NLPExplorer

Preslav Nakov

Number of Papers:- 173

Number of Citations:- 1105

First ACL Paper:- 2003

Latest ACL Paper:- 2021

Venues:-

WASSA

SEW

NLP4IF

WMT

ACL

EMNLP

SemEval

EXprom

NAACL

IWSLT

BSNLP

DiscoMT

Findings

COLING

MWE

TACL

LT4VAR

CoNLL

BioNLP

HLT

VarDial

IJCNLP

RANLP

WANLP

*SEMEVAL

EACL

Co-Authors:-

Similar Authors:-

Slav-NER: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic Languages BSNLP EACL

Proceedings of the Eighth Workshop on NLP for Similar Languages, Varieties and Dialects EACL VarDial

Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing BSNLP EACL

Proceedings of the Fourth Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda NAACL NLP4IF

Anna Feldman | Giovanni Da San Martino | Chris Leberknight | Preslav Nakov |

Findings of the NLP4IF-2021 Shared Tasks on Fighting the COVID-19 Infodemic and Censorship Detection NAACL NLP4IF

AraStance: A Multi-Country and Multi-Domain Dataset of Arabic Stance Detection for Fact Checking NAACL NLP4IF

SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images ACL IJCNLP SemEval

COVID-19 in Bulgarian Social Media: Factuality, Harmfulness, Propaganda, and Framing RANLP

Cross-Domain Label-Adaptive Stance Detection EMNLP

Momchil Hardalov | Arnav Arora | Preslav Nakov | Isabelle Augenstein |

RuleBERT: Teaching Soft Rules to Pre-Trained Language Models EMNLP

Mohammed Saeed | Naser Ahmadi | Preslav Nakov | Paolo Papotti |

A Second Pandemic? Analysis of Fake News about COVID-19 Vaccines in Qatar RANLP

Interpretable Propaganda Detection in News Articles RANLP

MOMENTA: A Multimodal Framework for Detecting Harmful Memes and Their Targets EMNLP Findings

Fighting the COVID-19 Infodemic: Modeling the Perspective of Journalists, Fact-Checkers, Social Media Platforms, Policy Makers, and the Society EMNLP Findings

SOLID: A Large-Scale Semi-Supervised Dataset for Offensive Language Identification Findings

Detecting Harmful Memes and Their Targets Findings

Compressing Large-Scale Transformer-Based Models: A Case Study on BERT TACL

Generating Answer Candidates for Quizzes and Answer-Aware Question Generators RANLP

Detecting Propaganda Techniques in Memes ACL IJCNLP

Predicting the Factuality of Reporting of News Media Using Observations about User Attention in Their YouTube Channels RANLP

That is a Known Lie: Detecting Previously Fact-Checked Claims ACL

Shaden Shaar | Nikolay Babulkov | Giovanni Da San Martino | Preslav Nakov |

Prta: A System to Support the Analysis of Propaganda Techniques in the News ACL

What Was Written vs. Who Read It: News Media Profiling Using Text Analysis and Social Media Context ACL

Predicting the Topical Stance and Political Leaning of Media using Tweets ACL

Peter Stefanov | Kareem Darwish | Atanas Atanasov | Preslav Nakov |

Proceedings of the 7th Workshop on NLP for Similar Languages, Varieties and Dialects COLING VarDial

SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020) COLING SemEval

SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles COLING SemEval

Aschern at SemEval-2020 Task 11: It Takes Three to Tango: RoBERTa, CRF, and Transfer Learning COLING SemEval

Anton Chernyavskiy | Dmitry Ilvovsky | Preslav Nakov |

Proceedings of the 3rd NLP4IF Workshop on NLP for Internet Freedom: Censorship, Disinformation, and Propaganda COLING NLP4IF

Fact-Checking, Fake News, Propaganda, and Media Bias: Truth Seeking in the Post-Truth Era EMNLP

Preslav Nakov | Giovanni Da San Martino |

Vector-Vector-Matrix Architecture: A Novel Hardware-Aware Framework for Low-Latency Inference in NLP Applications EMNLP

EXAMS: A Multi-subject High School Examinations Dataset for Cross-lingual and Multilingual Question Answering EMNLP

