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researcher

Jason Lee

New York University

6 papers hereh-index 253.2k citations93 works total

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

author position
  • first author4
  • middle author2

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CL4
  • cs.LG2
affiliations
  • New York University
Homepage
same name
  • Jason Lee — 5 papers, h 5
  • Jason Lee — 5 papers, h 3
  • Jason Lee — 4 papers, h 2
  • Jason Lee — 2 papers
  • Jason Lee — 2 papers
  • Jason Lee — 2 papers, 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
20182020
most citedOn the Discrepancy between Density Estimation and Sequence Generation

3 citations · 4 across the 2 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2020★ 1 cited

Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation

Jason Lee, Raphael Shu, Kyunghyun Cho

We propose an efficient inference procedure for non-autoregressive machine translation that iteratively refines translation purely in the continuous space. Given a continuous laten…

cs.CL2019

Countering Language Drift via Visual Grounding

Jason Lee, Kyunghyun Cho, Douwe Kiela

Emergent multi-agent communication protocols are very different from natural language and not easily interpretable by humans. We find that agents that were initially pretrained to…

cs.CL2019

Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference Using a Delta Posterior

Raphael Shu, Jason Lee, Hideki Nakayama +1

Although neural machine translation models reached high translation quality, the autoregressive nature makes inference difficult to parallelize and leads to high translation latenc…

cs.CL2019

Multi-Turn Beam Search for Neural Dialogue Modeling

Ilia Kulikov, Jason Lee, Kyunghyun Cho

In neural dialogue modeling, a neural network is trained to predict the next utterance, and at inference time, an approximate decoding algorithm is used to generate next utterances…

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