NLPExplorer

Ted Pedersen

Number of Papers:- 68

Number of Citations:- 463

First ACL Paper:- 1996

Latest ACL Paper:- 2023

Venues:-

TeachingNLP

BioNLP

*SEMEVAL

HLT

NAACL

Louhi

LREC

EMNLP

SemEval

SocialNLP

CoNLL

ANLP

CLPsych

ACL

EACL

IJCNLP

COLING

Co-Authors:-

Similar Authors:-

DuluthNLP at SemEval-2023 Task 12: AfriSenti-SemEval: Sentiment Analysis for Low-resource African Languages using Twitter Dataset SemEval

Samuel Akrah | Ted Pedersen |

DuluthNLP at SemEval-2022 Task 7: Classifying Plausible Alternatives with Pre–trained ELECTRA NAACL SemEval

Samuel Akrah | Ted Pedersen |

Proceedings of the Fifth Workshop on Teaching NLP NAACL TeachingNLP

Duluth at SemEval-2021 Task 11: Applying DeBERTa to Contributing Sentence Selection and Dependency Parsing for Entity Extraction ACL IJCNLP SemEval

Anna Martin | Ted Pedersen |

SemEval-2021 Task 11: NLPContributionGraph - Structuring Scholarly NLP Contributions for a Research Knowledge Graph ACL IJCNLP SemEval

Jennifer D’Souza | Sören Auer | Ted Pedersen |

Duluth at SemEval-2020 Task 7: Using Surprise as a Key to Unlock Humorous Headlines COLING SemEval

Shuning Jin | Yue Yin | XianE Tang | Ted Pedersen |

Duluth at SemEval-2020 Task 12: Offensive Tweet Identification in English with Logistic Regression COLING SemEval

Ted Pedersen |

Duluth at SemEval-2019 Task 6: Lexical Approaches to Identify and Categorize Offensive Tweets *SEMEVAL

Ted Pedersen |

Duluth at SemEval-2019 Task 4: The Pioquinto Manterola Hyperpartisan News Detector *SEMEVAL

Saptarshi Sengupta | Ted Pedersen |

UMDSub at SemEval-2018 Task 2: Multilingual Emoji Prediction Multi-channel Convolutional Neural Network on Subword Embedding *SEMEVAL

Zhenduo Wang | Ted Pedersen |

Duluth UROP at SemEval-2018 Task 2: Multilingual Emoji Prediction with Ensemble Learning and Oversampling *SEMEVAL

Shuning Jin | Ted Pedersen |

ALANIS at SemEval-2018 Task 3: A Feature Engineering Approach to Irony Detection in English Tweets *SEMEVAL

Kevin Swanberg | Madiha Mirza | Ted Pedersen | Zhenduo Wang |

UMDuluth-CS8761 at SemEval-2018 Task9: Hypernym Discovery using Hearst Patterns, Co-occurrence frequencies and Word Embeddings *SEMEVAL

Arshia Zernab Hassan | Manikya Swathi Vallabhajosyula | Ted Pedersen |

Duluth at SemEval-2017 Task 6: Language Models in Humor Detection *SEMEVAL

Xinru Yan | Ted Pedersen |

Duluth at SemEval-2017 Task 7 : Puns Upon a Midnight Dreary, Lexical Semantics for the Weak and Weary *SEMEVAL

Ted Pedersen |

Improving Correlation with Human Judgments by Integrating Semantic Similarity with Second–Order Vectors BioNLP WS

Bridget McInnes | Ted Pedersen |

Age and Gender Prediction on Health Forum Data LREC

Duluth at SemEval 2016 Task 14: Extending Gloss Overlaps to Enrich Semantic Taxonomies *SEMEVAL

Ted Pedersen |

UMNDuluth at SemEval-2016 Task 14: WordNet’s Missing Lemmas *SEMEVAL

Jon Rusert | Ted Pedersen |

Semi-supervised CLPsych 2016 Shared Task System Submission WS

Analysis of Anxious Word Usage on Online Health Forums Louhi WS

Why Do They Leave: Modeling Participation in Online Depression Forums SocialNLP WS

Duluth: Word Sense Discrimination in the Service of Lexicography *SEMEVAL

Ted Pedersen |

Screening Twitter Users for Depression and PTSD with Lexical Decision Lists CLPsych WS

Ted Pedersen |

Predicting Continued Participation in Online Health Forums Louhi WS

Duluth : Measuring Cross-Level Semantic Similarity with First and Second Order Dictionary Overlaps *SEMEVAL

Ted Pedersen |

UMLS::Similarity: Measuring the Relatedness and Similarity of Biomedical Concepts NAACL

Offspring from Reproduction Problems: What Replication Failure Teaches Us ACL

Duluth : Word Sense Induction Applied to Web Page Clustering *SEMEVAL

Ted Pedersen |

Duluth : Measuring Degrees of Relational Similarity with the Gloss Vector Measure of Semantic Relatedness *SEMEVAL