We Can Detect Your Bias: Predicting the Political Ideology of News Articles EMNLP

Ramy Baly | Giovanni Da San Martino | James Glass | Preslav Nakov |

Fact-Checking Meets Fauxtography: Verifying Claims About Images EMNLP

Dimitrina Zlatkova | Preslav Nakov | Ivan Koychev |

Evaluating Pronominal Anaphora in Machine Translation: An Evaluation Measure and a Test Suite EMNLP

Prathyusha Jwalapuram | Shafiq Joty | Irina Temnikova | Preslav Nakov |

Contrastive Language Adaptation for Cross-Lingual Stance Detection EMNLP

Mitra Mohtarami | James Glass | Preslav Nakov |

Fine-Grained Analysis of Propaganda in News Article EMNLP

Tanbih: Get To Know What You Are Reading EMNLP

Proceedings of the Second Workshop on Natural Language Processing for Internet Freedom: Censorship, Disinformation, and Propaganda EMNLP WS

Findings of the NLP4IF-2019 Shared Task on Fine-Grained Propaganda Detection EMNLP WS

Giovanni Da San Martino | Alberto Barrón-Cedeño | Preslav Nakov |

Predicting the Role of Political Trolls in Social Media CoNLL

Atanas Atanasov | Gianmarco De Francisci Morales | Preslav Nakov |

Predicting the Type and Target of Offensive Posts in Social Media NAACL

One Size Does Not Fit All: Comparing NMT Representations of Different Granularities NAACL

Multi-Task Ordinal Regression for Jointly Predicting the Trustworthiness and the Leading Political Ideology of News Media NAACL

Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts ACL

Preslav Nakov | Alexis Palmer |

Rotational Unit of Memory: A Novel Representation Unit for RNNs with Scalable Applications TACL

SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval) *SEMEVAL

SemEval-2019 Task 8: Fact Checking in Community Question Answering Forums *SEMEVAL

Team Jack Ryder at SemEval-2019 Task 4: Using BERT Representations for Detecting Hyperpartisan News *SEMEVAL

Daniel Shaprin | Giovanni Da San Martino | Alberto Barrón-Cedeño | Preslav Nakov |

Team QCRI-MIT at SemEval-2019 Task 4: Propaganda Analysis Meets Hyperpartisan News Detection *SEMEVAL

Proceedings of the Sixth Workshop on NLP for Similar Languages, Varieties and Dialects NAACL WS

Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing ACL WS

It Takes Nine to Smell a Rat: Neural Multi-Task Learning for Check-Worthiness Prediction RANLP

Detecting Toxicity in News Articles: Application to Bulgarian RANLP

Yoan Dinkov | Ivan Koychev | Preslav Nakov |

A Morpho-Syntactically Informed LSTM-CRF Model for Named Entity Recognition RANLP

Lilia Simeonova | Kiril Simov | Petya Osenova | Preslav Nakov |

Beyond English-Only Reading Comprehension: Experiments in Zero-shot Multilingual Transfer for Bulgarian RANLP

Momchil Hardalov | Ivan Koychev | Preslav Nakov |

Adversarial Domain Adaptation for Duplicate Question Detection EMNLP

Predicting Factuality of Reporting and Bias of News Media Sources EMNLP

Joint Multitask Learning for Community Question Answering Using Task-Specific Embeddings EMNLP

Shafiq Joty | Lluís Màrquez | Preslav Nakov |

Automatic Stance Detection Using End-to-End Memory Networks NAACL

Integrating Stance Detection and Fact Checking in a Unified Corpus NAACL

ClaimRank: Detecting Check-Worthy Claims in Arabic and English NAACL

Proceedings of the Fifth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial 2018) COLING VarDial WS

Language Identification and Morphosyntactic Tagging: The Second VarDial Evaluation Campaign COLING VarDial WS

Proceedings of the IJCNLP 2017, Shared Tasks IJCNLP

Chao-Hong Liu | Preslav Nakov | Nianwen Xue |

Discourse Structure in Machine Translation Evaluation CL

Shafiq Joty | Francisco Guzmán | Lluís Màrquez | Preslav Nakov |

Cross-language Learning with Adversarial Neural Networks CoNLL

Shafiq Joty | Preslav Nakov | Lluís Màrquez | Israa Jaradat |

Building Chatbots from Forum Data: Model Selection Using Question Answering Metrics RANLP

