Conference

Co-Stack Residual Affinity Networks with Multi-level Attention Refinement for Matching Text Sequences
Learning a matching function between two text sequences is a long standing problem in NLP research. This task enables many potential …
Multi-Cast Attention Networks for Retrieval-based Question Answering and Response Prediction
Attention is typically used to select informative sub-phrases that are used for prediction. This paper investigates the novel use of …
CoupleNet:Paying Attention to Couples with Coupled Attention for Relationship Recommendation
Dating and romantic relationships not only play a huge role in our personal lives but also collectively influence and shape society. …
Hermitian Co-Attention Networks for Text Matching in Asymmetrical Domains
Co-Attentions are highly effective attention mechanisms for text matching applications. Co-Attention enables the learning of pairwise …
Compare, Compress and Propagate:Enhancing Neural Architectures with Alignment Factorization for Natural Language Inference
This paper presents a new deep learning architecture for Natural Language Inference (NLI). Firstly, we introduce a new architecture …
Multi-Granular Sequence Encoding via Dilated Compositional Units for Reading Comprehension
Sequence encoders are crucial components in many neural architectures for learning to read and comprehend. This paper presents a new …
Multi-Pointer Co-Attention Networks for Recommendation
Many recent state-of-the-art recommender systems such as D-ATT, TransNet and DeepCoNN exploit reviews for representation learning. This …
Reasoning with Sarcasm by Reading In-between
Sarcasm is a sophisticated speech act which commonly manifests on social communities such as Twitter and Reddit. The prevalence of …
Learning to Attend via Word-Aspect Associative Fusion for Aspect-based Sentiment Analysis
Aspect-based sentiment analysis (ABSA) tries to predict the polarity of a given document with respect to a given aspect entity. While …
Cross Temporal Recurrent Networks for Ranking Question Answer Pairs
Temporal gates play a significant role in modern recurrent-based neural encoders, enabling fine-grained control over recursive …