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Matt Post

Microsoft Translator

35 papers hereh-index 4112.3k citations116 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author3
  • middle author17
  • last author14

Across the 35 of 35 papers where every author was matched, so the position is known.

fields
  • cs.CL32
  • cs.HC1
  • cs.LG1
  • cs.SE1
affiliations
  • Microsoft Translator
  • Johns Hopkins University
  • University of Rochester
  • Calvin College
HomepageORCID 0000-0002-1297-6794
same name
  • Matt Post — 2 papers, h 1
  • Matt Post — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162025
most citedEscaping the sentence-level paradigm in machine translation

13 citations · 59 across the 22 of their papers we have counts for

collaborators
Showing 2024 · cs.CLShow all

4 papers · 2 filters

cs.CL2024

CTC-GMM: CTC guided modality matching for fast and accurate streaming speech translation

Rui Zhao, Jinyu Li, Ruchao Fan +1

Models for streaming speech translation (ST) can achieve high accuracy and low latency if they're developed with vast amounts of paired audio in the source language and written tex…

cs.CL2024

PyMarian: Fast Neural Machine Translation and Evaluation in Python

Thamme Gowda, Roman Grundkiewicz, Elijah Rippeth +2

The deep learning language of choice these days is Python; measured by factors such as available libraries and technical support, it is hard to beat. At the same time, software wri…

cs.CL2024

Recovering document annotations for sentence-level bitext

Rachel Wicks, Matt Post, Philipp Koehn

Data availability limits the scope of any given task. In machine translation, historical models were incapable of handling longer contexts, so the lack of document-level datasets w…

cs.CL2024

Navigating the Metrics Maze: Reconciling Score Magnitudes and Accuracies

Tom Kocmi, Vilém Zouhar, Christian Federmann +1

Ten years ago a single metric, BLEU, governed progress in machine translation research. For better or worse, there is no such consensus today, and consequently it is difficult for…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.