Saved in:
| Main Authors: | Gao, Shangqian, Lin, Chi-Heng, Hua, Ting, Zheng, Tang, Shen, Yilin, Jin, Hongxia, Hsu, Yen-Chang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2410.11988 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing
by: Smith, James Seale, et al.
Published: (2025)
by: Smith, James Seale, et al.
Published: (2025)
MoDeGPT: Modular Decomposition for Large Language Model Compression
by: Lin, Chi-Heng, et al.
Published: (2024)
by: Lin, Chi-Heng, et al.
Published: (2024)
ToMoE: Converting Dense Large Language Models to Mixture-of-Experts through Dynamic Structural Pruning
by: Gao, Shangqian, et al.
Published: (2025)
by: Gao, Shangqian, et al.
Published: (2025)
DynaMo: Accelerating Language Model Inference with Dynamic Multi-Token Sampling
by: Tuli, Shikhar, et al.
Published: (2024)
by: Tuli, Shikhar, et al.
Published: (2024)
Dynamic Noise Preference Optimization: Self-Improvement of Large Language Models with Self-Synthetic Data
by: Yang, Haoyan, et al.
Published: (2025)
by: Yang, Haoyan, et al.
Published: (2025)
MossNet: Mixture of State-Space Experts is a Multi-Head Attention
by: Tuli, Shikhar, et al.
Published: (2025)
by: Tuli, Shikhar, et al.
Published: (2025)
DarwinLM: Evolutionary Structured Pruning of Large Language Models
by: Tang, Shengkun, et al.
Published: (2025)
by: Tang, Shengkun, et al.
Published: (2025)
Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA
by: Smith, James Seale, et al.
Published: (2023)
by: Smith, James Seale, et al.
Published: (2023)
Transformation-Augmented GRPO for Enhancing Exploration in Reasoning of Large Language Models
by: Le, Khiem, et al.
Published: (2026)
by: Le, Khiem, et al.
Published: (2026)
All-in-One Tuning and Structural Pruning for Domain-Specific LLMs
by: Lu, Lei, et al.
Published: (2024)
by: Lu, Lei, et al.
Published: (2024)
Jointly Training and Pruning CNNs via Learnable Agent Guidance and Alignment
by: Ganjdanesh, Alireza, et al.
Published: (2024)
by: Ganjdanesh, Alireza, et al.
Published: (2024)
Continual Diffusion with STAMINA: STack-And-Mask INcremental Adapters
by: Smith, James Seale, et al.
Published: (2023)
by: Smith, James Seale, et al.
Published: (2023)
MINI-LLM: Memory-Efficient Structured Pruning for Large Language Models
by: Cheng, Hongrong, et al.
Published: (2024)
by: Cheng, Hongrong, et al.
Published: (2024)
Prompt-prompted Adaptive Structured Pruning for Efficient LLM Generation
by: Dong, Harry, et al.
Published: (2024)
by: Dong, Harry, et al.
Published: (2024)
Sample-aware Adaptive Structured Pruning for Large Language Models
by: Kong, Jun, et al.
Published: (2025)
by: Kong, Jun, et al.
Published: (2025)
Olica: Efficient Structured Pruning of Large Language Models without Retraining
by: He, Jiujun, et al.
Published: (2025)
by: He, Jiujun, et al.
Published: (2025)
PIP: Perturbation-based Iterative Pruning for Large Language Models
by: Cao, Yi, et al.
Published: (2025)
by: Cao, Yi, et al.
Published: (2025)
High-Fidelity Pruning for Large Language Models
by: Zhu, Yijun, et al.
Published: (2026)
by: Zhu, Yijun, et al.
Published: (2026)
Pruning Large Language Models to Intra-module Low-rank Architecture with Transitional Activations
by: Shen, Bowen, et al.
Published: (2024)
by: Shen, Bowen, et al.
Published: (2024)
Measuring Taiwanese Mandarin Language Understanding
by: Chen, Po-Heng, et al.
Published: (2024)
by: Chen, Po-Heng, et al.
Published: (2024)
Toward Adaptive Large Language Models Structured Pruning via Hybrid-grained Weight Importance Assessment
by: Liu, Jun, et al.
Published: (2024)
by: Liu, Jun, et al.
Published: (2024)
Not All Prompts Are Made Equal: Prompt-based Pruning of Text-to-Image Diffusion Models
by: Ganjdanesh, Alireza, et al.
