Kevin Ellis
Assistant Professor, Cornell University, Computer Science
Research areas and selected papers:
- AI and program synthesis:
- World Models: ICLR’25 Spotlight
- Abstract Reasoning: Best Paper, ARCPrize’24
- AI and cognitive science:
- LLMs+Bayes: NeurIPS’23 oral
- Human grammar: Nature Comms ’22, Editor’s Highlight
Students
Cassidy Langenfeld, Masters
Alumni:
Keya (Lillian) Hu, visiting undergraduate
Leopoldo Sarra, visiting PhD
Teaching
Spring: Foundations of AI: Reasoning and Decision-Making (CS3700, undergrad)
Fall: Program Synthesis (CS6172, PhD)
Publications
Note: Most up to date is always Google Scholar
Combining Induction and
Transduction for Abstract Reasoning
Wen-Ding Li, Keya Hu,
Carter Larsen, Yuqing Wu, Simon Alford, Caleb Woo, Spencer M. Dunn, Hao
Tang, Michelangelo Naim, Dat Nguyen, Wei-Long Zheng, Zenna Tavares,
Yewen Pu, Kevin Ellis
ICLR 2025 & Best Paper at ARCPrize
VisualPredicator: Learning
Abstract World Models with Neuro-Symbolic Predicates for Robot
Planning
Yichao Liang, Nishanth Kumar, Hao Tang, Adrian
Weller, Joshua B. Tenenbaum, Tom Silver, João F. Henriques, Kevin Ellis
ICLR 2025 (Spotlight)
WorldCoder, a Model-Based
LLM Agent: Building World Models by Writing Code and Interacting with
the Environment
Hao Tang, Darren Key, Kevin Ellis
NeurIPS 2024
Doing Experiments and
Revising Rules with Natural Language and Probabilistic Reasoning
Wasu (Top) Piriyakulkij, Cassidy Lagenfeld, Tuan-Anh Le, Kevin
Ellis
NeurIPS 2024
Is Programming by Example
Solved by LLMs?
Wen-Ding Li, Kevin Ellis
NeurIPS
2024
Code Repair with LLMs
gives an Exploration-Exploitation Tradeoff
Hao Tang, Keya
Hu, Jin Peng Zhou, Sicheng Zhong, Wei-Long Zheng, Xujie Si, Kevin
Ellis
NeurIPS 2024
Symbolic
metaprogram search improves learning efficiency and explains rule
learning in humans
Joshua S. Rule, Steven T. Piantadosi,
Andrew Cropper, Kevin Ellis, Maxwell Nye, Joshua B. Tenenbaum
Nature Communications 2024
Rapid Motor Adaptation for
Robotic Manipulator Arms
Yichao Liang, Kevin Ellis, João
Henriques
CVPR 2024
Discovering
quantum circuit components with program synthesis
Leopoldo
Sarra, Kevin Ellis, Florian Marquardt
MLST 2024
Human-like Few-Shot
Learning via Bayesian Reasoning over Natural Language
Kevin
Ellis
NeurIPS 2023 (Oral)
LambdaBeam: Neural Program
Search with Higher-Order Functions and Lambdas
Kensen Shi,
Hanjun Dai, Wen-Ding Li, Kevin Ellis, Charles Sutton
NeurIPS
2023
Toward Trustworthy Neural
Program Synthesis
Wen-Ding Li, Darren Key, Kevin Ellis
arXiv 2023
From Perception to
Programs: Regularize, Overparameterize, and Amortize
Hao
Tang, Kevin Ellis
ICML 2023
Top-Down
Synthesis For Library Learning
Matthew Bowers, Theo X.
Olausson, Catherine Wong, Gabriel Grand, Joshua B. Tenenbaum, Kevin
Ellis, Armando Solar-Lezama
POPL 2023
A
language of thought for the mental representation of geometric
shapes
Mathias Sablé-Meyer, Kevin Ellis, Josh Tenenbaum,
Stanislas Dehaene
Cognitive Psychology 2023
Synthesizing
theories of human language with Bayesian program induction
Kevin Ellis, Adam Albright, Armando Solar-Lezama, Joshua B.