A Context-Aware Approach for Detecting Worth-Checking Claims in Political Debates RANLP

We Built a Fake News / Click Bait Filter: What Happened Next Will Blow Your Mind! RANLP

Georgi Karadzhov | Pepa Gencheva | Preslav Nakov | Ivan Koychev |

Fully Automated Fact Checking Using External Sources RANLP

Robust Tuning Datasets for Statistical Machine Translation RANLP

Preslav Nakov | Stephan Vogel |

Do Not Trust the Trolls: Predicting Credibility in Community Question Answering Forums RANLP

SemEval-2017 Task 3: Community Question Answering *SEMEVAL

SemEval-2017 Task 4: Sentiment Analysis in Twitter *SEMEVAL

Sara Rosenthal | Noura Farra | Preslav Nakov |

Proceedings of the Fourth Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial) VarDial WS

Findings of the VarDial Evaluation Campaign 2017 VarDial WS

Findings of the 2017 DiscoMT Shared Task on Cross-lingual Pronoun Prediction DiscoMT WS

On the Impact of Seed Words on Sentiment Polarity Lexicon Induction COLING

Dame Jovanoski | Veno Pachovski | Preslav Nakov |

An Interactive System for Exploring Community Question Answering Forums COLING

It Takes Three to Tango: Triangulation Approach to Answer Ranking in Community Question Answering EMNLP

Preslav Nakov | Lluís Màrquez | Francisco Guzmán |

Source Language Adaptation Approaches for Resource-Poor Machine Translation CL

Pidong Wang | Preslav Nakov | Hwee Tou Ng |

Joint Learning with Global Inference for Comment Classification in Community Question Answering NAACL

Shafiq Joty | Lluís Màrquez | Preslav Nakov |

Hunting for Troll Comments in News Community Forums ACL

Todor Mihaylov | Preslav Nakov |

Machine Translation Evaluation Meets Community Question Answering ACL

Francisco Guzmán | Lluís Màrquez | Preslav Nakov |

SemEval-2016 Task 4: Sentiment Analysis in Twitter *SEMEVAL

SemEval-2016 Task 3: Community Question Answering *SEMEVAL

SUper Team at SemEval-2016 Task 3: Building a Feature-Rich System for Community Question Answering *SEMEVAL

PMI-cool at SemEval-2016 Task 3: Experiments with PMI and Goodness Polarity Lexicons for Community Question Answering *SEMEVAL

Daniel Balchev | Yasen Kiprov | Ivan Koychev | Preslav Nakov |

SemanticZ at SemEval-2016 Task 3: Ranking Relevant Answers in Community Question Answering Using Semantic Similarity Based on Fine-tuned Word Embeddings *SEMEVAL

Todor Mihaylov | Preslav Nakov |

MTE-NN at SemEval-2016 Task 3: Can Machine Translation Evaluation Help Community Question Answering? *SEMEVAL

Francisco Guzmán | Preslav Nakov | Lluís Màrquez |

Sentiment Analysis in Twitter: A SemEval Perspective WASSA WS

Preslav Nakov |

Proceedings of the 12th Workshop on Multiword Expressions MWE WS

Findings of the 2016 WMT Shared Task on Cross-lingual Pronoun Prediction WMT WS

Proceedings of the Third Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial3) VarDial WS

Discriminating between Similar Languages and Arabic Dialect Identification: A Report on the Third DSL Shared Task VarDial WS

Negation and Modality in Machine Translation EXprom WS

Preslav Nakov |

Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016) SemEval

Global Thread-level Inference for Comment Classification in Community Question Answering EMNLP

Analyzing Optimization for Statistical Machine Translation: MERT Learns Verbosity, PRO Learns Length CoNLL

Francisco Guzmán | Preslav Nakov | Stephan Vogel |

Finding Opinion Manipulation Trolls in News Community Forums CoNLL

Todor Mihaylov | Georgi Georgiev | Preslav Nakov |

Pairwise Neural Machine Translation Evaluation ACL IJCNLP

Francisco Guzmán | Shafiq Joty | Lluís Màrquez | Preslav Nakov |

Thread-Level Information for Comment Classification in Community Question Answering ACL IJCNLP

