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We describe a novel neural network archi- tecture for the problem of semantic role la- beling. Many current solutions are compli- cated, consist of several stages and hand- built features, …...

We present a novel response generation sys- tem that can be trained end to end on large quantities of unstructured Twitter conversa- tions. A neural network architecture is used to …...

This paper describes IDEST, a new method for learning paraphrases of event patterns. It is based on a new neural network architecture that only relies on the weak supervision sig- …...

We present a neural network architecture to predict a point in color space from the se- quence of characters in the color’s name. Using large scale color–name pairs obtained from …...

Many language generation tasks require the production of text conditioned on both structured and unstructured inputs. We present a novel neural network architec- ture which generates an output sequence conditioned …...

We present a shift-reduce CCG semantic parser. Our parser uses a neural network ar- chitecture that balances model capacity and computational cost. We train by transferring a model from a …...

Textual similarity measurement is a challeng- ing problem, as it requires understanding the semantics of input sentences. Most previ- ous neural network models use coarse-grained sentence modeling, which has difficulty …...

AbstractDistant supervision is an efficient approach that automatically generates labeled data for relation extraction (RE). Traditional distantly supervised RE systems rely heavily on handcrafted features, and hence suffer from error …...

Transcription of speech is an important part of language documentation, and yet speech recognition technology has not been widely harnessed to aid linguists. We explore the use of a neural …...

AbstractFor many applications of question answering (QA), being able to explain why a given model chose an answer is critical. However, the lack of labeled data for answer justifications makes …...

Transcribing speech is an important part of language documentation, yet speech recognition technology has not been widely harnessed to aid linguists. We explore the use of a neural network architecture …...

AbstractBuilding systems that can communicate with humans is a core problem in Artificial Intelligence. This work proposes a novel neural network architecture for response selection in an end-to-end multi-turn conversational …...

AbstractThis paper describes a classification system that participated in the SemEval-2018 Task 12: The Argument Reasoning Comprehension Task. Briefly the task can be described as that a natural language “argument” …...

This paper describes a language-independent model for multi-class sentiment analysis using a simple neural network architecture of five layers (Embedding, Conv1D, GlobalMaxPooling and two Fully-Connected). The advantage of the proposed …...

AbstractWe present an approach to event coreference resolution by developing a general framework for clustering that uses supervised representation learning. We propose a neural network architecture with novel Clustering-Oriented Regularization …...

AbstractThis paper describes a hypernym discovery system for our participation in the SemEval-2018 Task 9, which aims to discover the best (set of) candidate hypernyms for input concepts or entities, …...

AbstractEfficient word representations play an important role in solving various problems related to Natural Language Processing (NLP), data mining, text mining etc. The issue of data sparsity poses a great …...

AbstractThis paper presents computational approaches for automatically detecting critical plot twists in reviews of media products. First, we created a large-scale book review dataset that includes fine-grained spoiler annotations at …...

AbstractThis paper presents the Know-Center system submitted for task 5 of the SemEval-2019 workshop. Given a Twitter message in either English or Spanish, the task is to first detect whether …...

AbstractAnswer selection aims at identifying the correct answer for a given question from a set of potentially correct answers. Contrary to previous works, which typically focus on the semantic similarity …...

AbstractLearning representations such that the source and target distributions appear as similar as possible has benefited transfer learning tasks across several applications. Generally it requires labeled data from the source …...

AbstractNamed entity recognition (NER) is one of the best studied tasks in natural language processing. However, most approaches are not capable of handling nested structures which are common in many …...

AbstractQuestion answering and conversational systems are often baffled and need help clarifying certain ambiguities. However, limitations of existing datasets hinder the development of large-scale models capable of generating and utilising …...

AbstractReferring expression comprehension, which is the ability to locate language to an object in an image, plays an important role in creating common ground. Many models that fuse visual and …...

AbstractWe propose a novel approach using representation learning for tackling the problem of extracting structured information from form-like document images. We propose an extraction system that uses knowledge of the …...

AbstractWord segmentation is a challenging pre-processing step for Thai Natural Language Processing due to the lack of explicit word boundaries. The previous systems rely on powerful neural network architecture alone …...

AbstractIn human-human conversations, Context Tracking deals with identifying important entities and keeping track of their properties and relationships. This is a challenging problem that encompasses several subtasks such as slot …...

AbstractIn this paper we present the final result of a project focused on Tunisian Arabic encoded in Arabizi, the Latin-based writing system for digital conversations. The project led to the …...

AbstractSexism is a harmful phenomenon that provokes gender inequalities and social imbalances. The expanding application of sexist content on social media platforms creates an unwelcoming and discomforting environment for many …...