:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wang, Liyuan, Xie, Jingyi, Zhang, Xingxing, Su, Hang, Zhu, Jun
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2407.05229
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Towards a General Framework for Continual Learning with Pre-training
by: Wang, Liyuan, et al.
Published: (2023)

HiDe-LLaVA: Hierarchical Decoupling for Continual Instruction Tuning of Multimodal Large Language Model
by: Guo, Haiyang, et al.
Published: (2025)

A Comprehensive Survey of Continual Learning: Theory, Method and Application
by: Wang, Liyuan, et al.
Published: (2023)

Safety Alignment as Continual Learning: Mitigating the Alignment Tax via Orthogonal Gradient Projection
by: Sun, Guanglong, et al.
Published: (2026)

HiFT: A Hierarchical Full Parameter Fine-Tuning Strategy
by: Liu, Yongkang, et al.
Published: (2024)

Gradient Projection For Continual Parameter-Efficient Tuning
by: Qiao, Jingyang, et al.
Published: (2024)

HiDe: Rethinking The Zoom-IN method in High Resolution MLLMs via Hierarchical Decoupling
by: Liu, Xianjie, et al.
Published: (2025)

Aligning Diffusion Behaviors with Q-functions for Efficient Continuous Control
by: Chen, Huayu, et al.
Published: (2024)

PEAC: Unsupervised Pre-training for Cross-Embodiment Reinforcement Learning
by: Ying, Chengyang, et al.
Published: (2024)

HiBid: A Cross-Channel Constrained Bidding System with Budget Allocation by Hierarchical Offline Deep Reinforcement Learning
by: Wang, Hao, et al.
Published: (2023)

Fourier Controller Networks for Real-Time Decision-Making in Embodied Learning
by: Tan, Hengkai, et al.
Published: (2024)

Tackling Noisy Labels with Network Parameter Additive Decomposition
by: Wang, Jingyi, et al.
Published: (2024)

Explainable Hierarchical Deep Learning Neural Networks (Ex-HiDeNN)
by: Batley, Reza T., et al.
Published: (2025)

Graph-Based Spectral Decomposition for Parameter Coordination in Language Model Fine-Tuning
by: Zhang, Hanlu, et al.
Published: (2025)

QUAD: Quantization and Parameter-Efficient Tuning of LLM with Activation Decomposition
by: Hu, Yuxuan, et al.
Published: (2025)

ManiBox: Enhancing Embodied Spatial Generalization via Scalable Simulation Data Generations
by: Tan, Hengkai, et al.
Published: (2024)

On Catastrophic Forgetting in Low-Rank Decomposition-Based Parameter-Efficient Fine-Tuning
by: Ahmad, Muhammad, et al.
Published: (2026)

Sparse Orthogonal Parameters Tuning for Continual Learning
by: Ning, Kun-Peng, et al.
Published: (2024)

Continual Fine-Tuning with Provably Accurate and Parameter-Free Task Retrieval
by: Le, Hang Thi-Thuy, et al.
Published: (2026)

Hierarchical Reinforcement Learning for Optimal Agent Grouping in Cooperative Systems
by: Hu, Liyuan
Published: (2025)

Parameter-Efficient Continual Fine-Tuning: A Survey
by: Coleman, Eric Nuertey, et al.
Published: (2025)

PACE: Pretrained Audio Continual Learning
by: Li, Chang, et al.
Published: (2026)

Hi-GMAE: Hierarchical Graph Masked Autoencoders
by: Liu, Chuang, et al.
Published: (2024)

Parameter-Efficient Tuning Large Language Models for Graph Representation Learning
by: Zhu, Qi, et al.
Published: (2024)

Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning
by: Joo, Hyeong-Gun, et al.
Published: (2025)

HiMAC: Hierarchical Macro-Micro Learning for Long-Horizon LLM Agents
by: Jin, Hongbo, et al.
Published: (2026)

Hi-ZFO: Hierarchical Zeroth- and First-Order LLM Fine-Tuning via Importance-Guided Tensor Selection
by: Jin, Feihu, et al.
Published: (2026)

SAFE: Slow and Fast Parameter-Efficient Tuning for Continual Learning with Pre-Trained Models
by: Zhao, Linglan, et al.
Published: (2024)

HiHa: Introducing Hierarchical Harmonic Decomposition to Implicit Neural Compression for Atmospheric Data
by: Xu, Zhewen, et al.
Published: (2024)

Parameter-Efficient Fine-Tuning for Continual Learning: A Neural Tangent Kernel Perspective
by: Liu, Jingren, et al.
Published: (2024)

F-Adapter: Frequency-Adaptive Parameter-Efficient Fine-Tuning in Scientific Machine Learning
by: Zhang, Hangwei, et al.
Published: (2025)

Meta-Learning Hyperparameters for Parameter Efficient Fine-Tuning
by: Tian, Zichen, et al.
Published: (2026)

Beyond Sharpness: A Flatness Decomposition Framework for Efficient Continual Learning
by: Chen, Yanan, et al.
Published: (2026)

HiCL: Hippocampal-Inspired Continual Learning
by: Kapoor, Kushal, et al.
Published: (2025)

Efficient machine unlearning with minimax optimality
by: Xie, Jingyi, et al.
Published: (2026)

HiPO: Hierarchical Preference Optimization for Adaptive Reasoning in LLMs
by: Kachroo, Darsh, et al.
Published: (2026)

Efficient Hyperparameter Tuning via Trajectory Invariance Principle
by: Li, Bingrui, et al.
Published: (2025)

HiPRAG: Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation
by: Wu, Peilin, et al.
Published: (2025)

HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation
by: Su, Weijie J., et al.
Published: (2018)

Optimizing Specific and Shared Parameters for Efficient Parameter Tuning
by: Nguyen, Van-Anh, et al.
Published: (2025)