Learning When to Trust LLM Priors: A Validated Framework for Semantic Prior Integration
Fuente:
arXiv
Guardado en:
| Autores principales: | Zhang, Erica, Sagan, Naomi, Tse, Danny, Zhang, Fangzhao, Pilanci, Mert, Blanchet, Jose |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
por: Zhang, Erica, et al.
Publicado: (2024)
por: Zhang, Erica, et al.
Publicado: (2024)
Analyzing Neural Network-Based Generative Diffusion Models through Convex Optimization
por: Zhang, Fangzhao, et al.
Publicado: (2024)
por: Zhang, Fangzhao, et al.
Publicado: (2024)
Spectral Adapter: Fine-Tuning in Spectral Space
por: Zhang, Fangzhao, et al.
Publicado: (2024)
por: Zhang, Fangzhao, et al.
Publicado: (2024)
Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models
por: Zhang, Fangzhao, et al.
Publicado: (2024)
por: Zhang, Fangzhao, et al.
Publicado: (2024)
LLM-Lasso: A Robust Framework for Domain-Informed Feature Selection and Regularization
por: Zhang, Erica, et al.
Publicado: (2025)
por: Zhang, Erica, et al.
Publicado: (2025)
Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing
por: Romanov, Elad, et al.
Publicado: (2024)
por: Romanov, Elad, et al.
Publicado: (2024)
Optimizer-Induced Mode Connectivity: From AdamW to Muon
por: Zhang, Fangzhao, et al.
Publicado: (2026)
por: Zhang, Fangzhao, et al.
Publicado: (2026)
When Should Humans Step In? Optimal Human Dispatching in AI-Assisted Decisions
por: Tan, Lezhi, et al.
Publicado: (2026)
por: Tan, Lezhi, et al.
Publicado: (2026)
Compressing Large Language Models using Low Rank and Low Precision Decomposition
por: Saha, Rajarshi, et al.
Publicado: (2024)
por: Saha, Rajarshi, et al.
Publicado: (2024)
Optimal Shrinkage for Distributed Second-Order Optimization
por: Zhang, Fangzhao, et al.
Publicado: (2024)
por: Zhang, Fangzhao, et al.
Publicado: (2024)
Unveiling Hidden Convexity in Deep Learning: a Sparse Signal Processing Perspective
por: Zeger, Emi, et al.
Publicado: (2026)
por: Zeger, Emi, et al.
Publicado: (2026)
From Complexity to Clarity: Analytical Expressions of Deep Neural Network Weights via Clifford's Geometric Algebra and Convexity
por: Pilanci, Mert
Publicado: (2023)
por: Pilanci, Mert
Publicado: (2023)
Optimal Sets and Solution Paths of ReLU Networks
por: Mishkin, Aaron, et al.
Publicado: (2023)
por: Mishkin, Aaron, et al.
Publicado: (2023)
Convex Distillation: Efficient Compression of Deep Networks via Convex Optimization
por: Varshney, Prateek, et al.
Publicado: (2024)
por: Varshney, Prateek, et al.
Publicado: (2024)
Black Boxes and Looking Glasses: Multilevel Symmetries, Reflection Planes, and Convex Optimization in Deep Networks
por: Zeger, Emi, et al.
Publicado: (2024)
por: Zeger, Emi, et al.
Publicado: (2024)
Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time
por: Kim, Sungyoon, et al.
Publicado: (2024)
por: Kim, Sungyoon, et al.
Publicado: (2024)
LLM-Prior: A Framework for Knowledge-Driven Prior Elicitation and Aggregation
por: Huang, Yongchao
Publicado: (2025)
por: Huang, Yongchao
Publicado: (2025)
A Recovery Guarantee for Sparse Neural Networks
por: Fridovich-Keil, Sara, et al.
Publicado: (2025)
por: Fridovich-Keil, Sara, et al.
Publicado: (2025)
CRONOS: Enhancing Deep Learning with Scalable GPU Accelerated Convex Neural Networks
por: Feng, Miria, et al.
Publicado: (2024)
por: Feng, Miria, et al.
Publicado: (2024)
Exploring the loss landscape of regularized neural networks via convex duality
por: Kim, Sungyoon, et al.
Publicado: (2024)
por: Kim, Sungyoon, et al.
Publicado: (2024)
Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model Classes and Cone Decompositions
por: Mishkin, Aaron, et al.
Publicado: (2022)
por: Mishkin, Aaron, et al.
Publicado: (2022)
Convex Optimization for Alignment and Preference Learning on a Single GPU
por: Feng, Miria, et al.
