5 papers indexed
Chunmei Xu, Siqi Zhang, Zhi Ding, Yi Ma, Rahim Tafazolli
This paper introduces LiTCom, a lightweight transmitter and inference-capable receiver framework, designed to enable robust 6G uplink communication under low signal-to-noise (SNR) conditions. It embraces the resource asymmetry between edge devices and the network infrastructure.…
Yunchao Yao, Zhuxiu Xu, Tianqi Zhang, Zixian Liu, Sikai Li, Zhenyu Wei, et al.
Building general-purpose dexterous manipulation policies requires benchmarks that go beyond isolated tasks to systematically evaluate policies across diverse interaction modes, sensory conditions, and robot embodiments. However, existing benchmarks remain limited in task and data…
Kaiwen Yu, Gang Wu, Xiaodong Xu, Yi Ma, Rahim Tafazolli
A fundamental design question in deep joint source-channel coding (Deep JSCC) remains insufficiently explored: given a channel signal-to-noise ratio (SNR), what effective computation depth is required for semantic reconstruction? Existing Deep JSCC systems typically employ fixed-…
Jing Liang, Hongyao Tang, Yi Ma, Yancheng He, Weixun Wang, Xiaoyang Li, et al.
Reinforcement learning (RL) has gained growing attention in large language model (LLM) post-training, yet RL training remains fragile and can suffer from instability or collapse. One vital cause is training-inference mismatch: LLM adopts separate inference and training engines fo…
Dacheng Qi, Chenyu Wang, Jingwei Xu, Yi Ma, Shenghua Gao
Computer-aided design (CAD) plays a fundamental role in modern manufacturing by providing the high precision required for industrial production. Recent large language model based approaches formulate CAD generation as a sequence prediction problem and have achieved promising resu…