1 code implementation • 9 Sep 2023 • Yang Jin, Kun Xu, Liwei Chen, Chao Liao, Jianchao Tan, Quzhe Huang, Bin Chen, Chenyi Lei, An Liu, Chengru Song, Xiaoqiang Lei, Di Zhang, Wenwu Ou, Kun Gai, Yadong Mu
Specifically, we introduce a well-designed visual tokenizer to translate the non-linguistic image into a sequence of discrete tokens like a foreign language that LLM can read.
1 code implementation • 15 Jun 2023 • Fengheng Li, An Liu, Wei Feng, Honghe Zhu, Yaoyu Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junjie Shen, Zhangang Lin, Jingping Shao
To advance research in this field, we have constructed a poster layout dataset named CGL-Dataset V2.
1 code implementation • 24 Nov 2021 • Jiaan Wang, Zhixu Li, Tingyi Zhang, Duo Zheng, Jianfeng Qu, An Liu, Lei Zhao, Zhigang Chen
Additionally, we also introduce a knowledge-enhanced summarizer that utilizes both live commentaries and the knowledge to generate sports news.
1 code implementation • 29 Jan 2022 • Jiaan Wang, Beiqi Zou, Zhixu Li, Jianfeng Qu, Pengpeng Zhao, An Liu, Lei Zhao
Story ending generation is an interesting and challenging task, which aims to generate a coherent and reasonable ending given a story context.
1 code implementation • 17 Jul 2022 • Kexin Wang, Zhixu Li, Jiaan Wang, Jianfeng Qu, Ying He, An Liu, Lei Zhao
Nevertheless, the correlations between knowledge implied in the multi-turn context and the transition regularities between relations in KGs are under-explored.
1 code implementation • CoNLL (EMNLP) 2021 • Shisong Chen, Binbin Gu, Jianfeng Qu, Zhixu Li, An Liu, Lei Zhao, Zhigang Chen
Zero pronoun resolution aims at recognizing dropped pronouns and pointing out their anaphoric mentions, while non-zero coreference resolution targets at clustering mentions referring to the same entity.
1 code implementation • 1 Dec 2022 • Shaohui Zheng, Zhixu Li, Jiaan Wang, Jianfeng Qu, An Liu, Lei Zhao, Zhigang Chen
Cross-Lingual Summarization (CLS) aims at generating summaries in one language for the given documents in another language.
1 code implementation • 26 May 2021 • Chang Tian, An Liu, Guang Huang, Wu Luo
We propose a successive convex approximation based off-policy optimization (SCAOPO) algorithm to solve the general constrained reinforcement learning problem, which is formulated as a constrained Markov decision process (CMDP) in the context of average cost.
1 code implementation • 18 Jul 2023 • Wenkang Xu, An Liu, Bingpeng Zhou, MinJian Zhao
To overcome these drawbacks, we first propose a successive linear approximation VBI (SLA-VBI) algorithm that can provide Bayesian estimation of both sparse signals and dynamic grid parameters.
1 code implementation • 9 Jan 2024 • Jiaan Wang, Jianfeng Qu, Kexin Wang, Zhixu Li, Wen Hua, Ximing Li, An Liu
Knowledge-grounded dialogue (KGD) learns to generate an informative response based on a given dialogue context and external knowledge (\emph{e. g.}, knowledge graphs; KGs).
no code implementations • 1 Jun 2019 • Jisheng Dai, An Liu, Hing Cheung So
By integrating the discretization enforcing prior into the SBL framework and applying the variational Bayesian inference (VBI) methodology, we devise an alternating optimization algorithm to jointly characterize the finite-alphabet feature and reconstruct the unknown signal.
no code implementations • 25 Jan 2018 • An Liu, Vincent Lau, Borna Kananian
The proposed CSSCA algorithm can also handle stochastic non-convex constraints in optimization problems, and it opens the way to solving more challenging optimization problems that occur in many applications.
Information Theory Information Theory
no code implementations • 18 May 2020 • Hualian Sheng, Xihan Chen, Xiongfei Zhai, An Liu, Min-Jian Zhao
This letter investigates the uplink of a multi-user millimeter wave (mmWave) system, where the base station (BS) is equipped with a massive multiple-input multiple-output (MIMO) array and resolution-adaptive analog-to-digital converters (RADCs).
no code implementations • 5 May 2021 • An Liu, Rui Yang, Tony Q. S. Quek, Min-Jian Zhao
Then we propose a PDD-based stochastic successive convex approximation (PDD-SSCA) algorithmic framework to find KKT solutions for two-stage stochastic optimization problems.
no code implementations • 11 Mar 2022 • Yi Wei, Ming-Min Zhao, An Liu, Min-Jian Zhao
Based on the proposed transmission protocol, we propose a two-stage channel tracking and prediction (2SCTP) scheme to obtain the direct and reflected channels with low channel training overhead, which is achieved by exploiting the temporal correlation of the time-varying channels.
