arXiv 2609.32712 · cs.AI · 2026-09-26
MassAlloc Attention: Let Attention Allocate Its Own Compute
Jingze Shi, Zhangyang Peng, Xianduo Li, Yanlin Qi, Xiaotian Lin, Haoxian Chen, Liangdong Wang, Guang Liu 等 9 人
Beijing Academy of Artificial Intelligence
在最新榜 #81 本站收录于 2026-10-21
一句话要点
MALA 注意力按每个位置的贡献自适应分配计算,跳过贡献极小的部分以提速。
MALA attention allocates post-score computation by normalised contribution, skipping negligible work to save compute.
阅读 arXiv 原文 PDF Hugging Face 讨论 代码仓库
主题与学科
同主题:高效训练与推理
- The Teacher Is a Direction, Not a Destination: Extrapolating RL-Induced Representation Residuals in On-Policy Distillation ▲511
- Scaling Properties of Same-Family On-Policy Distillation ▲327
- Beyond Domain-Routed Supervision: Cross-Teacher Guarding for Multi-Teacher On-Policy Distillation ▲251
- On-Policy or Off-Policy Learning? A Systematic Study of Distillation Dynamics ▲205
- Beyond Teacher Assignment: Domain-Normalized Multi-Teacher On-Policy Distillation ▲181
数据说明
元数据来自 arXiv API(已核实);点赞来自 Hugging Face 每日论文;引用来自 Semantic Scholar。最近刷新 2026-10-22。
要点由本站根据摘要自写,不转载摘要原文,请阅读原文。