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cs.LG2026
LoKiFormer: Locality-aware Attention with Decoupled Knowledge Memory for Efficient Large Language Model Pretraining
Qiuwu Chen, Zimo Liu, Yuchen Li +8
Large language models (LLMs) have achieved remarkable breakthroughs across various applications. However, their architectures remain inefficient in pretraining due to two main limi…
cs.CL2026
Latent-Condensed Transformer for Efficient Long Context Modeling
Zeng You, Yaofo Chen, Qiuwu Chen +5
Large language models (LLMs) face significant challenges in processing long contexts due to the linear growth of the key-value (KV) cache and quadratic complexity of self-attention…
cs.CL2026
Training-free Context-adaptive Attention for Efficient Long Context Modeling
Zeng You, Yaofo Chen, Shuhai Zhang +5
Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing tasks. These capabilities stem primarily from the self-att…