CORTEXA
← Browse

Feng Liu

5 papers indexed

arxivcs.LGcs.AIcs.CL2026-07-09Cited by 2

Towards Efficient Large Language Model Serving: A Survey on System-Aware KV Cache Optimization

Jiantong Jiang, Peiyu Yang, Rui Zhang, Feng Liu

Despite the rapid advancements of large language models (LLMs), LLM serving systems remain memory-intensive and costly. The key-value (KV) cache, which stores KV tensors during autoregressive decoding, is crucial for enabling low-latency, high-throughput LLM inference serving. In…

View free PDFSource page
crossref2026-07-02

Predicting Prognosis of Locoregionally Advanced Nasopharyngeal Carcinoma Using Machine Learning Models Based on Plasma Proteomics : A retrospectively registered Study

Yuyi Li, Chao Tan, Xiaoyu Chen, Weichang Zhu, Cuihong Jiang, Lili He, et al.

Abstract Background Patients with locoregionally advanced nasopharyngeal carcinoma (LA-NPC) exhibit heterogeneous short-term responses despite induction chemotherapy plus concurrent chemoradiotherapy, and effective plasma protein prognostic markers are lacking. This study aimed t…

View free PDFSource page
arxivcs.AI2026-06-29

SafePyramid: A Hierarchical Benchmark for In-context Policy Guardrailing

Jiacheng Zhang, Haoyu He, Sen Zhang, Shen Wang, Xiaolei Xu, Yuhao Sun, et al.

In real-world applications, guardrails are often expected to identify unsafe user-model interactions according to application-specific safety policies, rather than relying on predefined risk taxonomies. In this work, we study this setting under the paradigm of in-context policy g…

View free PDFSource page
arxivcs.LG2026-06-26

USAD: Uncertainty-aware Statistical Adversarial Detection

Zhijian Zhou, Xunye Tian, Jiacheng Zhang, Zesheng Ye, Yiyi Guo, Donghao Zhang, et al.

Statistical adversarial detection (SAD) treats detection as a two-sample test. Given a reference set of clean examples (CEs) and a batch of queries, potentially containing an unknown mixture of CEs and adversarial examples (AEs), SAD decides whether the query distribution drifts…

View free PDFSource page
crossrefElectronics2023-07-20Cited by 5

Digital Twin 3D System for Power Maintenance Vehicles Based on UWB and Deep Learning

Mingju Chen, Tingting Liu, Jinsong Zhang, Xingzhong Xiong, Feng Liu

To address the issue of the insufficient safety monitoring of power maintenance vehicles during power operations, this study proposes a vehicle monitoring scheme based on ultra wideband (UWB) and deep learning. The UWB localization algorithm employs Chaotic Particle Swarm Optimiz…

View free PDFSource page