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 and 1 more
Beijing Academy of Artificial Intelligence
In latest · #81 Added on 2026-10-21
One-line takeaway
MALA attention allocates post-score computation by normalised contribution, skipping negligible work to save compute.
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。
Read on arXiv PDF Hugging Face discussion Code
Topics & disciplines
More on Efficient training & inference
- 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
About this data
Metadata from the arXiv API (verified); upvotes from Hugging Face Daily Papers; citations from Semantic Scholar. Last refreshed 2026-10-22.
The takeaway is written by AIMap from the abstract; the abstract itself is not reproduced — read the original.