Q-Sparse: All Large Language Models can be Fully Sparsely-Activated
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Hongyu, Ma, Shuming, Wang, Ruiping, Wei, Furu |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
BitNet a4.8: 4-bit Activations for 1-bit LLMs
by: Wang, Hongyu, et al.
Published: (2024)
by: Wang, Hongyu, et al.
Published: (2024)
BitNet v2: Native 4-bit Activations with Hadamard Transformation for 1-bit LLMs
by: Wang, Hongyu, et al.
Published: (2025)
by: Wang, Hongyu, et al.
Published: (2025)
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
by: Ma, Shuming, et al.
Published: (2024)
by: Ma, Shuming, et al.
Published: (2024)
SparseEval: Efficient Evaluation of Large Language Models by Sparse Optimization
by: Zhang, Taolin, et al.
Published: (2026)
by: Zhang, Taolin, et al.
Published: (2026)
Auto-ICL: In-Context Learning without Human Supervision
by: Yang, Jinghan, et al.
Published: (2023)
by: Yang, Jinghan, et al.
Published: (2023)
CoreInfer: Accelerating Large Language Model Inference with Semantics-Inspired Adaptive Sparse Activation
by: Wang, Qinsi, et al.
Published: (2024)
by: Wang, Qinsi, et al.
Published: (2024)
BitNet b1.58 2B4T Technical Report
by: Ma, Shuming, et al.
Published: (2025)
by: Ma, Shuming, et al.
Published: (2025)
Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
by: Luo, Yuqi, et al.
Published: (2024)
by: Luo, Yuqi, et al.
Published: (2024)
Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models
by: Deng, Boyi, et al.
Published: (2026)
by: Deng, Boyi, et al.
Published: (2026)
Sparse Shift Autoencoders for Identifying Concepts from Large Language Model Activations
by: Joshi, Shruti, et al.
Published: (2025)
by: Joshi, Shruti, et al.
Published: (2025)
ROSE: Reordered SparseGPT for More Accurate One-Shot Large Language Models Pruning
by: Su, Mingluo, et al.
Published: (2026)
by: Su, Mingluo, et al.
Published: (2026)
First Activations Matter: Training-Free Methods for Dynamic Activation in Large Language Models
by: Ma, Chi, et al.
Published: (2024)
by: Ma, Chi, et al.
Published: (2024)
EdgeMoE: Empowering Sparse Large Language Models on Mobile Devices
by: Yi, Rongjie, et al.
Published: (2023)
by: Yi, Rongjie, et al.
Published: (2023)
Learn from the Past: Fast Sparse Indexing for Large Language Model Decoding
by: Yao, Feiyu, et al.
Published: (2025)
by: Yao, Feiyu, et al.
Published: (2025)
metabench -- A Sparse Benchmark of Reasoning and Knowledge in Large Language Models
by: Kipnis, Alex, et al.
Published: (2024)
by: Kipnis, Alex, et al.
Published: (2024)
Sparse-Autoencoder-Guided Internal Representation Unlearning for Large Language Models
by: Yamashita, Tomoya, et al.
Published: (2025)
by: Yamashita, Tomoya, et al.
Published: (2025)
Turbo Sparse: Achieving LLM SOTA Performance with Minimal Activated Parameters
by: Song, Yixin, et al.
Published: (2024)
by: Song, Yixin, et al.
Published: (2024)
Textual Aesthetics in Large Language Models
by: Jiang, Lingjie, et al.
Published: (2024)
by: Jiang, Lingjie, et al.
Published: (2024)
Scaling Sparse Fine-Tuning to Large Language Models
by: Ansell, Alan, et al.
Published: (2024)
by: Ansell, Alan, et al.
Published: (2024)
Prefixing Attention Sinks can Mitigate Activation Outliers for Large Language Model Quantization
by: Son, Seungwoo, et al.
Published: (2024)
by: Son, Seungwoo, et al.
Published: (2024)
In-context Autoencoder for Context Compression in a Large Language Model
by: Ge, Tao, et al.
Published: (2023)
by: Ge, Tao, et al.
Published: (2023)
Enhancing One-shot Pruned Pre-trained Language Models through Sparse-Dense-Sparse Mechanism
by: Li, Guanchen, et al.
