Guardado en:
| Autores principales: | Kim, Eungyeup, Gu, Chenchen, Tiwari, Vashisth, Kolter, J. Zico |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2605.11209 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line
por: Kim, Eungyeup, et al.
Publicado: (2023)
por: Kim, Eungyeup, et al.
Publicado: (2023)
Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning
por: Xu, Yixuan Even, et al.
Publicado: (2025)
por: Xu, Yixuan Even, et al.
Publicado: (2025)
AcceleratedLiNGAM: Learning Causal DAGs at the speed of GPUs
por: Akinwande, Victor, et al.
Publicado: (2024)
por: Akinwande, Victor, et al.
Publicado: (2024)
Mimetic Initialization of MLPs
por: Trockman, Asher, et al.
Publicado: (2026)
por: Trockman, Asher, et al.
Publicado: (2026)
FUSE-ing Language Models: Zero-Shot Adapter Discovery for Prompt Optimization Across Tokenizers
por: Williams, Joshua Nathaniel, et al.
Publicado: (2024)
por: Williams, Joshua Nathaniel, et al.
Publicado: (2024)
Equilibrium Reasoners: Learning Attractors Enables Scalable Reasoning
por: Huang, Benhao, et al.
Publicado: (2026)
por: Huang, Benhao, et al.
Publicado: (2026)
Why is SAM Robust to Label Noise?
por: Baek, Christina, et al.
Publicado: (2024)
por: Baek, Christina, et al.
Publicado: (2024)
Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws
por: Jiang, Yiding, et al.
Publicado: (2024)
por: Jiang, Yiding, et al.
Publicado: (2024)
Joint Distillation for Fast Likelihood Evaluation and Sampling in Flow-based Models
por: Ai, Xinyue, et al.
Publicado: (2025)
por: Ai, Xinyue, et al.
Publicado: (2025)
OS-Harm: A Benchmark for Measuring Safety of Computer Use Agents
por: Kuntz, Thomas, et al.
Publicado: (2025)
por: Kuntz, Thomas, et al.
Publicado: (2025)
Predicting the Performance of Black-box LLMs through Follow-up Queries
por: Sam, Dylan, et al.
Publicado: (2025)
por: Sam, Dylan, et al.
Publicado: (2025)
Evaluating Language Model Reasoning about Confidential Information
por: Sam, Dylan, et al.
Publicado: (2025)
por: Sam, Dylan, et al.
Publicado: (2025)
One-Step Diffusion Distillation via Deep Equilibrium Models
por: Geng, Zhengyang, et al.
Publicado: (2023)
por: Geng, Zhengyang, et al.
Publicado: (2023)
Diffusing Differentiable Representations
por: Savani, Yash, et al.
Publicado: (2024)
por: Savani, Yash, et al.
Publicado: (2024)
Rethinking LLM Memorization through the Lens of Adversarial Compression
por: Schwarzschild, Avi, et al.
Publicado: (2024)
por: Schwarzschild, Avi, et al.
Publicado: (2024)
Generative Posterior Networks for Approximately Bayesian Epistemic Uncertainty Estimation
por: Roderick, Melrose, et al.
Publicado: (2023)
por: Roderick, Melrose, et al.
Publicado: (2023)
The Mixing method: low-rank coordinate descent for semidefinite programming with diagonal constraints
por: Wang, Po-Wei, et al.
Publicado: (2017)
por: Wang, Po-Wei, et al.
Publicado: (2017)
Context-Parametric Inversion: Why Instruction Finetuning Can Worsen Context Reliance
por: Goyal, Sachin, et al.
Publicado: (2024)
por: Goyal, Sachin, et al.
Publicado: (2024)
Massive Activations in Large Language Models
por: Sun, Mingjie, et al.
Publicado: (2024)
por: Sun, Mingjie, et al.
Publicado: (2024)
An Axiomatic Approach to Model-Agnostic Concept Explanations
por: Feng, Zhili, et al.
Publicado: (2024)
por: Feng, Zhili, et al.
Publicado: (2024)
Rethinking Distance Metrics for Counterfactual Explainability
por: Williams, Joshua Nathaniel, et al.
Publicado: (2024)
por: Williams, Joshua Nathaniel, et al.
Publicado: (2024)
AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents
por: Andriushchenko, Maksym, et al.
