[PDF] Top 20 Question Answering Using Hierarchical Attention on Top of BERT Features
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Question Answering Using Hierarchical Attention on Top of BERT Features
... a question about a given ...Recently, attention mechanisms have been successfully extended to machine com- ...the question and pas- sage are encoded using BERT language em- beddings to ... See full document
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Multi Granularity Hierarchical Attention Fusion Networks for Reading Comprehension and Question Answering
... novel hierarchical attention network for reading comprehen- sion style question answering, which aims to answer questions for a given narrative ...between question and paragraph. ... See full document
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Structured Two-Stream Attention Network for Video Question Answering
... image features and use Recurrent Neural Net- works (RNN) to represent question ...image features with question features using some simple fusion methods such as concatenation, ... See full document
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Sentiment Classification towards Question Answering with Hierarchical Matching Network
... Document-level sentiment classification has also been studied in a long period in the research community of sentiment analysis. On one hand, many early studies have been devoted their efforts to various of aspects on ... See full document
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Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering
... In addition, we compare our VPSA to the recurrent layers which are commonly used for mapping one variable-length sequence of features to another sequence with equal length. Here, we adopt the bidirectional LSTM ... See full document
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Neural Attention for Learning to Rank Questions in Community Question Answering
... an attention mechanism, which can select impor- tant parts of text for the task of similar question retrieval from community Question Answering (cQA) ...the attention weights for both ... See full document
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HAS-QA: Hierarchical Answer Spans Model for Open-Domain Question Answering
... At the paragraph level, paragraph probability is defined as the degree to which a paragraph can answer the question. This probability is used to measure the quality of a para- graph and targeted to tackle the ... See full document
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Cross-Modal Multistep Fusion Network with Co-Attention for Visual Question Answering
... Visual question answering (VQA) is receiving increasing attention from researchers in both the computer vision and natural language processing ...Word Attention (SWA) and Question-guide ... See full document
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Extending Neural Question Answering with Linguistic Input Features
... Possibly, using no word embed- dings at all and scaling up the character embed- dings could increase the performance further and eliminate the need for pre-trained embeddings al- ...when using 5 ... See full document
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Neural Arabic Question Answering
... Arabic question answering (QA) us- ing Wikipedia as our knowledge ...any question to be a span of text in ...Stanford Question Answering Dataset ...main question answering ... See full document
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Sequential Attention with Keyword Mask Model for Community based Question Answering
... much attention in vari- ous tasks(Krizhevsky et ...In question answering field, the convo- lutional neural networks(CNNs)(Yu et ...the question and answer text into vec- tors and define a ... See full document
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Stacking with Auxiliary Features for Visual Question Answering
... Most VQA systems have a single underlying method that optimizes a specific loss function and do not leverage the advantage of using multiple di- verse models. One recent ensembling approach to VQA (Fukui et al., ... See full document
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Segmentation Guided Attention Networks for Visual Question Answering
... spatial attention to CNN features, instead of using global features from the entire ...local features extraction of the images from each of these ...CNN features, question ... See full document
6
Dynamic Capsule Attention for Visual Question Answering
... When using VGG-16, the dimensions of LSTM and CapsAtt is set to ...FRCNN features, we set the dimensions of LSTM and CapsAtt to both ...one attention layer, which confirms the generalization of our ... See full document
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A Recurrent BERT based Model for Question Generation
... rich features of the passage including answer posi- ...model using policy gradient tech- niques to maximize several rewards that measure question ...of using an annotation vector to tag the ... See full document
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Multi passage BERT: A Globally Normalized BERT Model for Open domain Question Answering
... However, BERT model simply concate- nates a passage with a question, and differenti- ates them by separating them with a delimiter to- ken [SEP], and assigning different segment ids for ...for BERT. ... See full document
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End to End Non Factoid Question Answering with an Interactive Visualization of Neural Attention Weights
... Advanced attention mechanisms are an im- portant part of successful neural network approaches for non-factoid answer selec- tion because they allow the models to focus on few important segments within rather long ... See full document
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Using Question Series to Evaluate Question Answering System Effectiveness
... series, using the series as abstractions of information-seeking ...Each question in a series asked for some information about the ...final question in each series was an explicit “other” ques- tion, ... See full document
8
Aspect Sentiment Classification Towards Question Answering with Reinforced Bidirectional Attention Network
... tional attention network approach to tackle the above two ...Bidirectional Attention Network (RBAN) approach to ASC-QA, which employs two funda- mental RAWS modules to perform word selection over the ... See full document
10
Science Question Answering using Instructional Materials
... (a) Surface-form match (Edit-distance), and (b) Semantic word match (cosine similarity using SENNA word vectors (Collobert et al., 2011) and “Antonymy” ‘Class-Inclusion’ or ‘Is-A’ relations using Wordnet). ... See full document
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