Daniel Cer

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

2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Language agnostic and semantic-language information isolation is an emerging research direction for multilingual representations models. We explore this problem from a novel angle of geometric algebra and semantic space. A simple but highly effective method …

Language-agnostic BERT Sentence Embedding

2020 · arXiv (Cornell University)

While BERT is an effective method for learning monolingual sentence embeddings for semantic similarity and embedding based transfer learning (Reimers and Gurevych, 2019), BERT based cross-lingual sentence embeddings have yet to be explored. We systematically …

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

2015

Eneko Agirre, Carmen Banea, Claire Cardie, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Weiwei Guo, Iñigo Lopez-Gazpio, Montse Maritxalar, Rada Mihalcea, German Rigau, Larraitz Uria, Janyce Wiebe. Proceedings of the 9th International Workshop on Semantic Evaluation …

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

2016

Eneko Agirre, Carmen Banea, Daniel Cer, Mona Diab, Aitor Gonzalez-Agirre, Rada Mihalcea, German Rigau, Janyce Wiebe. Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016). 2016.

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

2017

Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include machine translation (MT), summarization, generation, question answering (QA), short answer grading, semantic search, dialog and conversational systems. The STS shared task is a …

Universal Sentence Encoder

2018 · arXiv (Cornell University)

We present models for encoding sentences into embedding vectors that specifically target transfer learning to other NLP tasks. The models are efficient and result in accurate performance on diverse transfer tasks. Two variants of the …

Effective Parallel Corpus Mining using Bilingual Sentence Embeddings

2018

Mandy Guo, Qinlan Shen, Yinfei Yang, Heming Ge, Daniel Cer, Gustavo Hernandez Abrego, Keith Stevens, Noah Constant, Yun-Hsuan Sung, Brian Strope, Ray Kurzweil. Proceedings of the Third Conference on Machine Translation: Research Papers. 2018.

Universal Sentence Encoder for English

2018

Daniel Cer, Yinfei Yang, Sheng-yi Kong, Nan Hua, Nicole Limtiaco, Rhomni St. John, Noah Constant, Mario Guajardo-Cespedes, Steve Yuan, Chris Tar, Brian Strope, Ray Kurzweil. Proceedings of the 2018 Conference on Empirical Methods in Natural …

Learning Semantic Textual Similarity from Conversations

2018

Yinfei Yang, Steve Yuan, Daniel Cer, Sheng-yi Kong, Noah Constant, Petr Pilar, Heming Ge, Yun-Hsuan Sung, Brian Strope, Ray Kurzweil. Proceedings of the Third Workshop on Representation Learning for NLP. 2018.

Multilingual Universal Sentence Encoder for Semantic Retrieval

2020

Yinfei Yang, Daniel Cer, Amin Ahmad, Mandy Guo, Jax Law, Noah Constant, Gustavo Hernandez Abrego, Steve Yuan, Chris Tar, Yun-hsuan Sung, Brian Strope, Ray Kurzweil. Proceedings of the 58th Annual Meeting of the Association for …

Language-agnostic BERT Sentence Embedding

2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

While BERT is an effective method for learning monolingual sentence embeddings for semantic similarity and embedding based transfer learning (Reimers and Gurevych, 2019), BERT based cross-lingual sentence embeddings have yet to be explored. We systematically …

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

2022 · Findings of the Association for Computational Linguistics: ACL 2022

We provide the first exploration of sentence embeddings from text-to-text transformers (T5) including the effects of scaling up sentence encoders to 11B parameters. Sentence embeddings are broadly useful for language processing tasks. While T5 achieves …

SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer

2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

There has been growing interest in parameterefficient methods to apply pre-trained language models to downstream tasks. Building on the PROMPTTUNING approach of Lester et al. ( SPOT first learns a prompt on one or more …

SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation

2017 · HAL (Le Centre pour la Communication Scientifique Directe)

Semantic Textual Similarity (STS) measures the meaning similarity of sentences. Applications include machine translation (MT), summarization, generation, question answering (QA), short answer grading, semantic search, dialog and conversational systems. The STS shared task is a …