Neural Network Model

This paper treats the classification of the se- mantic functions performed by adnominal con- stituents in Japanese, where many parts of speech act as adnominal constituents. In order to establish …...

Coherence is what makes a multi-sentence text meaningful, both logically and syn- tactically. To solve the challenge of or- dering a set of sentences into coherent or- der, existing approaches …...

We introduce the challenge of detecting se- mantically compatible words, that is, words that can potentially refer to the same thing (cat and hindrance are compatible, cat and dog are …...

Monolingual alignment models have been shown to boost the performance of question answering systems by ”bridging the lexical chasm” between questions and answers. The main limitation of these approaches is …...

We propose a neural-network based model for coordination boundary prediction. The net- work is designed to incorporate two signals: the similarity between conjuncts and the ob- servation that replacing the …...

This paper presents our approach for SemEval 2016 task 4: Sentiment Analysis in Twitter. We participated in Subtask A: Message Polar- ity Classification. The aim is to classify Twit- ter …...

AbstractDeceptive opinion spam detection has attracted significant attention from both business and research communities. Existing approaches are based on manual discrete features, which can capture linguistic and psychological cues. However, …...

Semantic scripts is a conceptual represen- tation which defines how events are orga- nized into higher level activities. Practi- cally all the previous approaches to induc- ing script knowledge from …...

In this paper, we propose a neural network model for graph-based dependency pars- ing which utilizes Bidirectional LSTM (BLSTM) to capture richer contextual in- formation instead of using high-order fac- …...

AbstractEvaluation of machine translation (MT) into morphologically rich languages (MRL) has not been well studied despite posing many challenges. In this paper, we explore the use of embeddings obtained from …...

AbstractIn the wake of a polarizing election, the cyber world is laden with hate speech. Context accompanying a hate speech text is useful for identifying hate speech, which however has …...

AbstractSolving cold-start problem in review spam detection is an urgent and significant task. It can help the on-line review websites to relieve the damage of spammers in time, but has …...

AbstractWe describe a neural network model that jointly learns distributed representations of texts and knowledge base (KB) entities. Given a text in the KB, we train our proposed model to …...

AbstractThis paper describes a neural-network model which performed competitively (top 6) at the SemEval 2017 cross-lingual Semantic Textual Similarity (STS) task. Our system employs an attention-based recurrent neural network model …...

AbstractThis paper introduces a novel training/decoding strategy for sequence labeling. Instead of greedily choosing a label at each time step, and using it for the next prediction, we retain the …...

AbstractSinglish can be interesting to the ACL community both linguistically as a major creole based on English, and computationally for information extraction and sentiment analysis of regional social media. We …...

AbstractWith more and more people around the world learning Chinese as a second language, the need of Chinese error correction tools is increasing. In the HSK dynamic composition corpus, word …...

AbstractIn this paper, we study how we can improve a deep learning approach to textual entailment by incorporating lexical entailment relations from WordNet. Our idea is to embed the lexical …...

AbstractMining electronic health records for patients who satisfy a set of predefined criteria is known in medical informatics as phenotyping. Phenotyping has numerous applications such as outcome prediction, clinical trial …...

AbstractWe propose several ways of reusing subword embeddings and other weights in subword-aware neural language models. The proposed techniques do not benefit a competitive character-aware model, but some of them …...

AbstractThis paper describes our system in SemEval-2018 task 12: Argument Reasoning Comprehension. The task is to select the correct warrant that explains reasoning of a particular argument consisting of a …...

AbstractParallel corpora are crucial resources for NLP applications, most notably for machine translation. The direction of the (human) translation of parallel corpora has been shown to have significant implications for …...

AbstractNeural network models have recently gained traction for sentence-level intent classification and token-based slot-label identification. In many real-world scenarios, users have multiple intents in the same utterance, and a token-level …...

AbstractThe activities we do are linked to our interests, personality, political preferences, and decisions we make about the future. In this paper, we explore the task of predicting human activities …...

AbstractPronouns are often dropped in Chinese sentences, and this happens more frequently in conversational genres as their referents can be easily understood from context. Recovering dropped pronouns is essential to …...

AbstractTransliteration is generally a phonetically based transcription across different writing systems. It is a crucial task for various downstream natural language processing applications. For the Myanmar (Burmese) language, robust automatic …...

AbstractChinese discourse parsing, which aims to identify the hierarchical relationships of Chinese elementary discourse units, has not yet a consistent evaluation metric. Although Parseval is commonly used, variations of evaluation …...

AbstractWhile automatic term extraction is a well-researched area, computational approaches to distinguish between degrees of technicality are still understudied. We semi-automatically create a German gold standard of technicality across four …...

AbstractThe Universal Trigger (UniTrigger) is a recently-proposed powerful adversarial textual attack method. Utilizing a learning-based mechanism, UniTrigger generates a fixed phrase that, when added to any benign inputs, can drop …...

AbstractExisting work on Fine-grained Entity Typing (FET) typically trains automatic models on the datasets obtained by using Knowledge Bases (KB) as distant supervision. However, the reliance on KB means this …...

Recent advances in natural language process- ing (NLP) have the ability to transform how classroom learning takes place. Combined with the increasing integration of technology in today’s classrooms, NLP systems …...