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Doug Downey

Allen Institute for Artificial Intelligence

45 papers hereh-index 3812.1k citations116 works total

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

author position
  • middle author32
  • last author12

Across the 44 of 45 papers where every author was matched, so the position is known.

fields
  • cs.CL31
  • cs.IR5
  • cs.HC4
  • cs.DL3
  • cs.LG2
affiliations
  • Allen Institute for Artificial Intelligence
  • Northwestern University
Homepage
same name
  • Doug Downey — 9 papers, h 5
  • Doug Downey — 5 papers, h 2
  • Doug Downey — 5 papers, h 4

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 citedGenerative Data Augmentation for Commonsense Reasoning

99 citations · 610 across the 41 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.LG2019

Just Add Functions: A Neural-Symbolic Language Model

David Demeter, Doug Downey

Neural network language models (NNLMs) have achieved ever-improving accuracy due to more sophisticated architectures and increasing amounts of training data. However, the inductive…

cs.CL2019★ 3 cited

Multi-sense Definition Modeling using Word Sense Decompositions

Ruimin Zhu, Thanapon Noraset, Alisa Liu +2

Word embeddings capture syntactic and semantic information about words. Definition modeling aims to make the semantic content in each embedding explicit, by outputting a natural la…

cs.CL2019★ 33 cited

Abductive Commonsense Reasoning

Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya +6

Abductive reasoning is inference to the most plausible explanation. For example, if Jenny finds her house in a mess when she returns from work, and remembers that she left a window…

cs.CL2019★ 16 cited

A new evaluation framework for topic modeling algorithms based on synthetic corpora

Hanyu Shi, Martin Gerlach, Isabel Diersen +2

Topic models are in widespread use in natural language processing and beyond. Here, we propose a new framework for the evaluation of probabilistic topic modeling algorithms based o…

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