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Found 337 papers, 23 papers with code
The Annotated Transformer
A major goal of open-source NLP is to quickly and accurately reproduce the results of new work, in a manner that the community can easily use and modify.
CAMeL Tools: An Open Source Python Toolkit for Arabic Natural Language Processing
We present CAMeL Tools, a collection of open-source tools for Arabic natural language processing in Python.
TARGER: Neural Argument Mining at Your Fingertips
We present TARGER, an open source neural argument mining framework for tagging arguments in free input texts and for keyword-based retrieval of arguments from an argument-tagged web-scale corpus.
Graph-Based Meaning Representations: Design and Processing
This tutorial is on representing and processing sentence meaning in the form of labeled directed graphs.
EstNLTK - NLP Toolkit for Estonian
Although there are many tools for natural language processing tasks in Estonian, these tools are very loosely interoperable, and it is not easy to build practical applications on top of them.
Training for Diversity in Image Paragraph Captioning
Image paragraph captioning models aim to produce detailed descriptions of a source image.
Enriching the WebNLG corpus
This paper describes the enrichment of WebNLG corpus (Gardent et al., 2017a, b), with the aim to further extend its usefulness as a resource for evaluating common NLG tasks, including Discourse Ordering, Lexicalization and Referring Expression Generation.
IARM: Inter-Aspect Relation Modeling with Memory Networks in Aspect-Based Sentiment Analysis
Sentiment analysis has immense implications in e-commerce through user feedback mining.
Practical, Efficient, and Customizable Active Learning for Named Entity Recognition in the Digital Humanities
Scholars in inter-disciplinary fields like the Digital Humanities are increasingly interested in semantic annotation of specialized corpora.
Transfer Learning for Entity Recognition of Novel Classes
Our results empirically demonstrate when each of the published approaches tends to do well.
Entity Extraction using GAN
Named Entity Recognition (NER)
+2
Unsupervised Parallel Sentence Extraction with Parallel Segment Detection Helps Machine Translation
Mining parallel sentences from comparable corpora is important.
Evaluating bilingual word embeddings on the long tail
Bilingual word embeddings are useful for bilingual lexicon induction, the task of mining translations of given words.
Using Language Learner Data for Metaphor Detection
This article describes the system that participated in the shared task on metaphor detection on the Vrije University Amsterdam Metaphor Corpus (VUA).
Automated learning of templates for data-to-text generation: comparing rule-based, statistical and neural methods
The current study investigated novel techniques and methods for trainable approaches to data-to-text generation.
A Dataset for Noun Compositionality Detection for a Slavic Language
This paper presents the first gold-standard resource for Russian annotated with compositionality information of noun compounds.
Large-Scale Transfer Learning for Natural Language Generation
Large-scale pretrained language models define state of the art in natural language processing, achieving outstanding performance on a variety of tasks.
Aspect-based summarization of pros and cons in unstructured product reviews
In the second evaluation, the gold-standard pros and cons were assessed along with the system output.
Two Methods for Domain Adaptation of Bilingual Tasks: Delightfully Simple and Broadly Applicable
Bilingual tasks, such as bilingual lexicon induction and cross-lingual classification, are crucial for overcoming data sparsity in the target language.
Surface Realization Shared Task 2018 (SR18): The Tilburg University Approach
This study describes the approach developed by the Tilburg University team to the shallow task of the Multilingual Surface Realization Shared Task 2018 (SR18).
SatiricLR: a Language Resource of Satirical News Articles
We test the viability of our data on the task of classification of satire.
Statistical Models for Unsupervised, Semi-Supervised Supervised Transliteration Mining
After training, the unlabeled data is disambiguated based on the posterior probabilities of the two sub-models.
Discourse Coherence: Concurrent Explicit and Implicit Relations
Theories of discourse coherence posit relations between discourse segments as a key feature of coherent text.
Addressing Noise in Multidialectal Word Embeddings
Arabic dialects lack large corpora and are noisy, being linguistically disparate with no standardized spelling.
DeepPavlov: Open-Source Library for Dialogue Systems
It supports modular as well as end-to-end approaches to implementation of conversational agents.
Generating Contrastive Referring Expressions
The referring expressions (REs) produced by a natural language generation (NLG) system can be misunderstood by the hearer, even when they are semantically correct.
Unsupervised Does Not Mean Uninterpretable: The Case for Word Sense Induction and Disambiguation
On the example of word sense induction and disambiguation (WSID), we show that it is possible to develop an interpretable model that matches the state-of-the-art models in accuracy.
The ContrastMedium Algorithm: Taxonomy Induction From Noisy Knowledge Graphs With Just A Few Links
In this paper, we present ContrastMedium, an algorithm that transforms noisy semantic networks into full-fledged, clean taxonomies.
Generating flexible proper name references in text: Data, models and evaluation
The model relies on the REGnames corpus, a dataset with 53, 102 proper name references to 1, 000 people in different discourse contexts.
