activity
20122026
most citedActivity Detection for Massive Connectivity in Cell-free Networks with Unknown Large-scale Fading, Channel Statistics, Noise Variance, and Activity Probability: A Bayesian Approach

25 citations · 102 across the 54 of their papers we have counts for

collaborators

66 papers

eess.SP2026

CrossRAFT: Cross-Domain Complex-Valued Feature Extraction for Ultrasound Motion Estimation

Yang Leng, Yuchen Tang, Kai-Hang Yiu +2

Accurate multi-dimensional motion estimation is fundamental to broad biomedical ultrasound applications, primarily performed using real-valued radio-frequency (RF), analytic, and i…

cs.RO2026

Memory-Native Non-Terrestrial Networks for Embodied Intelligence

Chengyang Li, Yikun Wang, Jiahui He +6

Non-terrestrial networks (NTN) provide ubiquitous connectivity for embodied intelligence (EI), enabling robots in the wilderness to leverage cloud resources or report critical info…

cs.LG2026

FluxBin: Flexible LUT-based Ultra-low-bit LLM Inference by Algorithm-Kernel Synergy

Qingyao Yang, Runming Yang, He Xiao +7

While binary quantization theoretically promises extreme compression and acceleration for Large Language Models (LLMs), existing research often overlooks the necessity of specializ…

cs.LG2026

Dualformer: Efficient Feature Extractor for Complex-valued Blind Communication Signal Analysis

Yurui Zhao, Xiang Wang, Jingreng Lei +3

Designing effective feature extractors is critical for blind signal analysis tasks such as automatic modulation recognition (AMR), signal scheme recognition (SSR), and \color{black…

cs.LG2026

OScaR: The Occam's Razor for Extreme KV Cache Quantization in LLMs and Beyond

Zunhai Su, Rui Yang, Chao Zhang +11

The rapid advancement toward long-context reasoning and multi-modal intelligence has made the memory footprint of the Key-Value (KV) cache a dominant memory bottleneck for efficien…

cs.RO2026

Memory Centric Power Allocation for Multi-Agent Embodied Question Answering

Chengyang Li, Shuai Wang, Kejiang Ye +5

This paper considers multi-agent embodied question answering (MA-EQA), which enables robot teams to answer queries based on their long-horizon observations. In contrast to existing…