Rylan Schaeffer
14 papers · 2020–2025 · 4 venues · across top CS/AI venues
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(4)
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(3)
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large language model
(4)
recurrent neural network
(2)
online inference
(2)
bayesian inference
(2)
grid cell
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bayesian nonparametrics
(2)
loss function optimization
(1)
variational inference
(1)
catastrophic forgetting
(1)
self-supervised learning
(1)
knowledge distillation
(1)
toxicity detection
(1)
chinese restaurant process
(1)
deep learning
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model robustness
(1)
kernel density estimation
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indian buffet process
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sparse representation
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pretraining
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markov chain monte carlo
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Papers
Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World
ICML 2025
Failures to Find Transferable Image Jailbreaks Between Vision-Language Models
ICLR 2025
How Do Large Language Monkeys Get Their Power (Laws)?
ICML 2025
Uncovering Latent Memories in Large Language Models
ICLR 2025
Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive?
ICML 2025
Many-shot Jailbreaking
NeurIPS 2024
Are Emergent Abilities of Large Language Models a Mirage?
NeurIPS 2023
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
NeurIPS 2023
Emergence of Sparse Representations from Noise
ICML 2023
Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells
NeurIPS 2023
No Free Lunch from Deep Learning in Neuroscience: A Case Study through Models of the Entorhinal-Hippocampal Circuit
NeurIPS 2022
Streaming Inference for Infinite Feature Models
ICML 2022
Efficient online inference for nonparametric mixture models
UAI 2021
Reverse-engineering recurrent neural network solutions to a hierarchical inference task for mice
NeurIPS 2020