Cover Image

Accelerating Prefilling for Long-Context LLMs via Sparse Pattern Sharing

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Peng, Dan, Fu, Zhihui, Ye, Zewen, Song, Zhuoran, Wang, Jun
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

CritiPrefill: A Segment-wise Criticality-based Approach for Prefilling Acceleration in LLMs
by: Lv, Junlin, et al.
Published: (2024)

A Framework to Implement 1+N Multi-task Fine-tuning Pattern in LLMs Using the CGC-LORA Algorithm
by: Song, Chao, et al.
Published: (2024)

FlashPrefill: Instantaneous Pattern Discovery and Thresholding for Ultra-Fast Long-Context Prefilling
by: Fan, Qihang, et al.
Published: (2026)

Tactic: Adaptive Sparse Attention with Clustering and Distribution Fitting for Long-Context LLMs
by: Zhu, Kan, et al.
Published: (2025)

Block-Attention for Efficient Prefilling
by: Ma, Dongyang, et al.
Published: (2024)

SparsePO: Controlling Preference Alignment of LLMs via Sparse Token Masks
by: Christopoulou, Fenia, et al.
Published: (2024)

SampleAttention: Near-Lossless Acceleration of Long Context LLM Inference with Adaptive Structured Sparse Attention
by: Zhu, Qianchao, et al.
Published: (2024)

LongSafety: Enhance Safety for Long-Context LLMs
by: Huang, Mianqiu, et al.
Published: (2024)

TokenSelect: Efficient Long-Context Inference and Length Extrapolation for LLMs via Dynamic Token-Level KV Cache Selection
by: Wu, Wei, et al.
Published: (2024)

Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token Reduction
by: Shi, Zhenmei, et al.
Published: (2024)

Reward Is Enough: LLMs Are In-Context Reinforcement Learners
by: Song, Kefan, et al.
Published: (2025)

PocketLLM: Enabling On-Device Fine-Tuning for Personalized LLMs
by: Peng, Dan, et al.
Published: (2024)

Adapting LLMs for Efficient Context Processing through Soft Prompt Compression
by: Wang, Cangqing, et al.
Published: (2024)

100-LongBench: Are de facto Long-Context Benchmarks Literally Evaluating Long-Context Ability?
by: Yang, Wang, et al.
Published: (2025)

IntroLM: Introspective Language Models via Prefilling-Time Self-Evaluation
by: Kasnavieh, Hossein Hosseini, et al.
Published: (2026)

HSR-Enhanced Sparse Attention Acceleration
by: Chen, Bo, et al.
Published: (2024)

PowerFlow: Unlocking the Dual Nature of LLMs via Principled Distribution Matching
by: Chen, Ruishuo, et al.
Published: (2026)

PreFT: Prefill-only finetuning for efficient inference
by: Lanpouthakoun, Andrew, et al.
Published: (2026)

MoBA: Mixture of Block Attention for Long-Context LLMs
by: Lu, Enzhe, et al.
Published: (2025)

Long-Context LLMs Meet RAG: Overcoming Challenges for Long Inputs in RAG
by: Jin, Bowen, et al.
Published: (2024)

MiniCPM-SALA: Hybridizing Sparse and Linear Attention for Efficient Long-Context Modeling
by: MiniCPM Team, et al.
Published: (2026)

InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory
by: Xiao, Chaojun, et al.
Published: (2024)

AbsTopK: Rethinking Sparse Autoencoders For Bidirectional Features
by: Zhu, Xudong, et al.
Published: (2025)

VSPrefill: Vertical-Slash Sparse Attention with Lightweight Indexing for Long-Context Prefilling
by: Guanzhong, Chen
Published: (2026)

Long Exposure: Accelerating Parameter-Efficient Fine-Tuning for LLMs under Shadowy Sparsity
by: Wang, Tuowei, et al.
Published: (2025)

POP: Prefill-Only Pruning for Efficient Large Model Inference
by: He, Junhui, et al.
Published: (2026)

Prefill-Guided Thinking for zero-shot detection of AI-generated images
by: Kachwala, Zoher, et al.
Published: (2025)

In-Context Explainers: Harnessing LLMs for Explaining Black Box Models
by: Kroeger, Nicholas, et al.
Published: (2023)

CoPE: Clipped RoPE as A Scalable Free Lunch for Long Context LLMs
by: Li, Haoran, et al.
Published: (2026)

PISanitizer: Preventing Prompt Injection to Long-Context LLMs via Prompt Sanitization
by: Geng, Runpeng, et al.
Published: (2025)

SwiftKV: Fast Prefill-Optimized Inference with Knowledge-Preserving Model Transformation
by: Qiao, Aurick, et al.
Published: (2024)

Quokka: Accelerating Program Verification with LLMs via Invariant Synthesis
by: Wei, Anjiang, et al.
Published: (2025)

Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing
by: Le, Qi, et al.
Published: (2025)

ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
by: You, Haoran, et al.
Published: (2024)

From Compression to Expression: A Layerwise Analysis of In-Context Learning
by: Jiang, Jiachen, et al.
Published: (2025)

Artificial Hippocampus Networks for Efficient Long-Context Modeling
by: Fang, Yunhao, et al.
Published: (2025)

Prepacking: A Simple Method for Fast Prefilling and Increased Throughput in Large Language Models
by: Zhao, Siyan, et al.
Published: (2024)

Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach
by: Li, Zhuowan, et al.
Published: (2024)

EBFT: Effective and Block-Wise Fine-Tuning for Sparse LLMs
by: Guo, Song, et al.
Published: (2024)

Stress-Testing Long-Context Language Models with Lifelong ICL and Task Haystack
by: Xu, Xiaoyue, et al.
Published: (2024)