Publicado: (2024)
por: Andriushchenko, Maksym, et al.
Publicado: (2024)
Transformers to SSMs: Distilling Quadratic Knowledge to Subquadratic Models
por: Bick, Aviv, et al.
Publicado: (2024)
por: Bick, Aviv, et al.
Publicado: (2024)
A Simple and Effective Pruning Approach for Large Language Models
por: Sun, Mingjie, et al.
Publicado: (2023)
por: Sun, Mingjie, et al.
Publicado: (2023)
Looking beyond the next token
por: Thankaraj, Abitha, et al.
Publicado: (2025)
por: Thankaraj, Abitha, et al.
Publicado: (2025)
Predicting the Performance of Foundation Models via Agreement-on-the-Line
por: Saxena, Rahul, et al.
Publicado: (2024)
por: Saxena, Rahul, et al.
Publicado: (2024)
When Should We Introduce Safety Interventions During Pretraining?
por: Sam, Dylan, et al.
Publicado: (2026)
por: Sam, Dylan, et al.
Publicado: (2026)
Understanding Hallucinations in Diffusion Models through Mode Interpolation
por: Aithal, Sumukh K, et al.
Publicado: (2024)
por: Aithal, Sumukh K, et al.
Publicado: (2024)
Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression
por: Zhai, Runtian, et al.
Publicado: (2023)
por: Zhai, Runtian, et al.
Publicado: (2023)
Finetuning CLIP to Reason about Pairwise Differences
por: Sam, Dylan, et al.
Publicado: (2024)
por: Sam, Dylan, et al.
Publicado: (2024)
Prompt Recovery for Image Generation Models: A Comparative Study of Discrete Optimizers
por: Williams, Joshua Nathaniel, et al.
Publicado: (2024)
por: Williams, Joshua Nathaniel, et al.
Publicado: (2024)
Scaling Laws for Data Filtering -- Data Curation cannot be Compute Agnostic
por: Goyal, Sachin, et al.
Publicado: (2024)
por: Goyal, Sachin, et al.
Publicado: (2024)
Bayesian Neural Networks with Domain Knowledge Priors
por: Sam, Dylan, et al.
Publicado: (2024)
por: Sam, Dylan, et al.
Publicado: (2024)
Superhuman AI for Stratego Using Self-Play Reinforcement Learning and Test-Time Search
por: Sokota, Samuel, et al.
Publicado: (2025)
por: Sokota, Samuel, et al.
Publicado: (2025)
Mimetic Initialization Helps State Space Models Learn to Recall
por: Trockman, Asher, et al.
Publicado: (2024)
por: Trockman, Asher, et al.
Publicado: (2024)
Weight Ensembling Improves Reasoning in Language Models
por: Dang, Xingyu, et al.
Publicado: (2025)
por: Dang, Xingyu, et al.
Publicado: (2025)
Forcing Diffuse Distributions out of Language Models
por: Zhang, Yiming, et al.
Publicado: (2024)
por: Zhang, Yiming, et al.
Publicado: (2024)
Mean Flows for One-step Generative Modeling
por: Geng, Zhengyang, et al.
Publicado: (2025)
por: Geng, Zhengyang, et al.
Publicado: (2025)
Consistency Models Made Easy
por: Geng, Zhengyang, et al.
Publicado: (2024)
por: Geng, Zhengyang, et al.
Publicado: (2024)
TOFU: A Task of Fictitious Unlearning for LLMs
por: Maini, Pratyush, et al.
Publicado: (2024)
por: Maini, Pratyush, et al.
Publicado: (2024)
Ejemplares similares
-
Test-Time Adaptation Induces Stronger Accuracy and Agreement-on-the-Line
por: Kim, Eungyeup, et al.
Publicado: (2023) -
Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning
por: Xu, Yixuan Even, et al.
Publicado: (2025) -
AcceleratedLiNGAM: Learning Causal DAGs at the speed of GPUs
por: Akinwande, Victor, et al.
Publicado: (2024) -
Mimetic Initialization of MLPs
por: Trockman, Asher, et al.
Publicado: (2026) -
FUSE-ing Language Models: Zero-Shot Adapter Discovery for Prompt Optimization Across Tokenizers
por: Williams, Joshua Nathaniel, et al.
Publicado: (2024)