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All SourcesarXiv
#Sliding Window Attention

HySparse: A Hybrid Sparse Attention Architecture with Oracle Token Selection and KV Cache Sharing

Intermediate
Yizhao Gao, Jianyu Wei et al.Feb 3arXiv

HySparse is a new way for AI models to pay attention that mixes a few full attention layers with many fast, memory‑saving sparse layers.

#Hybrid Sparse Attention#Oracle Token Selection#KV Cache Sharing

MiMo-V2-Flash Technical Report

Intermediate
Xiaomi LLM-Core Team, : et al.Jan 6arXiv

MiMo-V2-Flash is a giant but efficient language model that uses a team-of-experts design to think well while staying fast.

#Mixture-of-Experts#Sliding Window Attention#Global Attention

K-EXAONE Technical Report

Intermediate
Eunbi Choi, Kibong Choi et al.Jan 5arXiv

K-EXAONE is a super-sized language model that speaks six languages and can read very long documents (up to 256,000 tokens) without forgetting important details.

#Mixture-of-Experts#Hybrid Attention#Sliding Window Attention

SWAA: Sliding Window Attention Adaptation for Efficient Long-Context LLMs Without Pretraining

Intermediate
Yijiong Yu, Jiale Liu et al.Dec 11arXiv

Long texts make standard attention in large language models very slow because it checks every word against every other word.

#Sliding Window Attention#SWAA#FA Decode