Language and Attention
Connecting Language to Images: A Progressive Attention-Guided Network for Simultaneous Image Captioning and Language Grounding
... and language grounding by a PAGNet, which has two appeal- ing properties: i) PAGNet predicts caption sentences for im- ages in a progressive ...the attention over the image can be progressively updated ...
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An Evaluation of Language Agnostic Inner Attention Based Representations in Machine Translation
... the attention bridge hampers the results for the monolingual se- mantic similarity measured with the cosine dis- tance, while it becomes easier in a bilingual sce- nario where the vector encodes only one source ...
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CN HIT MI T at SemEval 2019 Task 6: Offensive Language Identification Based on BiLSTM with Double Attention
... method Attention-based residual connected BiLSTM with Emojis Attention for SemEval 2019 Task 6: Iden- tifying and Categorizing Offensive Language in Social ...
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Overcoming Language Variation in Sentiment Analysis with Social Attention
... in language is ubiquitous, particu- larly in newer forms of writing such as social ...use language in similar ways. We formalize this idea in a novel attention-based neural network architec- ture, in ...
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The Relationship between Attention Problems and Language Learning Difficulty
... a language are due to the language itself or students’ attention ...a language has turn out to be difficult for some people but not for the ...But language learning difficulties may be ...
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Character-Level Language Modeling with Deeper Self-Attention
... key-value attention mechanism similar to transformers is ...of attention for processing a fix memory representing the input document and has been shown to be effective for language modeling in ...
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Research on attention memory networks as a model for learning natural language inference
... proposed attention memory net- works (AMNs) to solve the natural language infer- ence (NLI) ...The attention memory networks (AMN- s) over the premise provides further improvements to the predictive ...
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Analyzing the Structure of Attention in a Transformer Language Model
... fully attention-based alternative to recurrent networks that has achieved state-of-the-art results across a range of NLP ...of attention in a Transformer language model, the GPT-2 small pretrained ...
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Multilingual NMT with a Language Independent Attention Bridge
... We apply the sentence representations learned by our model to downstream tasks collected in the SentEval toolkit (Conneau and Kiela, 2018) to evaluate the quality of our language-agnostic sen- tence embeddings. We ...
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A Decomposable Attention Model for Natural Language Inference
... ral Language Inference (SNLI) dataset, we ob- tain state-of-the-art results with almost an order of magnitude fewer parameters than previous work and without relying on any word-order in- ...intra-sentence ...
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Survey on Attention Neural Network Models for Natural Language Processing
... Natural language processing(NLP) task like machine translation, sentence summarization,sentence pair modeling, paraphrase identification, natural language inference, question answering etc typically learn ...
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Dissociating Improvement of Attention and Intelligence during Written Language Acquisition in Adults
... by attention improvement during ...written language skills, children rely on cognitive abilities that were acquired before entering primary school [26-29] and that may be culturally specific ...written ...
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Learning the Dyck Language with Attention based Seq2Seq Models
... Dyck language has been used to analyze the ability of Recurrent Neural Net- works (RNNs) to learn context-free grammars ...of attention mechanisms within the seq2seq framework to learn the Dyck lan- guage, ...
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Language to Logical Form with Neural Attention
... The problem of learning semantic parsers has received significant attention, dating back to Woods (1973). Many approaches learn from sen- tences paired with logical forms following vari- ous modeling strategies. ...
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Character level Intra Attention Network for Natural Language Inference
... tra attention layer augment the model’s ability to efficiently encode long sentences, and it enhances the models’ interpretability by visualizing the at- tention ...
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Local Monotonic Attention Mechanism for End to End Speech And Language Processing
... those attention mechanism are based on “global” property, where the attention module tries to match the current hidden states with all the states from the encoder ...“local attention” was re- cently ...
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Visual Interrogation of Attention-Based Models for Natural Language Inference and Machine Comprehension
... the attention, we can see the word green in “green jacket” is aligned to the green in “green ...the attention value and remove the align between these two “greens” (see ...
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Improving Slot Filling in Spoken Language Understanding with Joint Pointer and Attention
... We present a generative neural network model for slot filling based on a sequence- to-sequence (Seq2Seq) model together with a pointer network, in the situation where only sentence-level slot annotations are available in ...
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Of language, limits, and secrets
... McVeigh (the Oklahoma bomber), and a theoretical reflection on monuments. Enough to leave one’s head spinning after a mere twenty pages. But as Horkheimer and Adorno posited in Dialectic of Enlightenment (1947/1973), ...
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What does Attention in Neural Machine Translation Pay Attention to?
... of attention recently due to its substantial im- provements in machine translation quality achiev- ing state-of-the-art performance for several lan- guages (Luong et ...
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