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Dan Gutfreund
Researcher at IBM
Publications - 63
Citations - 1941
Dan Gutfreund is an academic researcher from IBM. The author has contributed to research in topics: Computer science & Time complexity. The author has an hindex of 20, co-authored 56 publications receiving 1266 citations. Previous affiliations of Dan Gutfreund include Hebrew University of Jerusalem & Massachusetts Institute of Technology.
Papers
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Journal ArticleDOI
Moments in Time Dataset: One Million Videos for Event Understanding
Mathew Monfort,Carl Vondrick,Aude Oliva,Alex Andonian,Bolei Zhou,Kandan Ramakrishnan,Sarah Adel Bargal,Tom Yan,Lisa M. Brown,Quanfu Fan,Dan Gutfreund +10 more
TL;DR: The Moments in Time dataset, a large-scale human-annotated collection of one million short videos corresponding to dynamic events unfolding within three seconds, can serve as a new challenge to develop models that scale to the level of complexity and abstract reasoning that a human processes on a daily basis.
Proceedings Article
ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models
Andrei Barbu,David Mayo,Julian Alverio,William Luo,Christopher Wang,Dan Gutfreund,Joshua B. Tenenbaum,Boris Katz +7 more
TL;DR: A highly automated platform that enables gathering datasets with controls at scale using automated tools throughout machine learning to generate datasets that exercise models in new ways thus providing valuable feedback to researchers is developed.
Posted Content
ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation
Chuang Gan,Jeremy Schwartz,Seth Alter,Martin Schrimpf,James Traer,Julian De Freitas,Jonas Kubilius,Abhishek Bhandwaldar,Nick Haber,Megumi Sano,Kuno Kim,Elias Wang,Damian Mrowca,Michael Lingelbach,Aidan Curtis,Kevin T. Feigelis,Daniel M. Bear,Dan Gutfreund,David D. Cox,James J. DiCarlo,Josh H. McDermott,Joshua B. Tenenbaum,Daniel L. K. Yamins +22 more
TL;DR: Initial experiments enabled by the ThreeDWorld platform are presented, including multi-modal physical scene understanding, multi-agent interactions, models that "learn like a child", and attention studies in humans and neural networks.
Proceedings ArticleDOI
A Benchmark Dataset for Automatic Detection of Claims and Evidence in the Context of Controversial Topics
Ehud Aharoni,Anatoly Polnarov,Tamar Lavee,Daniel Hershcovich,Ran Levy,Ruty Rinott,Dan Gutfreund,Noam Slonim +7 more
TL;DR: A novel and unique argumentative structure dataset that consists of data extracted from hundreds of Wikipedia articles using a meticulously monitored manual annotation process, organized under a simp le claim-evidence structure.
Journal ArticleDOI
A lower bound for testing juntas
Hana Chockler,Dan Gutfreund +1 more
TL;DR: An Ω(m) lower bound on the number of queries required to test whether a Boolean function depends on at most m out of its n variables is shown.