3 papers
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.AI2026
Dynamic Important Example Mining for Reinforcement Finetuning
Haoru Tan, Sitong Wu, Yanfeng Chen +9
Reinforcement fine-tuning (RFT) is increasingly used to strengthen the reasoning abilities of large models, yet its effectiveness is bound by how training data are selected and use…
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…