no code implementations • 20 Jun 2022 • Yubo Wan, An Liu, Qiyu Hu, Mianyi Zhang, Yunlong Cai
In the coarse stage, we exploit the group sparsity structure of the multiband channel and propose a Turbo Bayesian inference (Turbo-BI) algorithm to achieve a good initial delay estimation based on a coarse signal model, which is transformed from the original multiband signal model by absorbing the carrier frequency terms.
no code implementations • 17 Jul 2022 • Yanzhen Liu, Yunlong Cai, An Liu, MinJian Zhao, Lajos Hanzo
Mobile edge computing (MEC) and millimeter wave (mmWave) communications are capable of significantly reducing the network's delay and enhancing its capacity.
no code implementations • 21 Jul 2022 • Zhixiang Hu, An Liu, Yubo Wan, Tony Xiao Han, MinJian Zhao
Multiband fusion enhances WiFi sensing by jointly utilizing signals from multiple non-contiguous frequency bands.
no code implementations • 21 Jul 2022 • Yubo Wan, An Liu, Rui Du, Tony Xiao Han
Then, a metric called the statistical resolution limit (SRL) that provides a resolution limit is employed to investigate the fundamental limits of delay resolution.
no code implementations • 3 Feb 2023 • Wenkang Xu, Yongbo Xiao, An Liu, MinJian Zhao
A location domain channel modeling method is proposed based on the position of targets and scatterers in the scattering environment, and the resulting radar and communication channels exhibit a partially common sparsity.
no code implementations • 6 Feb 2023 • Wenkang Xu, Yongbo Xiao, An Liu, Ming Lei, MinJian Zhao
A location domain channel modeling method is proposed based on the position of targets and scatterers in the scattering environment, and the resulting radar and communication channels exhibit a two-dimensional (2-D) joint burst sparsity.
no code implementations • 10 Jun 2023 • Kexuan Wang, An Liu, Baishuo Liu
In spite of the biased policy gradient estimation incurred by the single-loop design and observation reuse, we prove that the SLDAC with a feasible initial point can converge to a Karush-Kuhn-Tuker (KKT) point of the original problem almost surely.
no code implementations • 17 Jun 2023 • Jiaan Wang, Jianfeng Qu, Yunlong Liang, Zhixu Li, An Liu, Guanfeng Liu, Xin Zheng
Constructing commonsense knowledge graphs (CKGs) has attracted wide research attention due to its significant importance in cognitive intelligence.
no code implementations • 9 Oct 2023 • Zhixiang Hu, An Liu, MinJian Zhao
Given these challenges, firstly, we propose a parallel stochastic particle variational Bayesian inference (PSPVBI) algorithm.
no code implementations • 13 Oct 2023 • Yubo Wan, An Liu
A novel two-stage two-dimensional (2D) channel extrapolation scheme in both frequency and time domain is proposed, designed to mitigate the negative effects of imperfection factors and ensure high-accuracy channel estimation.
no code implementations • 14 Dec 2023 • Zhaochen Li, Fengheng Li, Wei Feng, Honghe Zhu, An Liu, Yaoyu Li, Zheng Zhang, Jingjing Lv, Xin Zhu, Junjie Shen, Zhangang Lin, Jingping Shao, Zhenglu Yang
At the planning stage, we propose a PlanNet to generate the layout of the product and other visual components considering both the appearance features of the product and semantic features of the text, which improves the diversity and rationality of the layouts.
no code implementations • 12 Feb 2024 • Zonghan Yang, An Liu, Zijun Liu, Kaiming Liu, Fangzhou Xiong, Yile Wang, Zeyuan Yang, Qingyuan Hu, Xinrui Chen, Zhenhe Zhang, Fuwen Luo, Zhicheng Guo, Peng Li, Yang Liu
We also conduct proof-of-concept studies by introducing realistic features to WebShop, including user profiles to demonstrate intentions, personalized reranking for complex environmental dynamics, and runtime cost statistics to reflect self-constraints.
no code implementations • 12 Feb 2024 • Wei Xu, An Liu, Yiting Zhang, Vincent Lau
In this work, we propose a message passing based Bayesian federated learning (BFL) framework to avoid these drawbacks. Specifically, we formulate the problem of deep neural network (DNN) learning and compression and as a sparse Bayesian inference problem, in which group sparse prior is employed to achieve structured model compression.
no code implementations • 20 Feb 2024 • An Liu, Zonghan Yang, Zhenhe Zhang, Qingyuan Hu, Peng Li, Ming Yan, Ji Zhang, Fei Huang, Yang Liu
While Large language models (LLMs) have demonstrated considerable capabilities across various natural language tasks, they often fall short of the performance achieved by domain-specific state-of-the-art models.