NLPExplorer

Julie Weeds

Number of Papers:- 24

Number of Citations:- 327

First ACL Paper:- 2003

Latest ACL Paper:- 2022

Venues:-

EACL

CVSC

IJCNLP

RepL4NLP

ACL

Findings

*SEMEVAL

COLING

RepEval

SENSE

EMNLP

WANLP

Co-Authors:-

Similar Authors:-

Predicate-Argument Based Bi-Encoder for Paraphrase Identification ACL

Qiwei Peng | David Weir | Julie Weeds | Yekun Chai |

Testing Large Language Models on Compositionality and Inference with Phrase-Level Adjective-Noun Entailment COLING

Lorenzo Bertolini | Julie Weeds | David Weir |

MuSeCLIR: A Multiple Senses and Cross-lingual Information Retrieval Dataset COLING

Wing Yan Li | Julie Weeds | David Weir |

Towards Structure-aware Paraphrase Identification with Phrase Alignment Using Sentence Encoders COLING

Qiwei Peng | David Weir | Julie Weeds |

Data Augmentation for Hypernymy Detection EACL

Thomas Kober | Julie Weeds | Lorenzo Bertolini | David Weir |

Structure-aware Sentence Encoder in Bert-Based Siamese Network ACL IJCNLP RepL4NLP

Qiwei Peng | David Weir | Julie Weeds |

Representing Syntax and Composition with Geometric Transformations Findings

Lorenzo Bertolini | Julie Weeds | David Weir | Qiwei Peng |

Embed More Ignore Less (EMIL): Exploiting Enriched Representations for Arabic NLP COLING WANLP

Ahmed Younes | Julie Weeds |

When a Red Herring in Not a Red Herring: Using Compositional Methods to Detect Non-Compositional Phrases EACL

Julie Weeds | Thomas Kober | Jeremy Reffin | David Weir |

Improving Semantic Composition with Offset Inference ACL

Thomas Kober | Julie Weeds | Jeremy Reffin | David Weir |

One Representation per Word - Does it make Sense for Composition? SENSE WS

Improving Sparse Word Representations with Distributional Inference for Semantic Composition EMNLP

Thomas Kober | Julie Weeds | Jeremy Reffin | David Weir |

Aligning Packed Dependency Trees: A Theory of Composition for Distributional Semantics CL

David Weir | Julie Weeds | Jeremy Reffin | Thomas Kober |

A critique of word similarity as a method for evaluating distributional semantic models RepEval WS

Learning to Distinguish Hypernyms and Co-Hyponyms COLING

Distributional Composition using Higher-Order Dependency Vectors CVSC WS

Julie Weeds | David Weir | Jeremy Reffin |

Unsupervised Acquisition of Predominant Word Senses CL

Diana McCarthy | Rob Koeling | Julie Weeds | John Carroll |

Co-occurrence Retrieval: A Flexible Framework for Lexical Distributional Similarity CL

Julie Weeds | David Weir |

The Distributional Similarity of Sub-Parses WS

Julie Weeds | David Weir | Bill Keller |

Characterising Measures of Lexical Distributional Similarity COLING

Julie Weeds | David Weir | Diana McCarthy |

Automatic Identification of Infrequent Word Senses COLING

Diana McCarthy | Rob Koeling | Julie Weeds | John Carroll |

Finding Predominant Word Senses in Untagged Text ACL

Diana McCarthy | Rob Koeling | Julie Weeds | John Carroll |

Using automatically acquired predominant senses for Word Sense Disambiguation *SEMEVAL WS

Diana McCarthy | Rob Koeling | Julie Weeds | John Carroll |

A General Framework for Distributional Similarity EMNLP WS

Julie Weeds | David Weir |