Producing Unseen Morphological Variants in Statistical Machine Translation
Translating into morphologically rich languages is difficult.
Addressing Problems across Linguistic Levels in SMT: Combining Approaches to Model Morphology, Syntax and Lexical Choice
Many errors in phrase-based SMT can be attributed to problems on three linguistic levels: morphological complexity in the target language, structural differences and lexical choice.
Alto: Rapid Prototyping for Parsing and Translation
We present Alto, a rapid prototyping tool for new grammar formalisms.
Audience Segmentation in Social Media
Understanding the social media audience is becoming increasingly important for social media analysis.
A tool for extracting sense-disambiguated example sentences through user feedback
This paper describes an application system aimed to help lexicographers in the extraction of example sentences for a given headword based on its different senses.
Noise-Robust Morphological Disambiguation for Dialectal Arabic
User-generated text tends to be noisy with many lexical and orthographic inconsistencies, making natural language processing (NLP) tasks more challenging.
PunFields at SemEval-2018 Task 3: Detecting Irony by Tools of Humor Analysis
The paper describes our search for a universal algorithm of detecting intentional lexical ambiguity in different forms of creative language.
ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings
In this paper we describe our system for SemEval-2018 Task 7 on classification of semantic relations in scientific literature for clean (subtask 1. 1) and noisy data (subtask 1. 2).
UMD at SemEval-2018 Task 10: Can Word Embeddings Capture Discriminative Attributes?
We describe the University of Maryland{'}s submission to SemEval-018 Task 10, {``}Capturing Discriminative Attributes{''}: given word triples (w1, w2, d), the goal is to determine whether d is a discriminating attribute belonging to w1 but not w2.
Modeling Second-Language Learning from a Psychological Perspective
Psychological research on learning and memory has tended to emphasize small-scale laboratory studies.
Complex Word Identification: Convolutional Neural Network vs. Feature Engineering
We describe the systems of NLP-CIC team that participated in the Complex Word Identification (CWI) 2018 shared task.
Literal, Metphorical or Both? Detecting Metaphoricity in Isolated Adjective-Noun Phrases
The paper addresses the classification of isolated Polish adjective-noun phrases according to their metaphoricity.
Detecting Figurative Word Occurrences Using Recurrent Neural Networks
The paper addresses detection of figurative usage of words in English text.
Multi-Module Recurrent Neural Networks with Transfer Learning
This paper describes multiple solutions designed and tested for the problem of word-level metaphor detection.
OpenNMT System Description for WNMT 2018: 800 words/sec on a single-core CPU
We present a system description of the OpenNMT Neural Machine Translation entry for the WNMT 2018 evaluation.
Aggression Detection in Social Media: Using Deep Neural Networks, Data Augmentation, and Pseudo Labeling
On this task, we investigate the efficacy of deep neural network models of varying complexity.
Debugging Sequence-to-Sequence Models with Seq2Seq-Vis
Neural attention-based sequence-to-sequence models (seq2seq) (Sutskever et al., 2014; Bahdanau et al., 2014) have proven to be accurate and robust for many sequence prediction tasks.
Complementary Strategies for Low Resourced Morphological Modeling
Morphologically rich languages are challenging for natural language processing tasks due to data sparsity.
Automatic Identification of Drugs and Adverse Drug Reaction Related Tweets
We describe our submissions to the Third Social Media Mining for Health Applications Shared Task.
Coreference and Coherence in Neural Machine Translation: A Study Using Oracle Experiments
We show that NMT models taking advantage of context oracle signals can achieve considerable gains in BLEU, of up to 7. 02 BLEU for coreference and 1. 89 BLEU for coherence on subtitles translation.
PROMT Systems for WMT 2018 Shared Translation Task
This paper describes the PROMT submissions for the WMT 2018 Shared News Translation Task.
The Karlsruhe Institute of Technology Systems for the News Translation Task in WMT 2018
We present our experiments in the scope of the news translation task in WMT 2018, in directions: English→German.
The LMU Munich Unsupervised Machine Translation Systems
We describe LMU Munich{'}s unsupervised machine translation systems for English↔German translation.
LMU Munich's Neural Machine Translation Systems at WMT 2018
The systems were used for our participation in the WMT18 biomedical translation task and in the shared task on machine translation of news.
An Unsupervised System for Parallel Corpus Filtering
In this paper we describe LMU Munich{'}s submission for the \textit{WMT 2018 Parallel Corpus Filtering} shared task which addresses the problem of cleaning noisy parallel corpora.
Sentence Packaging in Text Generation from Semantic Graphs as a Community Detection Problem
An increasing amount of research tackles the challenge of text generation from abstract ontological or semantic structures, which are in their very nature potentially large connected graphs.
E2E NLG Challenge Submission: Towards Controllable Generation of Diverse Natural Language
In natural language generation (NLG), the task is to generate utterances from a more abstract input, such as structured data.
