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Thomson Reuters (Canada)

Canada

4 papers here58 citations across 4
fields
  • cs.CL3
  • cs.IR1
ROR 01r4zz038OpenAlex

affiliations via OpenAlex

output
20172023
most citedComparing Sentence-Level Suggestions to Message-Level Suggestions in AI-Mediated Communication

29 citations

researchers with a paper here
  • Abhinav Agrawal1
  • Ali Oskooei1
  • Armineh Nourbakhsh1 · h 17
  • Benjamin Newman1
  • Hsiu-Wei Yang1
  • Liye Fu1
  • Maurice Jakesch1
  • N. Herger1
  • Omar Bari1
  • Quanzhi Li1
  • Sameena Shah1
  • Sarah Kreps1
collaborating institutions
  • Allen Institute for Artificial IntelligenceUS1 paper
  • Cornell UniversityUS1 paper
Showing cs.CLShow all

3 papers · 1 filter

cs.CL2023★ 29 cited

Comparing Sentence-Level Suggestions to Message-Level Suggestions in AI-Mediated Communication

Liye Fu, Benjamin Newman, Maurice Jakesch +1

Traditionally, writing assistance systems have focused on short or even single-word suggestions. Recently, large language models like GPT-3 have made it possible to generate signif…

cs.CL2020★ 10 cited

Named Entity Recognition in the Legal Domain using a Pointer Generator Network

Stavroula Skylaki, Ali Oskooei, Omar Bari +2

Named Entity Recognition (NER) is the task of identifying and classifying named entities in unstructured text. In the legal domain, named entities of interest may include the case…

cs.CL2017★ 17 cited

Data Sets: Word Embeddings Learned from Tweets and General Data

Quanzhi Li, Sameena Shah, Xiaomo Liu +1

A word embedding is a low-dimensional, dense and real- valued vector representation of a word. Word embeddings have been used in many NLP tasks. They are usually gener- ated from a…

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