Ted Pedersen |

Using Second-order Vectors in a Knowledge-based Method for Acronym Disambiguation CoNLL WS

The Ngram Statistics Package (Text::NSP) : A Flexible Tool for Identifying Ngrams, Collocations, and Word Associations WS

Identifying Collocations to Measure Compositionality: Shared Task System Description WS

Ted Pedersen |

Information Content Measures of Semantic Similarity Perform Better Without Sense-Tagged Text NAACL

Ted Pedersen |

Duluth-WSI: SenseClusters Applied to the Sense Induction Task of SemEval-2 *SEMEVAL

Ted Pedersen |

Proceedings of the NAACL HLT 2010 Young Investigators Workshop on Computational Approaches to Languages of the Americas WS

Thamar Solorio | Ted Pedersen |

WordNet::SenseRelate::AllWords - A Broad Coverage Word Sense Tagger that Maximizes Semantic Relatedness NAACL

Ted Pedersen | Varada Kolhatkar |

Last Words: Empiricism Is Not a Matter of Faith CL

Ted Pedersen |

UMND1: Unsupervised Word Sense Disambiguation Using Contextual Semantic Relatedness *SEMEVAL

Siddharth Patwardhan | Satanjeev Banerjee | Ted Pedersen |

UMND2 : SenseClusters Applied to the Sense Induction Task of Senseval-4 *SEMEVAL

Ted Pedersen |

Determining the Syntactic Structure of Medical Terms in Clinical Notes WS

Bridget McInnes | Ted Pedersen | Serguei Pakhomov |

Selecting the “Right” Number of Senses Based on Clustering Criterion Functions EACL

Ted Pedersen | Anagha Kulkarni |

Automatic Cluster Stopping with Criterion Functions and the Gap Statistic HLT NAACL

Ted Pedersen | Anagha Kulkarni |

Improving Name Discrimination: A Language Salad Approach WS

Using WordNet-based Context Vectors to Estimate the Semantic Relatedness of Concepts WS

Siddharth Patwardhan | Ted Pedersen |

Proceedings of the ACL Interactive Poster and Demonstration Sessions ACL

Masaaki Nagata | Ted Pedersen |

SenseRelate::TargetWord—A Generalized Framework for Word Sense Disambiguation ACL

Siddharth Patwardhan | Satanjeev Banerjee | Ted Pedersen |

SenseClusters: Unsupervised Clustering and Labeling of Similar Contexts ACL

Anagha Kulkarni | Ted Pedersen |

Proceedings of the ACL Workshop on Building and Using Parallel Texts WS

Word Alignment for Languages with Scarce Resources WS

Joel Martin | Rada Mihalcea | Ted Pedersen |

SenseClusters - Finding Clusters that Represent Word Senses HLT NAACL

Amruta Purandare | Ted Pedersen |

WordNet::Similarity - Measuring the Relatedness of Concepts HLT NAACL

Ted Pedersen | Siddharth Patwardhan | Jason Michelizzi |

The Senseval-3 Multilingual English-Hindi lexical sample task *SEMEVAL WS

Timothy Chklovski | Rada Mihalcea | Ted Pedersen | Amruta Purandare |

Complementarity of lexical and simple syntactic features: The SyntaLex approach to Senseval-3 *SEMEVAL WS

Saif Mohammad | Ted Pedersen |

The Duluth lexical sample systems in Senseval-3 *SEMEVAL WS

Ted Pedersen |

Combining Lexical and Syntactic Features for Supervised Word Sense Disambiguation CoNLL WS

Saif Mohammad | Ted Pedersen |

Word Sense Discrimination by Clustering Contexts in Vector and Similarity Spaces CoNLL WS

Amruta Purandare | Ted Pedersen |

An Evaluation Exercise for Word Alignment WS

Rada Mihalcea | Ted Pedersen |

The Duluth Word Alignment System WS

Bridget Thomson McInnes | Ted Pedersen |

Assessing System Agreement and Instance Difficulty in the Lexical WS

Ted Pedersen |

Evaluating the Effectiveness of Ensembles of Decision Trees WS

Ted Pedersen |

A Decision Tree of Bigrams is an Accurate Predictor of Word Sense NAACL

Ted Pedersen |

Machine Learning with Lexical Features: The Duluth Approach to SENSEVAL-2 *SEMEVAL

Ted Pedersen |

A Simple Approach to Building Ensembles of Naive Bayesian Classifiers for Word Sense Disambiguation ANLP NAACL

Ted Pedersen |

Sequential Model Selection for Word Sense Disambiguation ANLP

Ted Pedersen | Rebecca Bruce | Janyce Wiebe |

Distinguishing Word Senses in Untagged Text EMNLP WS

Ted Pedersen | Rebecca Bruce |

A Statistical Decision Making Method: A Case Study on Prepositional Phrase Attachment CoNLL WS

Mehmet Kayaalp | Ted Pedersen | Rebecca Bruce |

The Measure of a Model EMNLP WS

Rebecca Bruce | Janyce Wiebe | Ted Pedersen |