Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration
Fuente:
arXiv
Saved in:
| Main Authors: | Yu, Zhongzhi, Wang, Zheng, Fu, Yonggan, Shi, Huihong, Shaikh, Khalid, Lin, Yingyan Celine |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search
by: Fu, Yonggan, et al.
Published: (2020)
by: Fu, Yonggan, et al.
Published: (2020)
When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
by: You, Haoran, et al.
Published: (2024)
by: You, Haoran, et al.
Published: (2024)
MG-Verilog: Multi-grained Dataset Towards Enhanced LLM-assisted Verilog Generation
by: Zhang, Yongan, et al.
Published: (2024)
by: Zhang, Yongan, et al.
Published: (2024)
ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks
by: You, Haoran, et al.
Published: (2022)
by: You, Haoran, et al.
Published: (2022)
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free
by: Qiu, Zihan, et al.
Published: (2025)
by: Qiu, Zihan, et al.
Published: (2025)
LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models
by: Shi, Dachuan, et al.
Published: (2025)
by: Shi, Dachuan, et al.
Published: (2025)
A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning
by: Fu, Yonggan, et al.
Published: (2021)
by: Fu, Yonggan, et al.
Published: (2021)
Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse
by: Fu, Zizhuo, et al.
Published: (2026)
by: Fu, Zizhuo, et al.
Published: (2026)
Garbage Attention in Large Language Models: BOS Sink Heads and Sink-aware Pruning
by: Sok, Jaewon, et al.
Published: (2026)
by: Sok, Jaewon, et al.
Published: (2026)
Attention Sinks in Diffusion Language Models
by: Rulli, Maximo Eduardo, et al.
Published: (2025)
by: Rulli, Maximo Eduardo, et al.
Published: (2025)
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
by: You, Haoran, et al.
Published: (2024)
by: You, Haoran, et al.
Published: (2024)
AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment
by: Fu, Yonggan, et al.
Published: (2024)
by: Fu, Yonggan, et al.
Published: (2024)
GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models
by: Fu, Yonggan, et al.
Published: (2023)
by: Fu, Yonggan, et al.
Published: (2023)
LongMamba: Enhancing Mamba's Long Context Capabilities via Training-Free Receptive Field Enlargement
by: Ye, Zhifan, et al.
Published: (2025)
by: Ye, Zhifan, et al.
Published: (2025)
CTR-Sink: Attention Sink for Language Models in Click-Through Rate Prediction
by: Li, Zixuan, et al.
Published: (2025)
by: Li, Zixuan, et al.
Published: (2025)
Efficient Streaming Language Models with Attention Sinks
by: Xiao, Guangxuan, et al.
Published: (2023)
by: Xiao, Guangxuan, et al.
Published: (2023)
Attention Sinks as Internal Signals for Hallucination Detection in Large Language Models
by: Binkowski, Jakub, et al.
Published: (2026)
by: Binkowski, Jakub, et al.
Published: (2026)
How Attention Sinks Emerge in Large Language Models: An Interpretability Perspective
by: Peng, Runyu, et al.
Published: (2026)
by: Peng, Runyu, et al.
Published: (2026)
When Attention Sink Emerges in Language Models: An Empirical View
by: Gu, Xiangming, et al.
Published: (2024)
by: Gu, Xiangming, et al.
Published: (2024)
The Spike, the Sparse and the Sink: Anatomy of Massive Activations and Attention Sinks
by: Sun, Shangwen, et al.
Published: (2026)
by: Sun, Shangwen, et al.
Published: (2026)
A Unified View of Attention and Residual Sinks: Outlier-Driven Rescaling is Essential for Transformer Training
by: Qiu, Zihan, et al.
Published: (2026)
by: Qiu, Zihan, et al.
Published: (2026)
Retrieval Backward Attention without Additional Training: Enhance Embeddings of Large Language Models via Repetition
by: Duan, Yifei, et al.
Published: (2025)
by: Duan, Yifei, et al.
Published: (2025)
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)
Omni-Recon: Harnessing Image-based Rendering for General-Purpose Neural Radiance Fields
by: Fu, Yonggan, et al.
Published: (2024)
by: Fu, Yonggan, et al.
Published: (2024)
Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing
by: Fu, Yonggan, et al.
Published: (2022)
by: Fu, Yonggan, et al.
Published: (2022)
KVSink: Understanding and Enhancing the Preservation of Attention Sinks in KV Cache Quantization for LLMs
by: Su, Zunhai, et al.
Published: (2025)
by: Su, Zunhai, et al.
Published: (2025)
On the Existence and Behavior of Secondary Attention Sinks
by: Wong, Jeffrey T. H., et al.
Published: (2025)
by: Wong, Jeffrey T. H., et al.
Published: (2025)
Sliding Window Attention Training for Efficient Large Language Models
by: Fu, Zichuan, et al.
Published: (2025)
by: Fu, Zichuan, et al.
Published: (2025)
Spectral Filters, Dark Signals, and Attention Sinks
by: Cancedda, Nicola
Published: (2024)
by: Cancedda, Nicola
Published: (2024)
ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer
by: You, Haoran, et al.
Published: (2023)
by: You, Haoran, et al.
Published: (2023)
Early-Bird GCNs: Graph-Network Co-Optimization Towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets
by: You, Haoran, et al.
Published: (2021)
by: You, Haoran, et al.
Published: (2021)
$R^2$-dLLM: Accelerating Diffusion Large Language Models via Spatio-Temporal Redundancy Reduction
by: Du, Zhenbang, et al.
Published: (2026)
by: Du, Zhenbang, et al.
Published: (2026)
Zero-Shot RTL Code Generation with Attention Sink Augmented Large Language Models
by: Sandal, Selim, et al.
Published: (2024)
by: Sandal, Selim, et al.
Published: (2024)
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency
by: Fu, Yonggan, et al.
Published: (2021)
by: Fu, Yonggan, et al.
Published: (2021)
Truth Forest: Toward Multi-Scale Truthfulness in Large Language Models through Intervention without Tuning
by: Chen, Zhongzhi, et al.
Published: (2023)
by: Chen, Zhongzhi, et al.
Published: (2023)
Harnessing the Unseen: The Hidden Influence of Intrinsic Knowledge in Long-Context Language Models
by: Fu, Yu, et al.
Published: (2025)
by: Fu, Yu, et al.
Published: (2025)
Enhanced Structured State Space Models via Grouped FIR Filtering and Attention Sink Mechanisms
by: Meng, Tian, et al.
Published: (2024)
by: Meng, Tian, et al.
Published: (2024)
Back Attention: Understanding and Enhancing Multi-Hop Reasoning in Large Language Models
by: Yu, Zeping, et al.
Published: (2025)
by: Yu, Zeping, et al.
Published: (2025)
HW-NAS-Bench:Hardware-Aware Neural Architecture Search Benchmark
by: Li, Chaojian, et al.
Published: (2021)
by: Li, Chaojian, et al.
Published: (2021)
Attention Sinks: A 'Catch, Tag, Release' Mechanism for Embeddings
by: Zhang, Stephen, et al.
Published: (2025)
by: Zhang, Stephen, et al.
Published: (2025)
Similar Items
-
Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search
by: Fu, Yonggan, et al.
Published: (2020) -
When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
by: You, Haoran, et al.
Published: (2024) -
MG-Verilog: Multi-grained Dataset Towards Enhanced LLM-assisted Verilog Generation
by: Zhang, Yongan, et al.
Published: (2024) -
ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks
by: You, Haoran, et al.
Published: (2022) -
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free
by: Qiu, Zihan, et al.
Published: (2025)