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cs.LG2026
Higher-Dimensional Rotary Position Embedding
Yixing Li, Ruobing Xie, Yudong Zhang +3
Transformers rely on position embedding mechanisms in long context modeling in most cases. Rotary Position Embedding (RoPE) embeds positional information with independent 2D rotati…
cs.LG2026
DQuant: Accurate Low-bit Post-Training Weight Quantization for LLMs
Xianglong Yan, ChengZhu Bao, Zhiteng Li +5
Large language models (LLMs) deliver strong performance, but their high compute and memory costs make deployment difficult in resource-constrained scenarios. Weight-only post-train…