NLPExplorer

Daniel Cer

Number of Papers:- 38

Number of Citations:- 538

First ACL Paper:- 2006

Latest ACL Paper:- 2022

Venues:-

AdaptNLP

*SEMEVAL

HLT

NAACL

LREC

WMT

SemEval

EMNLP

ACL

EACL

IJCNLP

Findings

Co-Authors:-

Aditya Barua

Aitor Gonzalez Agirre

Amin Ahmad

Austin Waters

Bill Maccartney

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Miltos Deligiannis

Jorge Antonio Leoni De Leon

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Mara Chinea Rios1

Josu Landa

SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer ACL

Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models ACL Findings

Language-agnostic BERT Sentence Embedding ACL

Overcoming Catastrophic Forgetting in Zero-Shot Cross-Lingual Generation EMNLP

Crisscrossed Captions: Extended Intramodal and Intermodal Semantic Similarity Judgments for MS-COCO EACL

MultiReQA: A Cross-Domain Evaluation forRetrieval Question Answering Models AdaptNLP EACL

Neural Retrieval for Question Answering with Cross-Attention Supervised Data Augmentation ACL IJCNLP

A Simple and Effective Method To Eliminate the Self Language Bias in Multilingual Representations EMNLP

Ziyi Yang | Yinfei Yang | Daniel Cer | Eric Darve |

Universal Sentence Representation Learning with Conditional Masked Language Model EMNLP

Multilingual Universal Sentence Encoder for Semantic Retrieval ACL

ReQA: An Evaluation for End-to-End Answer Retrieval Models EMNLP WS

Amin Ahmad | Noah Constant | Yinfei Yang | Daniel Cer |

Learning Cross-Lingual Sentence Representations via a Multi-task Dual-Encoder Model ACL WS

Hierarchical Document Encoder for Parallel Corpus Mining ACL WMT WS

Universal Sentence Encoder for English EMNLP

Learning Semantic Textual Similarity from Conversations ACL WS

Effective Parallel Corpus Mining using Bilingual Sentence Embeddings EMNLP WMT WS

Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017) *SEMEVAL

SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation *SEMEVAL

SemEval-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation *SEMEVAL

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

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

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

SemEval-2015 Task 2: Semantic Textual Similarity, English, Spanish and Pilot on Interpretability *SEMEVAL

SemEval-2014 Task 10: Multilingual Semantic Textual Similarity *SEMEVAL

Phrasal: A Toolkit for New Directions in Statistical Machine Translation WMT WS

Spence Green | Daniel Cer | Christopher Manning |

An Empirical Comparison of Features and Tuning for Phrase-based Machine Translation WMT WS

Spence Green | Daniel Cer | Christopher Manning |

Bilingual Word Embeddings for Phrase-Based Machine Translation EMNLP

Will Y. Zou | Richard Socher | Daniel Cer | Christopher D. Manning |

Fast and Adaptive Online Training of Feature-Rich Translation Models ACL

Spence Green | Sida Wang | Daniel Cer | Christopher D. Manning |

SEM 2013 shared task: Semantic Textual Similarity SEMEVAL

Feature-Rich Phrase-based Translation: Stanford University’s Submission to the WMT 2013 Translation Task WMT WS

Positive Diversity Tuning for Machine Translation System Combination WMT WS

Daniel Cer | Christopher D. Manning | Dan Jurafsky |

SemEval-2012 Task 6: A Pilot on Semantic Textual Similarity *SEMEVAL

Eneko Agirre | Daniel Cer | Mona Diab | Aitor Gonzalez-Agirre |

Stanford: Probabilistic Edit Distance Metrics for STS *SEMEVAL

Mengqiu Wang | Daniel Cer |

Parsing to Stanford Dependencies: Trade-offs between Speed and Accuracy LREC

Daniel Cer | Marie-Catherine de Marneffe | Dan Jurafsky | Chris Manning |

The Best Lexical Metric for Phrase-Based Statistical MT System Optimization NAACL

Daniel Cer | Christopher D. Manning | Daniel Jurafsky |

Phrasal: A Statistical Machine Translation Toolkit for Exploring New Model Features NAACL

Daniel Cer | Michel Galley | Daniel Jurafsky | Christopher D. Manning |

Regularization and Search for Minimum Error Rate Training WMT WS

Daniel Cer | Dan Jurafsky | Christopher D. Manning |

Learning Alignments and Leveraging Natural Logic WS

Learning to recognize features of valid textual entailments HLT NAACL