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Nonlinear Reconstruction for Operator Learning of PDEs with...
Feb 1, 2023 · Operator learning based on non-linear reconstruction (FNOs, shift-DeepONets) outperform methods based on linear …
Fast Model Editing at Scale - OpenReview
Jan 28, 2022 · the core method utilizes a clever trick (rank-1 gradients) that significantly reduces the complexity of model editing. …
DoReMi: Optimizing Data Mixtures Speeds Up Language Model …
Sep 21, 2023 · The idea to optimize the pre-training data sounds clever, particularly their use of a proxy model trained with DRO. …
Hyperbolic Attention Networks - OpenReview
Dec 20, 2018 · We propose to incorporate inductive biases and operations coming from hyperbolic geometry to improve the attention …
The Clever Hans Mirage: A Comprehensive Survey on Spurious...
Feb 21, 2026 · This survey on spurious correlations uses the Clever Hans metaphor to motivate the problem, formalizes a group …
PaZO: Preconditioned Accelerated Zeroth-Order Optimization for...
Sep 18, 2025 · This paper introduces PaZO, a preconditioned accelerated zeroth-order optimization algorithm for fine-tuning large …
Building Normalizing Flows with Stochastic Interpolants
Feb 1, 2023 · A method is proposed to construct normalizing flows based on stochastic interpolants, yielding an efficient training …
Evaluating the Robustness of Neural Networks: An Extreme Value...
Feb 15, 2018 · Our analysis yields a novel robustness metric called CLEVER, which is short for Cross Lipschitz Extreme Value for …
MoRA: Missing Modality Low-Rank Adaptation for Visual Recognition
Jan 26, 2026 · The core mechanism of MoRA is clever. Using Gram matrices to facilitate shared, low-rank adaptation between two …
Who’s Harry Potter? Approximate Unlearning for LLMs
Sep 23, 2023 · TL;DR: We present a method for unlearning in LLMs and demonstrate its effectiveness by finetuning Llama2-7b to …
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