Saved in:
| Main Authors: | Nordby, Erik, Pais, Tasha, Parrack, Aviel |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.13386 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Soft Prompts for Evaluation: Measuring Conditional Distance of Capabilities
by: Nordby, Ross
Published: (2025)
by: Nordby, Ross
Published: (2025)
Benchmarking Deception Probes via Black-to-White Performance Boosts
by: Parrack, Avi, et al.
Published: (2025)
by: Parrack, Avi, et al.
Published: (2025)
The Disparate Benefits of Deep Ensembles
by: Schweighofer, Kajetan, et al.
Published: (2024)
by: Schweighofer, Kajetan, et al.
Published: (2024)
Optimal Representation Size: High-Dimensional Analysis of Pretraining and Linear Probing
by: Njaradi, Valentina, et al.
Published: (2026)
by: Njaradi, Valentina, et al.
Published: (2026)
Probe-then-Commit Multi-Objective Bandits: Theoretical Benefits of Limited Multi-Arm Feedback
by: Shi, Ming
Published: (2026)
by: Shi, Ming
Published: (2026)
On the Benefits of Rank in Attention Layers
by: Amsel, Noah, et al.
Published: (2024)
by: Amsel, Noah, et al.
Published: (2024)
SiamTST: A Novel Representation Learning Framework for Enhanced Multivariate Time Series Forecasting applied to Telco Networks
by: Kristoffersen, Simen, et al.
Published: (2024)
by: Kristoffersen, Simen, et al.
Published: (2024)
LayerMatch: Do Pseudo-labels Benefit All Layers?
by: Liang, Chaoqi, et al.
Published: (2024)
by: Liang, Chaoqi, et al.
Published: (2024)
Joint Optimization of Piecewise Linear Ensembles
by: Raymond, Matt, et al.
Published: (2024)
by: Raymond, Matt, et al.
Published: (2024)
Improved Regret of Linear Ensemble Sampling
by: Lee, Harin, et al.
Published: (2024)
by: Lee, Harin, et al.
Published: (2024)
An Ensemble Classification Approach in A Multi-Layered Large Language Model Framework for Disease Prediction
by: Hamdi, Ali, et al.
Published: (2025)
by: Hamdi, Ali, et al.
Published: (2025)
Gated Uncertainty-Aware Runtime Dual Invariants for Neural Signal-Controlled Robotics
by: Kim, Tasha, et al.
Published: (2025)
by: Kim, Tasha, et al.
Published: (2025)
Scaling Motion Forecasting Models with Ensemble Distillation
by: Ettinger, Scott, et al.
Published: (2024)
by: Ettinger, Scott, et al.
Published: (2024)
The Law of Multi-Model Collaboration: Scaling Limits of Model Ensembling for Large Language Models
by: Lu, Dakuan, et al.
Published: (2025)
by: Lu, Dakuan, et al.
Published: (2025)
ReLU Neural Networks with Linear Layers are Biased Towards Single- and Multi-Index Models
by: Parkinson, Suzanna, et al.
Published: (2023)
by: Parkinson, Suzanna, et al.
Published: (2023)
Linear Mode Connectivity in Differentiable Tree Ensembles
by: Kanoh, Ryuichi, et al.
Published: (2024)
by: Kanoh, Ryuichi, et al.
Published: (2024)
What Linear Probes Miss: Multi-View Probing for Weight-Space Learning
by: Heo, Eunwoo, et al.
Published: (2026)
by: Heo, Eunwoo, et al.
Published: (2026)
Hardware Aware Ensemble Selection for Balancing Predictive Accuracy and Cost
by: Maier, Jannis, et al.
Published: (2024)
by: Maier, Jannis, et al.
Published: (2024)
Better and Worse with Scale: How Contextual Entrainment Diverges with Model Size
by: Kukreja, Dikshant, et al.
Published: (2026)
by: Kukreja, Dikshant, et al.
Published: (2026)
Beyond Linear Probes: Dynamic Safety Monitoring for Language Models
by: Oldfield, James, et al.
Published: (2025)
by: Oldfield, James, et al.
Published: (2025)
Transfer Learning of Linear Regression with Multiple Pretrained Models: Benefiting from More Pretrained Models via Overparameterization Debiasing
by: Boharon, Daniel, et al.
Published: (2026)
by: Boharon, Daniel, et al.
Published: (2026)
Balancing Accuracy and Speed: A Multi-Fidelity Ensemble Kalman Filter with a Machine Learning Surrogate Model
by: van der Voort, Jeffrey, et al.
Published: (2025)
by: van der Voort, Jeffrey, et al.
