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Tomer Ullman

3 papers here

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

author position
  • sole author1
  • middle author1
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.AI2
  • cs.CV1
ORCID 0000-0003-1722-2382

identity via Semantic Scholar / OpenAlex

activity
20162023
most citedA Compositional Object-Based Approach to Learning Physical Dynamics

166 citations · 289 across the 3 of their papers we have counts for

collaborators

3 papers

cs.AI2023★ 83 cited

Large Language Models Fail on Trivial Alterations to Theory-of-Mind Tasks

Tomer Ullman

Intuitive psychology is a pillar of common-sense reasoning. The replication of this reasoning in machine intelligence is an important stepping-stone on the way to human-like artifi…

cs.CV2022★ 40 cited

Testing Relational Understanding in Text-Guided Image Generation

Colin Conwell, Tomer Ullman

Relations are basic building blocks of human cognition. Classic and recent work suggests that many relations are early developing, and quickly perceived. Machine models that aspire…

cs.AI2016★ 166 cited

A Compositional Object-Based Approach to Learning Physical Dynamics

Michael B. Chang, Tomer Ullman, Antonio Torralba +1

We present the Neural Physics Engine (NPE), a framework for learning simulators of intuitive physics that naturally generalize across variable object count and different scene conf…

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