8 citations · 21 across the 14 of their papers we have counts for
28 papers
Towards an On-device Agent for Text Rewriting
Yun Zhu, Yinxiao Liu, Felix Stahlberg +7
Large Language Models (LLMs) have demonstrated impressive capabilities for text rewriting. Nonetheless, the large sizes of these models make them impractical for on-device inferenc…
Improved Long-Form Spoken Language Translation with Large Language Models
Arya D. McCarthy, Hao Zhang, Shankar Kumar +2
A challenge in spoken language translation is that plenty of spoken content is long-form, but short units are necessary for obtaining high-quality translations. To address this mis…
Conciseness: An Overlooked Language Task
Felix Stahlberg, Aashish Kumar, Chris Alberti +1
We report on novel investigations into training models that make sentences concise. We define the task and show that it is different from related tasks such as summarization and si…
Text Generation with Text-Editing Models
Eric Malmi, Yue Dong, Jonathan Mallinson +7
Text-editing models have recently become a prominent alternative to seq2seq models for monolingual text-generation tasks such as grammatical error correction, simplification, and s…
Jam or Cream First? Modeling Ambiguity in Neural Machine Translation with SCONES
Felix Stahlberg, Shankar Kumar
The softmax layer in neural machine translation is designed to model the distribution over mutually exclusive tokens. Machine translation, however, is intrinsically uncertain: the…
Uncertainty Determines the Adequacy of the Mode and the Tractability of Decoding in Sequence-to-Sequence Models
Felix Stahlberg, Ilia Kulikov, Shankar Kumar
In many natural language processing (NLP) tasks the same input (e.g. source sentence) can have multiple possible outputs (e.g. translations). To analyze how this ambiguity (also kn…