Rui Zhang

Research on attribution and prediction of runoff changes in loess gully areas based on SWAT and machine learning models

Yun Zhao, Enhui Jiang, Bo Qu, Rui Zhang, Chang Liu, Jiaqi Li, et al.

Genomic characterization of carbapenem-resistant Acinetobacter baumannii from a specialized orthopaedic hospital in Southeast China, with phenotypic analysis of biofilm formation

Tengfei Shi, Shaohan Xu, X B Zheng, Weiqiang Shi, Rui Zhang, H Z Chen, et al.

Background Carbapenem−resistant Acinetobacter baumannii (CRAB) is a major threat to hospitalised patients, particularly in intensive care units and orthopaedic wards where implant−associated infections are common. However, the genomic and biofilm characteristics of CRAB in orthop…Read more

AXIS: A Growable Community-Driven Data Engine for Scalable Robot Manipulation

Mengfei Zhao, Dihong Huang, Yikai Tang, Peihao Li, Mingxuan Yan, Ruiqi Zhuang, et al.

Learning effective robot manipulation policies requires diverse, high-quality demonstrations, yet existing data pipelines are often difficult to scale because they rely on specialized hardware, centralized operators, or fixed task suites. We present AXIS, a growable community-dri…Read more

ToolSciVer: Multimodal Scientific Claim Verification with Visual Tool Augmented Reinforcement Learning

Binglin Zhou, Peng Shi, Ryo Kamoi, Nan Zhang, Rui Zhang

Multimodal Scientific Claim Verification (MSCV) requires models to verify scientific claims using visually grounded evidence from papers, including figures, tables, charts, and textual context. However, existing methods often fail because they struggle to locate decisive visual e…Read more

Are LLM-Generated GPU Kernels Production-Ready? A Trace-Driven Benchmark and Optimization Agent

Lingyun Yang, Yuxiao Wang, Shenghao Liang, Linfeng Yang, Daocheng Ying, Chunbo You, et al.

Existing GPU kernel generation benchmarks draw problems from synthetic or curated sources that diverge from deployed workloads. We present Atrex-Bench, a benchmark whose 30 operators and 440 shapes are sampled directly from full-cluster production inference traces of compute-limi…Read more

Disentangling Knowledge States with Ability and Proficiency Modeling for Knowledge Tracing

Duantengchuan Li, Yingqian Bi, Jinsong Chen, Rui Zhang, Mingwen Tong

Knowledge tracing (KT) aims to predict students' future performance by modeling their evolving knowledge states from historical interactions. Existing KT methods usually treat the raw interaction sequence as a unified behavioral process, overlooking the phase-specific nature of l…Read more

VINE: Taming Generative Control Policies for Reinforcement Learning

Rushuai Yang, Zhuo Han, Houlin Li, Hecheng Wang, Zhichao Wu, Rui Zhang, et al.

Flow-matching policies have emerged as an effective policy parameterization for robot learning. They iteratively generate actions from noise, enabling highly expressive modeling of complex and multimodal action distributions. However, prior works observed that scaling these polic…Read more

Rotating ULA-Enabled Computed Tomography for Efficient 3D Spatial Power Spectrum Synthesis: Architecture and Principled Orientation Design

Haocheng Hua, Weidong Mei, Jie Xu, Rui Zhang

This paper proposes an efficient three-dimensional (3D) spatial power spectrum synthesis method by rotating a uniform linear array (ULA) about its center in 3D space. Inspired by classical computed tomography (CT), the ULA performs analog receive combining at each rotation angle…Read more

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…Read more

Bending Beam for THz Wireless Networks: Fundamental, Design Issue, and Prototype

Aoran Liu, Xin Tong Hu, Weidong Mei, Ya Fei Wu, Ke Liu, Boyu Ning, et al.

Bending beams, characterized by their non diffracting and self-healing properties in the near field, offer a new approach to bypass blockage in terahertz (THz) wireless communication and sensing. However, the investigations of bend ing beams in the context of wireless communicati…Read more

Toward Efficient Sensing in Multi-Device ISCC by Removing Frequency Domain Redundancy

Ziqi Ye, Yinghui He, Weiwei Chen, Guanding Yu, Rui Zhang

Integrated sensing, communication, and computation (ISCC) is envisioned as a key enabler for intelligent services in future wireless networks. However, in multi-device ISCC systems, directly offloading full orthogonal frequency division multiplexing (OFDM) sensing data to the edg…Read more