Physics-AI Fellow
Publications
MEMOIR: Lifelong Model Editing with Minimal Overwrite and Informed Retention for LLMs
– Advances in Neural Information Processing Systems
(2025)
Probing the latent hierarchical structure of data via diffusion models*
– Journal of Statistical Mechanics: Theory and Experiment
(2025)
2025,
084005
(doi: 10.1088/1742-5468/aded6c)
How compositional generalization and creativity improve as diffusion models are trained
– Proceedings of the 42nd International Conference on Machine Learning, PMLR 267
(2025)
Lines: Post-training layer scaling prevents forgetting and enhances model merging
– International Conference on Learning Representations
(2025)
A phase transition in diffusion models reveals the hierarchical nature of data.
– Proceedings of the National Academy of Sciences
(2025)
122,
e2408799121
(doi: 10.1073/pnas.2408799121)
Computational complexity of deep learning: fundamental limitations and empirical phenomena
– Journal of Statistical Mechanics: Theory and Experiment
(2024)
2024,
104008
(doi: 10.1088/1742-5468/ad3a5b)
What can be learnt with wide convolutional neural networks?
– Journal of Statistical Mechanics: Theory and Experiment
(2024)
2024,
104020
(doi: 10.1088/1742-5468/ad65df)
How Deep Neural Networks Learn Compositional Data: The Random Hierarchy Model
– Physical Review X
(2024)
14,
031001
(doi: 10.1103/PhysRevX.14.031001)
Multi-Modal Hallucination Control by Visual Information Grounding
– 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
(2024)
00,
14303
(doi: 10.1109/cvpr52733.2024.01356)
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models
– Advances in Neural Information Processing Systems
(2023)
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