Noah Constant
Publications by Year
Research Areas
Topic Modeling, Natural Language Processing Techniques, Multimodal Machine Learning Applications, Speech Recognition and Synthesis, Syntax, Semantics, Linguistic Variation
Most-Cited Works
- → mT5: A Massively Multilingual Pre-trained Text-to-Text Transformer(2021)1,508 cited
- → Universal Sentence Encoder(2018)1,292 cited
- → Universal Sentence Encoder for English(2018)1,245 cited
- → Multilingual Universal Sentence Encoder for Semantic Retrieval(2020)404 cited
- → Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Models(2022)248 cited
- → ByT5: Towards a Token-Free Future with Pre-trained Byte-to-Byte Models(2022)222 cited
- → SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer(2022)167 cited
- → Learning Semantic Textual Similarity from Conversations(2018)155 cited
- → English rise-fall-rise: a study in the semantics and pragmatics of intonation(2012)124 cited