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Lunbin Zeng

MiniMax Sparse Attention coauthor and MiniMax-M1 recurring contributor. GitHub identifies Lunbin Zeng as a HUST master's student supervised by Xinggang Wang, with LLM/MLLM interests and a Scholar link. No high-confidence personal X account was found.

1 archived notes X: not-found Homepage GitHub

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Jun 24, 2026

MiniMax Sparse Attention

MiniMax Sparse Attention (MSA) 是 MiniMax M3 的长上下文技术核心：它在 GQA (Grouped Query Attention，分组查询注意力) 之上增加轻量 Index Branch，为每个 query token 和每个 GQA group 选择少量 KV blocks，再由 Main Branch 对被选 block 做精确 softmax attention；论文的强证据在于 109...

2606.13392-minimax-sparse-attention-m3 Sparse Attention Long Context MoE Architecture