Publicado: (2026)
por: Feng, Miria, et al.
Publicado: (2026)
Thinking While Listening: Simple Test Time Scaling For Audio Classification
por: Verma, Prateek, et al.
Publicado: (2025)
por: Verma, Prateek, et al.
Publicado: (2025)
Large Language Models Implicitly Learn to See and Hear Just By Reading
por: Verma, Prateek, et al.
Publicado: (2025)
por: Verma, Prateek, et al.
Publicado: (2025)
Adaptive Large Language Models By Layerwise Attention Shortcuts
por: Verma, Prateek, et al.
Publicado: (2024)
por: Verma, Prateek, et al.
Publicado: (2024)
Towards Signal Processing In Large Language Models
por: Verma, Prateek, et al.
Publicado: (2024)
por: Verma, Prateek, et al.
Publicado: (2024)
Faster Convergence of Stochastic Accelerated Gradient Descent under Interpolation
por: Mishkin, Aaron, et al.
Publicado: (2024)
por: Mishkin, Aaron, et al.
Publicado: (2024)
Adversarial Training of Two-Layer Polynomial and ReLU Activation Networks via Convex Optimization
por: Kuelbs, Daniel, et al.
Publicado: (2024)
por: Kuelbs, Daniel, et al.
Publicado: (2024)
AdaPTwin: Low-Cost Adaptive Compression of Product Twins in Transformers
por: Biju, Emil, et al.
Publicado: (2024)
por: Biju, Emil, et al.
Publicado: (2024)
Adaptive Inference: Theoretical Limits and Unexplored Opportunities
por: Hor, Soheil, et al.
Publicado: (2024)
por: Hor, Soheil, et al.
Publicado: (2024)
Convex Low-resource Accent-Robust Language Detection in Speech Recognition
por: Feng, Miria, et al.
Publicado: (2026)
por: Feng, Miria, et al.
Publicado: (2026)
PRCD-MAP: Learning How Much to Trust Imperfect Priors in Causal Discovery
por: Shan, Xihang, et al.
Publicado: (2026)
por: Shan, Xihang, et al.
Publicado: (2026)
When Priors Backfire: On the Vulnerability of Unlearnable Examples to Pretraining
por: Li, Zhihao, et al.
Publicado: (2026)
por: Li, Zhihao, et al.
Publicado: (2026)
MatRL: Provably Generalizable Iterative Algorithm Discovery via Monte-Carlo Tree Search
por: Kim, Sungyoon, et al.
Publicado: (2025)
por: Kim, Sungyoon, et al.
Publicado: (2025)
LLM Priors for ERM over Programs
por: Singhal, Shivam, et al.
Publicado: (2025)
por: Singhal, Shivam, et al.
Publicado: (2025)
Residual Prior Diffusion: A Probabilistic Framework Integrating Coarse Latent Priors with Diffusion Models
por: Kutsuna, Takuro
Publicado: (2025)
por: Kutsuna, Takuro
Publicado: (2025)
Prior Learning in Introspective VAEs
por: Athanasiadis, Ioannis, et al.
Publicado: (2024)
por: Athanasiadis, Ioannis, et al.
Publicado: (2024)
LLM Sparsity Prior for Robust Feature Selection
por: Skinner, Caleb, et al.
Publicado: (2026)
por: Skinner, Caleb, et al.
Publicado: (2026)
Efficient Reinforcement Learning with Large Language Model Priors
por: Yan, Xue, et al.
Publicado: (2024)
por: Yan, Xue, et al.
Publicado: (2024)
A KL-regularization Framework for Learning to Plan with Adaptive Priors
por: Serra-Gomez, Álvaro, et al.
Publicado: (2025)
por: Serra-Gomez, Álvaro, et al.
Publicado: (2025)
Ejemplares similares
-
Active Learning of Deep Neural Networks via Gradient-Free Cutting Planes
por: Zhang, Erica, et al.
Publicado: (2024) -
Analyzing Neural Network-Based Generative Diffusion Models through Convex Optimization
por: Zhang, Fangzhao, et al.
Publicado: (2024) -
Spectral Adapter: Fine-Tuning in Spectral Space
por: Zhang, Fangzhao, et al.
Publicado: (2024) -
Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models
por: Zhang, Fangzhao, et al.
Publicado: (2024) -
LLM-Lasso: A Robust Framework for Domain-Informed Feature Selection and Regularization
por: Zhang, Erica, et al.
Publicado: (2025)