Published: (2024)
by: Li, Guanchen, et al.
Published: (2024)
Saten: Sparse Augmented Tensor Networks for Post-Training Compression of Large Language Models
by: Solgi, Ryan, et al.
Published: (2025)
by: Solgi, Ryan, et al.
Published: (2025)
ProSparse: Introducing and Enhancing Intrinsic Activation Sparsity within Large Language Models
by: Song, Chenyang, et al.
Published: (2024)
by: Song, Chenyang, et al.
Published: (2024)
Sparse Layers are Critical to Scaling Looped Language Models
by: Lee, Ryan, et al.
Published: (2026)
by: Lee, Ryan, et al.
Published: (2026)
Bitnet.cpp: Efficient Edge Inference for Ternary LLMs
by: Wang, Jinheng, et al.
Published: (2025)
by: Wang, Jinheng, et al.
Published: (2025)
NeuroPrune: A Neuro-inspired Topological Sparse Training Algorithm for Large Language Models
by: Dhurandhar, Amit, et al.
Published: (2024)
by: Dhurandhar, Amit, et al.
Published: (2024)
Model Unlearning via Sparse Autoencoder Subspace Guided Projections
by: Wang, Xu, et al.
Published: (2025)
by: Wang, Xu, et al.
Published: (2025)
Sparse is Enough in Fine-tuning Pre-trained Large Language Models
by: Song, Weixi, et al.
Published: (2023)
by: Song, Weixi, et al.
Published: (2023)
JumpLoRA: Sparse Adapters for Continual Learning in Large Language Models
by: Dragomir, Alexandra, et al.
Published: (2026)
by: Dragomir, Alexandra, et al.
Published: (2026)
A Survey on Sparse Autoencoders: Interpreting the Internal Mechanisms of Large Language Models
by: Shu, Dong, et al.
Published: (2025)
by: Shu, Dong, et al.
Published: (2025)
Scaling Linear Attention with Sparse State Expansion
by: Pan, Yuqi, et al.
Published: (2025)
by: Pan, Yuqi, et al.
Published: (2025)
Sparse Autoencoders Enable Scalable and Reliable Circuit Identification in Language Models
by: O'Neill, Charles, et al.
Published: (2024)
by: O'Neill, Charles, et al.
Published: (2024)
MediSwift: Efficient Sparse Pre-trained Biomedical Language Models
by: Thangarasa, Vithursan, et al.
Published: (2024)
by: Thangarasa, Vithursan, et al.
Published: (2024)
SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability
by: Karvonen, Adam, et al.
Published: (2025)
by: Karvonen, Adam, et al.
Published: (2025)
Jacobian Sparse Autoencoders: Sparsify Computations, Not Just Activations
by: Farnik, Lucy, et al.
Published: (2025)
by: Farnik, Lucy, et al.
Published: (2025)
Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention
by: Yuan, Jingyang, et al.
Published: (2025)
by: Yuan, Jingyang, et al.
Published: (2025)
Let the Expert Stick to His Last: Expert-Specialized Fine-Tuning for Sparse Architectural Large Language Models
by: Wang, Zihan, et al.
Published: (2024)
by: Wang, Zihan, et al.
Published: (2024)
PowerAttention: Exponentially Scaling of Receptive Fields for Effective Sparse Attention
by: Chen, Lida, et al.
Published: (2025)
by: Chen, Lida, et al.
Published: (2025)
Steering LLMs? Actually, Sparse Autoencoders can outperform simple baselines
by: Jørgensen, Mikkel Godsk, et al.
Published: (2026)
by: Jørgensen, Mikkel Godsk, et al.
Published: (2026)
Similar Items
-
BitNet a4.8: 4-bit Activations for 1-bit LLMs
by: Wang, Hongyu, et al.
Published: (2024) -
BitNet v2: Native 4-bit Activations with Hadamard Transformation for 1-bit LLMs
by: Wang, Hongyu, et al.
Published: (2025) -
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
by: Ma, Shuming, et al.
Published: (2024) -
SparseEval: Efficient Evaluation of Large Language Models by Sparse Optimization
by: Zhang, Taolin, et al.
Published: (2026) -
Auto-ICL: In-Context Learning without Human Supervision
by: Yang, Jinghan, et al.
Published: (2023)