Published: (2025)
LOTOS: Layer-wise Orthogonalization for Training Robust Ensembles
by: Ebrahimpour-Boroojeny, Ali, et al.
Published: (2024)
by: Ebrahimpour-Boroojeny, Ali, et al.
Published: (2024)
Understanding Linear Probing then Fine-tuning Language Models from NTK Perspective
by: Tomihari, Akiyoshi, et al.
Published: (2024)
by: Tomihari, Akiyoshi, et al.
Published: (2024)
Boosting the Accuracy of Stock Market Prediction via Multi-Layer Hybrid MTL Structure
by: Hong, Yuxi
Published: (2025)
by: Hong, Yuxi
Published: (2025)
On Extending Semantic Abstraction for Efficient Search of Hidden Objects
by: Pais, Tasha, et al.
Published: (2025)
by: Pais, Tasha, et al.
Published: (2025)
Ensembles at Any Cost? Accuracy-Energy Trade-offs in Recommender Systems
by: Nitschke, Jannik, et al.
Published: (2026)
by: Nitschke, Jannik, et al.
Published: (2026)
Multi-Objective Linear Ensembles for Robust and Sparse Training of Few-Bit Neural Networks
by: Bernardelli, Ambrogio Maria, et al.
Published: (2022)
by: Bernardelli, Ambrogio Maria, et al.
Published: (2022)
Integrating Random Forests and Generalized Linear Models for Improved Accuracy and Interpretability
by: Agarwal, Abhineet, et al.
Published: (2023)
by: Agarwal, Abhineet, et al.
Published: (2023)
Detecting Strategic Deception Using Linear Probes
by: Goldowsky-Dill, Nicholas, et al.
Published: (2025)
by: Goldowsky-Dill, Nicholas, et al.
Published: (2025)
Enhancing Predictive Accuracy in Pharmaceutical Sales Through An Ensemble Kernel Gaussian Process Regression Approach
by: Mirshekari, Shahin, et al.
Published: (2024)
by: Mirshekari, Shahin, et al.
Published: (2024)
Scaling Embedding Layers in Language Models
by: Yu, Da, et al.
Published: (2025)
by: Yu, Da, et al.
Published: (2025)
Layer-wise Linear Mode Connectivity
by: Adilova, Linara, et al.
Published: (2023)
by: Adilova, Linara, et al.
Published: (2023)
Improving World Models using Deep Supervision with Linear Probes
by: Zahorodnii, Andrii
Published: (2025)
by: Zahorodnii, Andrii
Published: (2025)
A Hierarchical Language Model with Predictable Scaling Laws and Provable Benefits of Reasoning
by: Gaitonde, Jason, et al.
Published: (2026)
by: Gaitonde, Jason, et al.
Published: (2026)
Understanding the Benefits of SimCLR Pre-Training in Two-Layer Convolutional Neural Networks
by: Zhang, Han, et al.
Published: (2024)
by: Zhang, Han, et al.
Published: (2024)
AutoScale: Linear Scalarization Guided by Multi-Task Optimization Metrics
by: Yang, Yi, et al.
Published: (2025)
by: Yang, Yi, et al.
Published: (2025)
Meta-Black-Box Optimization with Ensemble Surrogate Modeling for Robustness-Accuracy Trade-off within SAEA
by: Jin, Xiao, et al.
Published: (2026)
by: Jin, Xiao, et al.
Published: (2026)
Balancing Learning Rates Across Layers: Exact Two-Step Dynamics and Optimal Scaling in Linear Neural Networks
by: Pang, Tianyu, et al.
Published: (2026)
by: Pang, Tianyu, et al.
Published: (2026)
Multi-Probe Zero Collision Hash (MPZCH): Mitigating Embedding Collisions and Enhancing Model Freshness in Large-Scale Recommenders
by: Zhao, Ziliang, et al.
Published: (2026)
by: Zhao, Ziliang, et al.
Published: (2026)
Similar Items
-
Soft Prompts for Evaluation: Measuring Conditional Distance of Capabilities
by: Nordby, Ross
Published: (2025) -
Benchmarking Deception Probes via Black-to-White Performance Boosts
by: Parrack, Avi, et al.
Published: (2025) -
The Disparate Benefits of Deep Ensembles
by: Schweighofer, Kajetan, et al.
Published: (2024) -
Optimal Representation Size: High-Dimensional Analysis of Pretraining and Linear Probing
by: Njaradi, Valentina, et al.
Published: (2026) -
Probe-then-Commit Multi-Objective Bandits: Theoretical Benefits of Limited Multi-Arm Feedback
by: Shi, Ming
Published: (2026)