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cs.AI2026
HyQuant: Hybrid-Precision Quantization for LLM Attention
Jiatong Ding, Bingxin Xing, Yu Zhang +9
Quantization has been widely adopted in LLM training and inference to reduce cost and improve efficiency. However, low-bit quantization of the \emph{attention} module often introdu…
cs.AI2026
EntropyMoE: Entropy-Aware Sparse Expert Routing for Tokenizer-Free LLMs
Bo Liu, Muxuab Yu, Yu Zhang +2
Recent byte-level large language models (LLMs) have made tokenizer-free modeling increasingly competitive by grouping bytes into dynamically sized patches. However, existing byte-p…