Ilia Sucholutsky
14 papers · 2021–2025 · 8 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (8) π Cross-Pollinator (13) π Interdisciplinary Bridge π§ Keyword Pioneer π Renaissance Researcher (6)
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Taxonomy Completionist
(23)
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Renaissance Researcher
(6)
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Grand Slam
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Triple Crown
β
The Questioner
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Century Club
(14)
β‘
Prolific Year
(5)
Conferences
ICLR (3)
AAAI (2)
ICML (2)
NIPS (2)
UAI (2)
ACL (1)
AISTATS (1)
CORL (1)
Top co-authors
Research topics
Keywords
few-shot learning
(4)
representation learning
(3)
cognitive science
(2)
one-shot learning
(1)
sample efficiency
(1)
adversarial learning
(1)
model robustness
(1)
cognitive modeling
(1)
language model
(1)
human-in-the-loop learning
(1)
ai safety
(1)
human-computer interaction
(1)
serial reproduction
(1)
generative model
(1)
diffusion model
(1)
multi-armed bandit
(1)
deep neural network
(1)
adversarial perturbation
(1)
generative modeling
(1)
federated learning
(1)
Papers
Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse
ICML 2025
Large Language Models Assume People are More Rational than We Really are
ICLR 2025
Quantifying Knowledge Distillation using Partial Information Decomposition
AISTATS 2025
Learning Human-like Representations to Enable Learning Human Values
NIPS 2024
Characterizing Similarities and Divergences in Conversational Tones in Humans and LLMs by Sampling with People
ACL 2024
Learning with Language-Guided State Abstractions
ICLR 2024
Adaptive Language-Guided Abstraction from Contrastive Explanations
CORL 2024
On the informativeness of supervision signals
UAI 2023
Words are all you need? Language as an approximation for human similarity judgments
ICLR 2023
Human-in-the-Loop Mixup
UAI 2023
Alignment with human representations supports robust few-shot learning
NIPS 2023
Analyzing Diffusion as Serial Reproduction
ICML 2023
SecDD: Efficient and Secure Method for Remotely Training Neural Networks (Student Abstract)
AAAI 2021
`Less Than One'-Shot Learning: Learning N Classes From M < N Samples
AAAI 2021