Understanding the Semantics of Narratives of Interpersonal Violence through Reader Annotations and Physiological Reactions
Interpersonal violence (IPV) is a prominent sociological problem that affects people of all demographic backgrounds.
Using Linked Disambiguated Distributional Networks for Word Sense Disambiguation
We introduce a new method for unsupervised knowledge-based word sense disambiguation (WSD) based on a resource that links two types of sense-aware lexical networks: one is induced from a corpus using distributional semantics, the other is manually constructed.
Supervised and Unsupervised Word Sense Disambiguation on Word Embedding Vectors of Unambigous Synonyms
This paper compares two approaches to word sense disambiguation using word embeddings trained on unambiguous synonyms.
Parameter Free Hierarchical Graph-Based Clustering for Analyzing Continuous Word Embeddings
Word embeddings are high-dimensional vector representations of words and are thus difficult to interpret.
Linguistic realisation as machine translation: Comparing different MT models for AMR-to-text generation
In this paper, we study AMR-to-text generation, framing it as a translation task and comparing two different MT approaches (Phrase-based and Neural MT).
PASS: A Dutch data-to-text system for soccer, targeted towards specific audiences
We present PASS, a data-to-text system that generates Dutch soccer reports from match statistics.
Integrated sentence generation using charts
Integrating surface realization and the generation of referring expressions into a single algorithm can improve the quality of the generated sentences.
Coarse-to-Fine Attention Models for Document Summarization
Sequence-to-sequence models with attention have been successful for a variety of NLP problems, but their speed does not scale well for tasks with long source sequences such as document summarization.
Ranked #25 on
Document Summarization
on CNN / Daily Mail
A Multimodal Dialogue System for Medical Decision Support inside Virtual Reality
We present a multimodal dialogue system that allows doctors to interact with a medical decision support system in virtual reality (VR).
Coarse-To-Fine Parsing for Expressive Grammar Formalisms
We generalize coarse-to-fine parsing to grammar formalisms that are more expressive than PCFGs and/or describe languages of trees or graphs.
Entity-Centric Information Access with Human in the Loop for the Biomedical Domain
In this paper, we describe the concept of entity-centric information access for the biomedical domain.
Challenges and Solutions for Latin Named Entity Recognition
Although spanning thousands of years and genres as diverse as liturgy, historiography, lyric and other forms of prose and poetry, the body of Latin texts is still relatively sparse compared to English.
Towards grounding computational linguistic approaches to readability: Modeling reader-text interaction for easy and difficult texts
Computational approaches to readability assessment are generally built and evaluated using gold standard corpora labeled by publishers or teachers rather than being grounded in observations about human performance.
A Comparison Between Morphological Complexity Measures: Typological Data vs. Language Corpora
Language complexity is an intriguing phenomenon argued to play an important role in both language learning and processing.
Unsupervised Abbreviation Detection in Clinical Narratives
The disambiguation of period characters is therefore an important task for sentence and abbreviation detection.
Evaluating the text quality, human likeness and tailoring component of PASS: A Dutch data-to-text system for soccer
We present an evaluation of PASS, a data-to-text system that generates Dutch soccer reports from match statistics which are automatically tailored towards fans of one club or the other.
KIT Lecture Translator: Multilingual Speech Translation with One-Shot Learning
{\%} Combining these techniques, we are able to provide an adapted speech translation system for several European languages.
LTV: Labeled Topic Vector
In this paper we present LTV, a website and API that generates labeled topic classifications based on the Dewey Decimal Classification (DDC), an international standard for topic classification in libraries.
A Proposition-Based Abstractive Summariser
It is a further development of an existing summariser that has an incremental, proposition-based content selection process but lacks a natural language (NL) generator for the final output.
TextImager: a Distributed UIMA-based System for NLP
More and more disciplines require NLP tools for performing automatic text analyses on various levels of linguistic resolution.
Interactive Relation Extraction in Main Memory Database Systems
We present INDREX-MM, a main memory database system for interactively executing two interwoven tasks, declarative relation extraction from text and their exploitation with SQL.
TASTY: Interactive Entity Linking As-You-Type
We introduce TASTY (Tag-as-you-type), a novel text editor for interactive entity linking as part of the writing process.
Event Ordering with a Generalized Model for Sieve Prediction Ranking
Within this prediction reranking framework, we propose an alternative scoring function, showing an 8. 8{\%} relative gain over the original CAEVO.
NITMZ-JU at IJCNLP-2017 Task 4: Customer Feedback Analysis
In this paper, we describe a deep learning framework for analyzing the customer feedback as part of our participation in the shared task on Customer Feedback Analysis at the 8th International Joint Conference on Natural Language Processing (IJCNLP 2017).
Detecting Metaphorical Phrases in the Polish Language
In this paper we describe experiments with automated detection of metaphors in the Polish language.
Word Sense Disambiguation with Recurrent Neural Networks
This paper presents a neural network architecture for word sense disambiguation (WSD).
