3 papers
cs.LG2026
An Empirical Study of openPangu Quantization on Ascend NPUs
Tong Shi, Jiacheng Wang, Hui Xie +4
openPangu models are attractive targets for private and domestic large-language-model deployment, yet their robustness under aggressive post-training quantization on Ascend NPUs ha…
cs.LG2026
Patch the Distribution Mismatch: RL Rewriting Agent for Stable Off-Policy SFT
Jiacheng Wang, Ping Jian, Zhen Yang +3
Large language models (LLMs) have made rapid progress, yet adapting them to downstream scenarios still commonly relies on supervised fine-tuning (SFT). When downstream data exhibit…
cs.CV2026
Can LLMs See Without Pixels? Benchmarking Spatial Intelligence from Textual Descriptions
Zhongbin Guo, Zhen Yang, Yushan Li +6
Recent advancements in Spatial Intelligence (SI) have predominantly relied on Vision-Language Models (VLMs), yet a critical question remains: does spatial understanding originate f…