collaborators

9 papers

cs.LG2026

CoCurve: Cross-Module Co-Pruning Curvature for Training-Free Structured LLM Pruning

Zhiren Gong, Zihao Zeng, Zijie Wang +3

Structured pruning compresses large language models (LLMs) by removing whole computational units, such as attention heads and feed-forward (FFN) channel groups. Most training-free…

cs.LG2026

Conditional Co-Ablation: Recovering Self-Repair Backups in Transformer Circuits

Zhiren Gong, Zihao Zeng, Chau Yuen +1

Mechanistic interpretability often relies on component-level interventions to discover how a model produces a behavior. This guides attribution, capability knockout, and model prun…

cs.IT2026

Rydberg Atomic Quantum Receivers for Wireless Communications: Two-Color vs. Three-Color Excitation

Jian Xiao, Tierui Gong, Ji Wang +2

An efficient three-color (3C) laser excitation-based Rydberg atomic quantum receiver (RAQR) architecture is investigated for wireless communications, utilizing a five-level (5L) el…

cs.AI2026

XDomainBench: Diagnosing Reasoning Collapse in High-Dimensional Scientific Knowledge Composition

Gong Zhiren, Tiantong Wu, Jiaming Zhang +9

Large Language Models (LLMs) are increasingly deployed for knowledge synthesis, yet their capacity for compositional generalization in scientific knowledge remains under-characteri…

eess.SP2026

Signal-Dependent Shot Noise Modeling of Rydberg Atomic Quantum Receivers: A Design Perspective

Qihao Peng, Qu Luo, Tierui Gong +8

In this paper, we develop a communication-oriented complex baseband equivalent model for superheterodyne Rydberg atomic quantum receivers (RAQRs). The model explicitly captures pho…

cs.IT2026

Wireless large AI model: shaping the AI-empowered future of 6G and beyond

Fenghao Zhu, Xinquan Wang, Siming Jiang +22

The emergence of sixth-generation and beyond communication systems is expected to fundamentally transform digital experiences through introducing unparalleled levels of intelligenc…