Sentiment Analysis in Twitter for Macedonian RANLP

Dame Jovanoski | Veno Pachovski | Preslav Nakov |

Fine-Grained Sentiment Analysis for Movie Reviews in Bulgarian RANLP

Borislav Kapukaranov | Preslav Nakov |

Exposing Paid Opinion Manipulation Trolls RANLP

Todor Mihaylov | Ivan Koychev | Georgi Georgiev | Preslav Nakov |

Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015) *SEMEVAL

Preslav Nakov | Torsten Zesch | Daniel Cer | David Jurgens |

QCRI: Answer Selection for Community Question Answering - Experiments for Arabic and English *SEMEVAL

SemEval-2015 Task 3: Answer Selection in Community Question Answering *SEMEVAL

SemEval-2015 Task 10: Sentiment Analysis in Twitter *SEMEVAL

Pronoun-Focused MT and Cross-Lingual Pronoun Prediction: Findings of the 2015 DiscoMT Shared Task on Pronoun Translation DiscoMT WS

The Web as an Implicit Training Set: Application to Noun Compounds Syntax and Semantics WS

Preslav Nakov |

Proceedings of the Joint Workshop on Language Technology for Closely Related Languages, Varieties and Dialects LT4VAR WS

Overview of the DSL Shared Task 2015 LT4VAR WS

A Study of using Syntactic and Semantic Structures for Concept Segmentation and Labeling COLING

Learning to Differentiate Better from Worse Translations EMNLP

Semantic Kernels for Semantic Parsing EMNLP

Predicting Dialect Variation in Immigrant Contexts Using Light Verb Constructions EMNLP

A. Seza Doğruöz | Preslav Nakov |

Using Discourse Structure Improves Machine Translation Evaluation ACL

Francisco Guzmán | Shafiq Joty | Lluís Màrquez | Preslav Nakov |

Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014) *SEMEVAL

Preslav Nakov | Torsten Zesch |

SemEval-2014 Task 9: Sentiment Analysis in Twitter *SEMEVAL

Sara Rosenthal | Alan Ritter | Preslav Nakov | Veselin Stoyanov |

SU-FMI: System Description for SemEval-2014 Task 9 on Sentiment Analysis in Twitter *SEMEVAL

DiscoTK: Using Discourse Structure for Machine Translation Evaluation WMT WS

Shafiq Joty | Francisco Guzmán | Lluís Màrquez | Preslav Nakov |

Unsupervised Word Segmentation Improves Dialectal Arabic to English Machine Translation WANLP WS

Proceedings of the EMNLP’2014 Workshop on Language Technology for Closely Related Languages and Language Variants LT4VAR WS

Preslav Nakov | Petya Osenova | Cristina Vertan |

A Tale about PRO and Monsters ACL

Preslav Nakov | Francisco Guzmán | Stephan Vogel |

51st Annual Meeting of the Association for Computational Linguistics Proceedings of the Student Research Workshop ACL

Parameter Optimization for Statistical Machine Translation: It Pays to Learn from Hard Examples RANLP

Preslav Nakov | Fahad Al Obaidli | Francisco Guzmán | Stephan Vogel |

Analyzing the Use of Character-Level Translation with Sparse and Noisy Datasets RANLP

Jörg Tiedemann | Preslav Nakov |

SemEval-2013 Task 4: Free Paraphrases of Noun Compounds *SEMEVAL

SemEval-2013 Task 2: Sentiment Analysis in Twitter *SEMEVAL

Proceedings of the Joint Workshop on NLP&LOD and SWAIE: Semantic Web, Linked Open Data and Information Extraction WS

Combining, Adapting and Reusing Bi-texts between Related Languages: Application to Statistical Machine Translation (invited talk) WS

Preslav Nakov |

Proceedings of the Workshop on Multiword Expressions: Identification, Interpretation, Disambiguation and Applications (MWE 2009) WS

Dimitra Anastasiou | Chikara Hashimoto | Preslav Nakov | Su Nam Kim |

Improving English-Spanish Statistical Machine Translation: Experiments in Domain Adaptation, Sentence Paraphrasing, Tokenization, and Recasing WMT WS

Preslav Nakov |