Published: (2024)
by: Ganjdanesh, Alireza, et al.
Published: (2024)
Adaptive Pruning for Large Language Models with Structural Importance Awareness
by: Zheng, Haotian, et al.
Published: (2024)
by: Zheng, Haotian, et al.
Published: (2024)
Unlocking Memorization in Large Language Models with Dynamic Soft Prompting
by: Wang, Zhepeng, et al.
Published: (2024)
by: Wang, Zhepeng, et al.
Published: (2024)
Any Large Language Model Can Be a Reliable Judge: Debiasing with a Reasoning-based Bias Detector
by: Yang, Haoyan, et al.
Published: (2025)
by: Yang, Haoyan, et al.
Published: (2025)
LLM-BIP: Structured Pruning for Large Language Models with Block-Wise Forward Importance Propagation
by: Wu, Haihang
Published: (2024)
by: Wu, Haihang
Published: (2024)
Instruction-Following Pruning for Large Language Models
by: Hou, Bairu, et al.
Published: (2025)
by: Hou, Bairu, et al.
Published: (2025)
Deterministic Differentiable Structured Pruning for Large Language Models
by: Huang, Weiyu, et al.
Published: (2026)
by: Huang, Weiyu, et al.
Published: (2026)
Improving Generalization in LLM Structured Pruning via Function-Aware Neuron Grouping
by: Yu, Tao, et al.
Published: (2025)
by: Yu, Tao, et al.
Published: (2025)
Understanding Performance Collapse in Layer-Pruned Large Language Models via Decision Representation Transitions
by: Shi, Boyu, et al.
Published: (2026)
by: Shi, Boyu, et al.
Published: (2026)
Backdooring Instruction-Tuned Large Language Models with Virtual Prompt Injection
by: Yan, Jun, et al.
Published: (2023)
by: Yan, Jun, et al.
Published: (2023)
Iterative Structured Pruning for Large Language Models with Multi-Domain Calibration
by: Wu, Guangxin, et al.
Published: (2026)
by: Wu, Guangxin, et al.
Published: (2026)
KVPruner: Structural Pruning for Faster and Memory-Efficient Large Language Models
by: Lv, Bo, et al.
Published: (2024)
by: Lv, Bo, et al.
Published: (2024)
Structural Pruning of Large Vision Language Models: A Comprehensive Study on Pruning Dynamics, Recovery, and Data Efficiency
by: Huang, Yiran, et al.
Published: (2026)
by: Huang, Yiran, et al.
Published: (2026)
Large Language Models on Graphs: A Comprehensive Survey
by: Jin, Bowen, et al.
Published: (2023)
by: Jin, Bowen, et al.
Published: (2023)
A Survey of Useful LLM Evaluation
by: Peng, Ji-Lun, et al.
Published: (2024)
by: Peng, Ji-Lun, et al.
Published: (2024)
Sink-Aware Pruning for Diffusion Language Models
by: Myrzakhan, Aidar, et al.
Published: (2026)
by: Myrzakhan, Aidar, et al.
Published: (2026)
SOP-Maze: Evaluating Large Language Models on Complicated Business Standard Operating Procedures
by: Wang, Jiaming, et al.
Published: (2025)
by: Wang, Jiaming, et al.
Published: (2025)
Enhancing Finite State Machine Design Automation with Large Language Models and Prompt Engineering Techniques
by: Lin, Qun-Kai, et al.
Published: (2025)
by: Lin, Qun-Kai, et al.
Published: (2025)
One-for-All Pruning: A Universal Model for Customized Compression of Large Language Models
by: Ye, Rongguang, et al.
Published: (2025)
by: Ye, Rongguang, et al.
Published: (2025)
Similar Items
-
FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing
by: Smith, James Seale, et al.
Published: (2025) -
MoDeGPT: Modular Decomposition for Large Language Model Compression
by: Lin, Chi-Heng, et al.
Published: (2024) -
ToMoE: Converting Dense Large Language Models to Mixture-of-Experts through Dynamic Structural Pruning
by: Gao, Shangqian, et al.
Published: (2025) -
DynaMo: Accelerating Language Model Inference with Dynamic Multi-Token Sampling
by: Tuli, Shikhar, et al.
Published: (2024) -
Dynamic Noise Preference Optimization: Self-Improvement of Large Language Models with Self-Synthetic Data
by: Yang, Haoyan, et al.
Published: (2025)