:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Ross, Alexis, Srivastava, Megha, Blanchard, Jeremiah, Andreas, Jacob
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2510.05056
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning to Make MISTAKEs: Modeling Incorrect Student Thinking And Key Errors
by: Ross, Alexis, et al.
Published: (2025)

Toward In-Context Teaching: Adapting Examples to Students' Misconceptions
by: Ross, Alexis, et al.
Published: (2024)

Policy Learning with a Language Bottleneck
by: Srivastava, Megha, et al.
Published: (2024)

Optimistic Verifiable Training by Controlling Hardware Nondeterminism
by: Srivastava, Megha, et al.
Published: (2024)

TabFlex: Scaling Tabular Learning to Millions with Linear Attention
by: Zeng, Yuchen, et al.
Published: (2025)

Agnostic Smoothed Online Learning without Knowledge of the Base Measure
by: Blanchard, Moïse
Published: (2024)

Learning to Forget with Information Divergence Reweighted Objectives for Noisy Labels
by: Birrell, Jeremiah, et al.
Published: (2025)

Concentration Inequalities for Stochastic Optimization of Unbounded Objective Functions with Application to Denoising Score Matching
by: Birrell, Jeremiah
Published: (2025)

Statistical Error Bounds for GANs with Nonlinear Objective Functionals
by: Birrell, Jeremiah
Published: (2024)

Hawkeye: Reproducing GPU-Level Non-Determinism
by: Badash, Erez, et al.
Published: (2026)

How does Graph Structure Modulate Membership-Inference Risk for Graph Neural Networks?
by: Khosla, Megha
Published: (2026)

Machine learning for modular multiplication
by: Lauter, Kristin, et al.
Published: (2024)

AGALE: A Graph-Aware Continual Learning Evaluation Framework
by: Zhao, Tianqi, et al.
Published: (2024)

Learning to Optimize Feedback for One Million Students: Insights from Multi-Armed and Contextual Bandits in Large-Scale Online Tutoring
by: Schmucker, Robin, et al.
Published: (2025)

Distributionally-Constrained Adversaries in Online Learning
by: Blanchard, Moïse, et al.
Published: (2025)

Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders
by: He, Zhengfu, et al.
Published: (2024)

Disentangled and Self-Explainable Node Representation Learning
by: Piaggesi, Simone, et al.
Published: (2024)

GNN-MultiFix: Addressing the pitfalls for GNNs for multi-label node classification
by: Zhao, Tianqi, et al.
Published: (2024)

OpenEstimate: Evaluating LLMs on Reasoning Under Uncertainty with Real-World Data
by: Renda, Alana, et al.
Published: (2025)

Statistical Guarantees for Distributionally Robust Optimization with Optimal Transport and OT-Regularized Divergences
by: Birrell, Jeremiah, et al.
Published: (2026)

Optimal Transport Regularized Divergences: Application to Adversarial Robustness
by: Birrell, Jeremiah, et al.
Published: (2023)

Re-Emergent Misalignment: How Narrow Fine-Tuning Erodes Safety Alignment in LLMs
by: Giordani, Jeremiah
Published: (2025)

Preventing Learning Stagnation in PPO by Scaling to 1 Million Parallel Environments
by: Beukman, Michael, et al.
Published: (2026)

Investigating the Robustness of Knowledge Tracing Models in the Presence of Student Concept Drift
by: Lee, Morgan, et al.
Published: (2025)

Automatically Interpreting Millions of Features in Large Language Models
by: Paulo, Gonçalo, et al.
Published: (2024)

World Model on Million-Length Video And Language With Blockwise RingAttention
by: Liu, Hao, et al.
Published: (2024)

Benchmarking Reliability of Deep Learning Models for Pathological Gait Classification
by: Jaiswal, Abhishek, et al.
Published: (2024)

Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization
by: Xue, Yuan, et al.
Published: (2026)

Mixture of A Million Experts
by: He, Xu Owen
Published: (2024)

A Teacher Is Worth A Million Instructions
by: Kothari, Nikhil, et al.
Published: (2024)

Self-Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale
by: Jones, Haydn, et al.
Published: (2026)

On the Scaling of PEFT: Towards Million Personal Models of Trillion Parameters
by: Lab, Mind, et al.
Published: (2026)

Revisiting Day-ahead Electricity Price: Simple Model Save Millions
by: Wang, Linian, et al.
Published: (2024)

Making Multi-Axis Gaussian Graphical Models Scalable to Millions of Cells
by: Andrew, Bailey, et al.
Published: (2024)

Collaborative Min-Max Regret in Grouped Multi-Armed Bandits
by: Blanchard, Moïse, et al.
Published: (2025)

Draw a Portrait of Your Graph Data: An Instance-Level Profiling Framework for Graph-Structured Data
by: Zhao, Tianqi, et al.
Published: (2025)

Efficient Generative Transformer Operators For Million-Point PDEs
by: Koupaï, Armand Kassaï, et al.
Published: (2025)

Model Selection with Model Zoo via Graph Learning
by: Li, Ziyu, et al.
Published: (2024)

Using Low-Discrepancy Points for Data Compression in Machine Learning: An Experimental Comparison
by: Göttlich, Simone, et al.
Published: (2024)

A Factored MDP Approach To Moving Target Defense With Dynamic Threat Modeling and Cost Efficiency
by: Bose, Megha, et al.
Published: (2024)