Copertina

ZETA: Leveraging Z-order Curves for Efficient Top-k Attention

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zeng, Qiuhao, Huang, Jerry, Lu, Peng, Xu, Gezheng, Chen, Boxing, Ling, Charles, Wang, Boyu
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Calibrated Language Models and How to Find Them with Label Smoothing
di: Huang, Jerry, et al.
Pubblicazione: (2025)

Mamba Modulation: On the Length Generalization of Mamba
di: Lu, Peng, et al.
Pubblicazione: (2025)

Homophily Enhanced Graph Domain Adaptation
di: Fang, Ruiyi, et al.
Pubblicazione: (2025)

Toward Better Generalization in Few-Shot Learning through the Meta-Component Combination
di: Zeng, Qiuhao
Pubblicazione: (2025)

Optimizing Partial Area Under the Top-k Curve: Theory and Practice
di: Wang, Zitai, et al.
Pubblicazione: (2022)

Attention Dispersion in Dynamic Graph Transformers: Diagnosis and a Transferable Fix
di: Zhang, Jinhao, et al.
Pubblicazione: (2026)

On the Benefits of Attribute-Driven Graph Domain Adaptation
di: Fang, Ruiyi, et al.
Pubblicazione: (2025)

HATA: Trainable and Hardware-Efficient Hash-Aware Top-k Attention for Scalable Large Model Inference
di: Gong, Ping, et al.
Pubblicazione: (2025)

Entropy-Guided Dynamic Tokens for Graph-LLM Alignment in Molecular Understanding
di: Jing, Zihao, et al.
Pubblicazione: (2026)

A Mathematical Theory of Top-$k$ Sparse Attention via Total Variation Distance
di: Tzachristas, Georgios, et al.
Pubblicazione: (2025)

Do Robot Snakes Dream like Electric Sheep? Investigating the Effects of Architectural Inductive Biases on Hallucination
di: Huang, Jerry, et al.
Pubblicazione: (2024)

PoTPTQ: A Two-step Power-of-Two Post-training for LLMs
di: Wang, Xinyu, et al.
Pubblicazione: (2025)

Scaling-Aware Adapter for Structure-Grounded LLM Reasoning
di: Jing, Zihao, et al.
Pubblicazione: (2026)

Leveraging Group Classification with Descending Soft Labeling for Deep Imbalanced Regression
di: Pu, Ruizhi, et al.
Pubblicazione: (2024)

HiRE: High Recall Approximate Top-$k$ Estimation for Efficient LLM Inference
di: L, Yashas Samaga B, et al.
Pubblicazione: (2024)

SCOUT: Toward Sub-Quadratic Attention via Segment Compression for Optimized Utility in Transformers
di: Jafari, Aref, et al.
Pubblicazione: (2025)

A Sensitivity-Driven Expert Allocation Method in LoRA-MoE for Efficient Fine-Tuning
di: Xu, Junzhou, et al.
Pubblicazione: (2025)

Leveraging Logical Rules in Knowledge Editing: A Cherry on the Top
di: Cheng, Keyuan, et al.
Pubblicazione: (2024)

Estimating Long-term Heterogeneous Dose-response Curve: Generalization Bound Leveraging Optimal Transport Weights
di: Yang, Zeqin, et al.
Pubblicazione: (2024)

Intersectional Unfairness Discovery
di: Xu, Gezheng, et al.
Pubblicazione: (2024)

Turn Waste into Worth: Rectifying Top-$k$ Router of MoE
di: Zeng, Zhiyuan, et al.
Pubblicazione: (2024)

Policy Gradient for Robust Markov Decision Processes
di: Wang, Qiuhao, et al.
Pubblicazione: (2024)

Shiva-DiT: Residual-Based Differentiable Top-$k$ Selection for Efficient Diffusion Transformers
di: Zhang, Jiaji, et al.
Pubblicazione: (2026)

Foundations of Top-$k$ Decoding For Language Models
di: Noarov, Georgy, et al.
Pubblicazione: (2025)

Personalized Top-k Set Queries Over Predicted Scores
di: Nia, Sohrab Namazi, et al.
Pubblicazione: (2025)

Nested-ReFT: Efficient Reinforcement Learning for Large Language Model Fine-Tuning via Off-Policy Rollouts
di: Heuillet, Maxime, et al.
Pubblicazione: (2025)

CurvGAD: Leveraging Curvature for Enhanced Graph Anomaly Detection
di: Grover, Karish, et al.
Pubblicazione: (2025)

Generalizing across Temporal Domains with Koopman Operators
di: Zeng, Qiuhao, et al.
Pubblicazione: (2024)

Training with Confidence: Catching Silent Errors in Deep Learning Training with Automated Proactive Checks
di: Jiang, Yuxuan, et al.
Pubblicazione: (2025)

Enhancing Generalization in Chain of Thought Reasoning for Smaller Models
di: Yin, Maxwell J., et al.
Pubblicazione: (2025)

Variational Autoencoder-Based Approach to Latent Feature Analysis on Efficient Representation of Power Load Monitoring Data
di: Xie, Boyu, et al.
Pubblicazione: (2025)

Towards Robust Knowledge Tracing Models via k-Sparse Attention
di: Huang, Shuyan, et al.
Pubblicazione: (2024)

$\mathbb{R}^{2k}$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval
di: Wang, Zihao, et al.
Pubblicazione: (2026)

Universal Approximation with Softmax Attention
di: Hu, Jerry Yao-Chieh, et al.
Pubblicazione: (2025)

Antithetic Sampling for Top-k Shapley Identification
di: Kolpaczki, Patrick, et al.
Pubblicazione: (2025)

TANGNN: a Concise, Scalable and Effective Graph Neural Networks with Top-m Attention Mechanism for Graph Representation Learning
di: E, Jiawei, et al.
Pubblicazione: (2024)

Baguan-TS: A Sequence-Native In-Context Learning Model for Time Series Forecasting with Covariates
di: Yang, Linxiao, et al.
Pubblicazione: (2026)

Double-P: Hierarchical Top-P Sparse Attention for Long-Context LLMs
di: Ni, Wentao, et al.
Pubblicazione: (2026)

ATP: Enabling Fast LLM Serving via Attention on Top Principal Keys
di: Niu, Yue, et al.
Pubblicazione: (2024)

EMA Policy Gradient: Taming Reinforcement Learning for LLMs with EMA Anchor and Top-k KL
di: Zhang, Lunjun, et al.
Pubblicazione: (2026)