activity
20182023
most citedLingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

184 citations · 221 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2023★ 7 cited

BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information

Mehran Kazemi, Quan Yuan, Deepti Bhatia +4

Automated reasoning with unstructured natural text is a key requirement for many potential applications of NLP and for developing robust AI systems. Recently, Language Models (LMs)…

cs.AI2022★ 5 cited

LAMBADA: Backward Chaining for Automated Reasoning in Natural Language

Mehran Kazemi, Najoung Kim, Deepti Bhatia +2

Remarkable progress has been made on automated reasoning with natural text, by using Language Models (LMs) and methods such as Chain-of-Thought and Selection-Inference. These techn…

eess.AS2021★ 2 cited

Learning Word-Level Confidence For Subword End-to-End ASR

David Qiu, Qiujia Li, Yanzhang He +9

We study the problem of word-level confidence estimation in subword-based end-to-end (E2E) models for automatic speech recognition (ASR). Although prior works have proposed trainin…

cs.LG2019★ 184 cited

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

Jonathan Shen, Patrick Nguyen, Yonghui Wu +88

Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models a…

cs.CL2018★ 23 cited

Streaming End-to-end Speech Recognition For Mobile Devices

Yanzhang He, Tara N. Sainath, Rohit Prabhavalkar +17

End-to-end (E2E) models, which directly predict output character sequences given input speech, are good candidates for on-device speech recognition. E2E models, however, present nu…