre-cision) from machine (low precision) is striking.

  Machine, Blue, Precision, Cisions, Pre cision

Dual Graph Convolutional Networks for Aspect-based ...

Aspect-based sentiment analysis is a fine-grained sentiment classification task. Re-cently, graph neural networks over depen-dency trees have been explored to explicitly model connections between aspects and opin-ion words. However, the improvement is lim-ited due to the inaccuracy of the dependency parsing results and the informal expressions

  Analysis, Sentiment, Sentiment analysis

Learning Implicit Sentiment in Aspect-based Sentiment ...

Aspect-based sentiment analysis aims to iden-tify the sentiment polarity of a specific aspect in product reviews. We notice that about 30% of reviews do not contain obvious opinion words, but still convey clear human-aware sen-timent orientation, which is known as implicit sentiment. However, recent neural network-

  Analysis, Sentiment, Mitten, Sentiment analysis, Sen timent

Sentiment Analysis of Twitter Data

even though it does not require detailed feature en-gineering. We use manually annotated Twitter data for our. experiments. One advantage of this data, over pre-viously used data-sets, is that the tweets are col-lected in a streaming fashion and therefore represent

  Ingegneri, E ngineering

ELEMENTARY DIFFERENTIAL EQUATIONS WITH BOUNDARY …

Elementary Differential Equations with Boundary Value Problems is written for students in science, en-gineering,and mathematics whohave completed calculus throughpartialdifferentiation. Ifyoursyllabus includes Chapter 10 (Linear Systems of Differential Equations), your students should have some prepa-ration inlinear algebra.

  Differential, Equations, Differential equations, Ingegneri, E ngineering

Electrical Plan Design

7. Master Concepts • When designing an electrical plan, the designer must understand the scope of the project, define each required part, and then design them to recognized industry

2017 Infiniti QX60 Owner's Manual and Maintenance …

It integrates advanced en-gineering and superior craftsmanship with a simple, refined aesthetic sensitivity associated with traditional Japanese culture. The result is a different notion of luxury and beauty. The car itself is important, but so is the sense of …

  Manual, 2017, Owner, Infiniti, Ingegneri, E ngineering, 2017 infiniti qx60 owner s manual, Qx60