Tenenbaum, Timothy J. O’Donnell
Nature Communications 2022
CrossBeam:
Learning to Search in Bottom-Up Program Synthesis
Kensen
Shi*, Hanjun Dai*, Kevin Ellis, Charles Sutton
ICLR 2022
Hybrid Memoised
Wake-Sleep: Approximate Inference at the Discrete-Continuous
Interface
Tuan Anh Le, Katherine M. Collins, Luke Hewitt,
Kevin Ellis, Siddharth N, Samuel J. Gershman, Joshua B. Tenenbaum
ICLR 2022
Scaling Neural Program
Synthesis with Distribution-based Search
Nathanaël Fijalkow,
Guillaume Lagarde, Théo Matricon, Kevin Ellis, Pierre Ohlmann, Akarsh
Potta
AAAI 2022
DreamCoder:
Bootstrapping Inductive Program Synthesis with Wake-Sleep Library
Learning
Kevin Ellis, Catherine Wong, Maxwell Nye, Mathias
Sablé-Meyer, Lucas Morales, Luke Hewitt, Luc Cary, Armando Solar-Lezama,
Joshua B. Tenenbaum
PLDI 2021
Neurosymbolic
Programming
Swarat Chaudhuri, Kevin Ellis, Oleksandr
Polozov, Rishabh Singh, Armando Solar-Lezama, Yisong Yue
FnT in
Programming Languages 2021
Making
sense of raw input
Richard Evans, Matko Bošnjak, Lars
Buesing, Kevin Ellis, David Pfau, Pushmeet Kohli, Marek Sergot
Artificial Intelligence 2021
Leveraging natural
language for program search and abstraction learning
Catherine Wong, Kevin Ellis, Josh Tenenbaum, Jacob Andreas
ICML 2021
Phonological
Interactions, Process Types, and Minimum Description Length
Principles
Christopher Yang, Kevin Ellis
CogSci
2021
Learning abstract
structure for drawing by efficient motor program induction
Lucas Y. Tian, Kevin Ellis, Marta Kryven, Joshua B. Tenenbaum
NeurIPS 2020 (Oral)
Program Synthesis with
Pragmatic Communication
Yewen Pu, Kevin Ellis, Marta Kryven,
Joshua B. Tenenbaum, Armando Solar-Lezama
NeurIPS 2020
Write, Execute, Assess:
Program Synthesis with a REPL
Kevin Ellis*, Maxwell Nye*,
Yewen Pu*, Felix Sosa*, Joshua B. Tenenbaum, Armando Solar-Lezama
NeurIPS 2019
Learning to Infer and
Execute 3D Shape Programs
Yonglong Tian, Andrew Luo,
Xingyuan Sun, Kevin Ellis, William T. Freeman, Joshua B. Tenenbaum,
Jiajun Wu
ICLR 2019
Five
ways in which computational modeling can help advance cognitive science:
lessons from Artificial Grammar Learning
Willem Zuidema,
Robert M. French, Raquel G. Alhama, Kevin Ellis, Tim O’Donnell, Tim
Sainburgh, Tim Gentner
Topics in Cognitive Science 2019
Learning
Libraries of Subroutines for Neurally-Guided Bayesian Program
Induction
Kevin Ellis, Lucas Morales, Mathias Sablé-Meyer,
Armando Solar-Lezama, Joshua B. Tenenbaum
NeurIPS 2018
Learning to Infer
Graphics Programs from Hand-Drawn Images
Kevin Ellis, Daniel
Ritchie, Armando Solar-Lezama, Joshua B. Tenenbaum
NeurIPS
2018
Learning
to Learn Programs from Examples: Going Beyond Program Structure
Kevin Ellis, Sumit Gulwani
IJCAI 2017
Sampling
for Bayesian Program Learning
Kevin Ellis, Armando
Solar-Lezama, Joshua B. Tenenbaum
NeurIPS 2016
Unsupervised
Learning by Program Synthesis
Kevin Ellis, Armando
Solar-Lezama, Joshua B. Tenenbaum
NeurIPS 2015
Dimensionality
Reduction via Program Induction
Kevin Ellis, Eyal Dechter,
Joshua B. Tenenbaum
AAAI Symposium 2015
Bias
reformulation for one-shot function induction
Dianhuan Lin,
Eyal Dechter, Kevin Ellis, Joshua B. Tenenbaum, Stephen Muggleton
ECAI 2014
My PhD thesis was about program induction for artificial intelligence, and is available as a document, podcast, and video
Website template taken from Mathias Sablé-Meyer