Copertina

CoreQ: Learning-Free Mismatch Correction and Successive Rounding for Quantization

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Cha, Seohyeon, Chen, Huancheng, Kim, Dongjun, Zhang, Haoran, Chan, Kevin, de Veciana, Gustavo, Vikalo, Haris
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Online Learning for Multi-Layer Hierarchical Inference under Partial and Policy-Dependent Feedback
di: Zhang, Haoran, et al.
Pubblicazione: (2026)

FedRot-LoRA: Mitigating Rotational Misalignment in Federated LoRA
di: Zhang, Haoran, et al.
Pubblicazione: (2026)

Task-Agnostic Federated Continual Learning via Replay-Free Gradient Projection
di: Cha, Seohyeon, et al.
Pubblicazione: (2025)

Batching-Aware Joint Model Onloading and Offloading for Hierarchical Multi-Task Inference
di: Cha, Seohyeon, et al.
Pubblicazione: (2025)

Foundation-Preserving Adaptation via Generalized Rayleigh-Quotient Optimization
di: Kim, Dongjun, et al.
Pubblicazione: (2026)

Recovering Labels from Local Updates in Federated Learning
di: Chen, Huancheng, et al.
Pubblicazione: (2024)

Heterogeneity-Guided Client Sampling: Towards Fast and Efficient Non-IID Federated Learning
di: Chen, Huancheng, et al.
Pubblicazione: (2023)

Federated Self-Supervised Learning for Automatic Modulation Classification under Non-IID and Class-Imbalanced Data
di: Akram, Usman, et al.
Pubblicazione: (2025)

Optimal Resource Allocation for ML Model Training and Deployment under Concept Drift
di: Beytur, Hasan Burhan, et al.
Pubblicazione: (2025)

GeFL: Model-Agnostic Federated Learning with Generative Models
di: Kang, Honggu, et al.
Pubblicazione: (2024)

When Is Rank-1 Steering Cheap? Geometry, Granularity, and Budgeted Search
di: Robertson, John T., et al.
Pubblicazione: (2026)

Training-Free Layout-to-Image Generation with Marginal Attention Constraints
di: Chen, Huancheng, et al.
Pubblicazione: (2024)

NeFL: Nested Model Scaling for Federated Learning with System Heterogeneous Clients
di: Kang, Honggu, et al.
Pubblicazione: (2023)

FlexRound: Learnable Rounding based on Element-wise Division for Post-Training Quantization
di: Lee, Jung Hyun, et al.
Pubblicazione: (2023)

Training-Free Safe Denoisers for Safe Use of Diffusion Models
di: Kim, Mingyu, et al.
Pubblicazione: (2025)

Rounding-Guided Backdoor Injection in Deep Learning Model Quantization
di: Chen, Xiangxiang, et al.
Pubblicazione: (2025)

Your Agents Are Aging Too: Agent Lifespan Engineering for Deployed Systems
di: Zhu, Jianing, et al.
Pubblicazione: (2026)

Learning to Explore for Stochastic Gradient MCMC
di: Kim, SeungHyun, et al.
Pubblicazione: (2024)

LoopQ: Quantization for Recursive Transformers
di: Fang, Rui, et al.
Pubblicazione: (2026)

Missing Old Logits in Asynchronous Agentic RL: Semantic Mismatch and Repair Methods for Off-Policy Correction
di: Guan, Zhong, et al.
Pubblicazione: (2026)

HeadQ: Model-Visible Distortion and Score-Space Correction for KV-Cache Quantization
di: Williams, Jorge L. Ruiz
Pubblicazione: (2026)

FOSSIL: Regret-Minimizing Curriculum Learning for Metadata-Free and Low-Data Mpox Diagnosis
di: Han, Sahng-Min, et al.
Pubblicazione: (2025)

Calibration and Transformation-Free Weight-Only LLMs Quantization via Dynamic Grouping
di: Zheng, Xinzhe, et al.
Pubblicazione: (2025)

FM3Q: Factorized Multi-Agent MiniMax Q-Learning for Two-Team Zero-Sum Markov Game
di: Hu, Guangzheng, et al.
Pubblicazione: (2024)

GlowQ: Group-Shared LOw-Rank Approximation for Quantized LLMs
di: An, Selim, et al.
Pubblicazione: (2026)

MolDA: Molecular Understanding and Generation via Large Language Diffusion Model
di: Shin, Seohyeon, et al.
Pubblicazione: (2026)

Q-DIVER: Integrated Quantum Transfer Learning and Differentiable Quantum Architecture Search with EEG Data
di: Park, Junghoon Justin, et al.
Pubblicazione: (2026)

Transformers as Implicit State Estimators: In-Context Learning in Dynamical Systems
di: Akram, Usman, et al.
Pubblicazione: (2024)

Does Prior Data Matter? Exploring Joint Training in the Context of Few-Shot Class-Incremental Learning
di: Kim, Shiwon, et al.
Pubblicazione: (2025)

A Comprehensive Survey of Deep Learning for Time Series Forecasting: Architectural Diversity and Open Challenges
di: Kim, Jongseon, et al.
Pubblicazione: (2024)

Double Successive Over-Relaxation Q-Learning with an Extension to Deep Reinforcement Learning
di: R, Shreyas S
Pubblicazione: (2024)

Learning to Generate Unit Test via Adversarial Reinforcement Learning
di: Lee, Dongjun, et al.
Pubblicazione: (2025)

Navigation with QPHIL: Quantizing Planner for Hierarchical Implicit Q-Learning
di: Canesse, Alexi, et al.
Pubblicazione: (2024)

Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs
di: Cheng, Wenhua, et al.
Pubblicazione: (2023)

Jackpot: Optimal Budgeted Rejection Sampling for Extreme Actor-Policy Mismatch Reinforcement Learning
di: Chen, Zhuoming, et al.
Pubblicazione: (2026)

Mathematical Knowledge Graph-Driven Framework for Equation-Based Predictive and Reliable Additive Manufacturing
di: Cha, Yeongbin, et al.
Pubblicazione: (2026)

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models
di: Chen, Kejia, et al.
Pubblicazione: (2025)

CoAst: Validation-Free Contribution Assessment for Federated Learning based on Cross-Round Valuation
di: Wu, Hao, et al.
Pubblicazione: (2024)

OOM-Free Alpamayo via CPU-GPU Memory Swapping for Vision-Language-Action Models
di: Roh, Seungwoo, et al.
Pubblicazione: (2026)

Frictional Q-Learning
di: Kim, Hyunwoo, et al.
Pubblicazione: (2025)