EMNLP

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 …
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 …
Learning Term Embeddings for Taxonomic Relation Identification with Dynamic Weighting Neural Network
In this paper, the aim is to recognize the ‘is-a’ relation between two terms through taxonomic relation identification. …
Taxonomy Construction using Syntactic Contextual Evidence
Taxonomies serve as the foundational structure for numerous structured, semantic knowledge resources. Recent efforts aimed at …
Incorporating Trustiness and Collective Synonym/ Contrastive Evidence into Taxonomy Construction
In many applications, taxonomy plays a crucial role by organizing domain knowledge into a hierarchy of is-are relations between terms. …