no code implementations • 19 Mar 2024 • Haochen Wu, Liyang Lu, Zhaocheng Wang
Specifically, we formulate the dual-band near-field communication model based on the fact that high-frequency systems are likely to be deployed with lower-frequency systems.
no code implementations • 19 Mar 2024 • Liyang Lu, Ke Ma, Zhaocheng Wang
Near-field (NF) communications draw much attention in the context of extremely large-scale antenna arrays (ELAA).
no code implementations • 4 Feb 2024 • Liyang Lu, Zhaocheng Wang, Zhen Gao, Sheng Chen, H. Vincent Poor
This work explores the fundamental problem of the recoverability of a sparse tensor being reconstructed from its compressed embodiment.
no code implementations • 24 Sep 2023 • An Chen, Wenbo Xu, Liyang Lu, Yue Wang
Massive multiple-input multiple-output (MIMO) enjoys great advantage in 5G wireless communication systems owing to its spectrum and energy efficiency.
no code implementations • 7 Apr 2023 • Liyang Lu, Zhaocheng Wang, Sheng Chen
We consider the greedy algorithms for the joint recovery of high-dimensional sparse signals based on the block multiple measurement vector (BMMV) model in compressed sensing (CS).
no code implementations • 14 Nov 2022 • Liyang Lu, Wenbo Xu, Yue Wang, Zhi Tian
In this paper, we propose a blind-block orthogonal least squares-based compressive spectrum sensing (B-BOLS-CSS) algorithm, which utilizes a novel blind stopping rule to cut the cords to these prior information.
no code implementations • 14 Nov 2022 • Liyang Lu, Wenbo Xu, Yue Wang, Zhi Tian
To this end, the minimum number of required measurements for successful recovery is first derived in terms of its probabilistic lower bound.
no code implementations • 31 Oct 2022 • An Chen, Wenbo Xu, Liyang Lu, Yue Wang
In frequency division duplex (FDD) massive MIMO systems, reliable downlink channel estimation is essential for the subsequent data transmission but is realized at the cost of massive pilot overhead due to hundreds of antennas at base station (BS).
1 code implementation • 21 Aug 2022 • Pengcheng He, Baolin Peng, Liyang Lu, Song Wang, Jie Mei, Yang Liu, Ruochen Xu, Hany Hassan Awadalla, Yu Shi, Chenguang Zhu, Wayne Xiong, Michael Zeng, Jianfeng Gao, Xuedong Huang
Z-Code++ creates new state of the art on 9 out of 13 text summarization tasks across 5 languages.
no code implementations • 3 May 2022 • ZiYi Yang, Yuwei Fang, Chenguang Zhu, Reid Pryzant, Dongdong Chen, Yu Shi, Yichong Xu, Yao Qian, Mei Gao, Yi-Ling Chen, Liyang Lu, Yujia Xie, Robert Gmyr, Noel Codella, Naoyuki Kanda, Bin Xiao, Lu Yuan, Takuya Yoshioka, Michael Zeng, Xuedong Huang
Human intelligence is multimodal; we integrate visual, linguistic, and acoustic signals to maintain a holistic worldview.
no code implementations • 11 Apr 2022 • Liyang Lu, Wenbo Xu, Yue Wang, Zhi Tian
As an enabling technique of cognitive radio (CR), compressive spectrum sensing (CSS) based on compressive sensing (CS) can detect the spectrum opportunities from wide frequency bands efficiently and accurately by using sub-Nyquist sampling rate.
1 code implementation • 22 Sep 2021 • Young Jin Kim, Ammar Ahmad Awan, Alexandre Muzio, Andres Felipe Cruz Salinas, Liyang Lu, Amr Hendy, Samyam Rajbhandari, Yuxiong He, Hany Hassan Awadalla
By combining the efficient system and training methods, we are able to significantly scale up large multitask multilingual models for language generation which results in a great improvement in model accuracy.
no code implementations • 22 Feb 2021 • Junwei Liao, Yu Shi, Ming Gong, Linjun Shou, Sefik Eskimez, Liyang Lu, Hong Qu, Michael Zeng
Many downstream tasks and human readers rely on the output of the ASR system; therefore, errors introduced by the speaker and ASR system alike will be propagated to the next task in the pipeline.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 9 Apr 2020 • Junwei Liao, Sefik Emre Eskimez, Liyang Lu, Yu Shi, Ming Gong, Linjun Shou, Hong Qu, Michael Zeng
In this work, we propose a novel NLP task called ASR post-processing for readability (APR) that aims to transform the noisy ASR output into a readable text for humans and downstream tasks while maintaining the semantic meaning of the speaker.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • ICCV 2015 • Lingfei Meng, Liyang Lu, Noah Bedard, Kathrin Berkner
Unlike a conventional plenoptic camera, our system captures the BRDF variation of the object surface in a single image in addition to the light field information from the scene, which allows us to recover very fine 3D structures of the surface.