:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Rubinstein, Ittai, Hopkins, Samuel B.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2506.06656
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

On the Accuracy of Newton Step and Influence Function Data Attributions
by: Rubinstein, Ittai, et al.
Published: (2025)

Robustness Auditing for Linear Regression: To Singularity and Beyond
by: Rubinstein, Ittai, et al.
Published: (2024)

The Quasi-probability Method and Applications for Trace Reconstruction
by: Rubinstein, Ittai
Published: (2024)

Revisiting Data Attribution for Influence Functions
by: Zhu, Hongbo, et al.
Published: (2025)

Bayesian Influence Functions for Hessian-Free Data Attribution
by: Kreer, Philipp Alexander, et al.
Published: (2025)

An Iterative Algorithm for Rescaled Hyperbolic Functions Regression
by: Gao, Yeqi, et al.
Published: (2023)

Influence Functions for Scalable Data Attribution in Diffusion Models
by: Mlodozeniec, Bruno, et al.
Published: (2024)

High-Layer Attention Pruning with Rescaling
by: Liu, Songtao, et al.
Published: (2025)

A Versatile Influence Function for Data Attribution with Non-Decomposable Loss
by: Deng, Junwei, et al.
Published: (2024)

LoRIF: Low-Rank Influence Functions for Scalable Training Data Attribution
by: Li, Shuangqi, et al.
Published: (2026)

Influence Dynamics and Stagewise Data Attribution
by: Lee, Jin Hwa, et al.
Published: (2025)

Distributional Training Data Attribution: What do Influence Functions Sample?
by: Mlodozeniec, Bruno, et al.
Published: (2025)

Which Data Attributes Stimulate Math and Code Reasoning? An Investigation via Influence Functions
by: Kou, Siqi, et al.
Published: (2025)

Interaction-Aware Influence Functions for Group Attribution
by: Heo, Jaeseung, et al.
Published: (2026)

Integrated Influence: Data Attribution with Baseline
by: Yang, Linxiao, et al.
Published: (2025)

Adaptive Data Analysis for Growing Data
by: Marchant, Neil G., et al.
Published: (2024)

Fast, Sample-Efficient, Affine-Invariant Private Mean and Covariance Estimation for Subgaussian Distributions
by: Brown, Gavin, et al.
Published: (2023)

Accumulative SGD Influence Estimation for Data Attribution
by: Shi, Yunxiao, et al.
Published: (2025)

SeeDNorm: Self-Rescaled Dynamic Normalization
by: Cai, Wenrui, et al.
Published: (2025)

Adversarially-Robust Inference on Trees via Belief Propagation
by: Hopkins, Samuel B., et al.
Published: (2024)

Hypothesis Class Determines Explanation: Why Accurate Models Disagree on Feature Attribution
by: B, Thackshanaramana
Published: (2026)

Imperfect Influence, Preserved Rankings: A Theory of TRAK for Data Attribution
by: Tong, Han, et al.
Published: (2026)

Data Attribution for Diffusion Models: Timestep-induced Bias in Influence Estimation
by: Xie, Tong, et al.
Published: (2024)

Self-Attribution Bias: When AI Monitors Go Easy on Themselves
by: Khullar, Dipika, et al.
Published: (2026)

AMLA: MUL by ADD in FlashAttention Rescaling
by: Liao, Qichen, et al.
Published: (2025)

Temporal Score Rescaling for Temperature Sampling in Diffusion and Flow Models
by: Xu, Yanbo, et al.
Published: (2025)

Support Vector Machine Classifier with Rescaled Huberized Pinball Loss
by: Diao, Shibo
Published: (2025)

Non-Vacuous Generalization Bounds: Can Rescaling Invariances Help?
by: Rouchouse, Damien, et al.
Published: (2025)

Recovering Plasticity of Neural Networks via Soft Weight Rescaling
by: Oh, Seungwon, et al.
Published: (2025)

STAR: Spectral Truncation and Rescale for Model Merging
by: Lee, Yu-Ang, et al.
Published: (2025)

Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models
by: Lin, Jinxu, et al.
Published: (2024)

A Snapshot of Influence: A Local Data Attribution Framework for Online Reinforcement Learning
by: Hu, Yuzheng, et al.
Published: (2025)

Energy-Based Model for Accurate Estimation of Shapley Values in Feature Attribution
by: Lu, Cheng, et al.
Published: (2024)

Variance Control via Weight Rescaling in LLM Pre-training
by: Owen, Louis, et al.
Published: (2025)

Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity
by: Mahran, Ammar, et al.
Published: (2026)

LARV: Data-Free Layer-wise Adaptive Rescaling Veneer for Model Merging
by: Wang, Xinyu, et al.
Published: (2026)

Concept Influence: Leveraging Interpretability to Improve Performance and Efficiency in Training Data Attribution
by: Kowal, Matthew, et al.
Published: (2026)

Attribute Graphs Underlying Molecular Generative Models: Path to Learning with Limited Data
by: Hoffman, Samuel C., et al.
Published: (2022)

Influence-based Attributions can be Manipulated
by: Yadav, Chhavi, et al.
Published: (2024)

SoS Certificates for Sparse Singular Values and Their Applications: Robust Statistics, Subspace Distortion, and More
by: Diakonikolas, Ilias, et al.
Published: (2024)