1 code implementation • 26 Jun 2025 • Xinping Zhao, Xinshuo Hu, Zifei Shan, Shouzheng Huang, Yao Zhou, Zetian Sun, Zhenyu Liu, Dongfang Li, Xinyuan Wei, Qian Chen, Youcheng Pan, Yang Xiang, Meishan Zhang, Haofen Wang, Jun Yu, Baotian Hu, Min Zhang
In this paper, we propose KaLM-Embedding-V2, a versatile and compact embedding model, which achieves impressive performance in general-purpose text embedding tasks by leveraging superior training techniques and data.
no code implementations • 8 Jun 2025 • Zhenyu Liu, HuiZhi Liang, Rajiv Ranjan, Zhanxing Zhu, Vaclav Snasel, Varun Ojha
The adversarial distribution and clean distribution optimizations enhance the target model's robustness by leveraging the strengths of different loss functions obtained via a suitable function space exploration to focus more precisely on the target model's distribution.
1 code implementation • 25 May 2025 • Yunxin Li, Xinyu Chen, Zitao Li, Zhenyu Liu, Longyue Wang, Wenhan Luo, Baotian Hu, Min Zhang
Applying Reinforcement Learning (RL) to Video Large Language Models (Video-LLMs) shows significant promise for complex video reasoning.
no code implementations • 23 May 2025 • Anjie Le, Henan Liu, Yue Wang, Zhenyu Liu, Rongkun Zhu, Taohan Weng, Jinze Yu, Boyang Wang, Yalun Wu, Kaiwen Yan, Quanlin Sun, Meirui Jiang, Jialun Pei, Siya Liu, Haoyun Zheng, Zhoujun Li, Alison Noble, Jacques Souquet, Xiaoqing Guo, Manxi Lin, Hongcheng Guo
Ultrasound is a widely-used imaging modality critical to global healthcare, yet its interpretation remains challenging due to its varying image quality on operators, noises, and anatomical structures.
no code implementations • 9 May 2025 • Zehao Fan, Garrett Gagnon, Zhenyu Liu, Liu Liu
Transformer-based models are the foundation of modern machine learning, but their execution, particularly during autoregressive decoding in large language models (LLMs), places significant pressure on memory systems due to frequent memory accesses and growing key-value (KV) caches.
1 code implementation • 8 May 2025 • Yunxin Li, Zhenyu Liu, Zitao Li, Xuanyu Zhang, Zhenran Xu, Xinyu Chen, Haoyuan Shi, Shenyuan Jiang, Xintong Wang, Jifang Wang, Shouzheng Huang, Xinping Zhao, Borui Jiang, Lanqing Hong, Longyue Wang, Zhuotao Tian, Baoxing Huai, Wenhan Luo, Weihua Luo, Zheng Zhang, Baotian Hu, Min Zhang
Large Multimodal Reasoning Models (LMRMs) have emerged as a promising paradigm, integrating modalities such as text, images, audio, and video to support complex reasoning capabilities and aiming to achieve comprehensive perception, precise understanding, and deep reasoning.
1 code implementation • 13 Mar 2025 • Zhenyu Liu, Dongfang Li, Xinshuo Hu, Xinping Zhao, Yibin Chen, Baotian Hu, Min Zhang
We find that the transformer embeds the task function learned from demonstrations into the separator token representation, which plays an important role in the generation of prior response tokens.
1 code implementation • CVPR 2025 • Wang YuHang, Junkang Guo, Aolei Liu, Kaihao Wang, Zaitong Wu, Zhenyu Liu, Wenfei Yin, Jian Liu
This paper provides a comprehensive analysis of adversarial training under long-tailed distributions and identifies limitations in the current state-of-the-art method, AT-BSL, in achieving robust performance under such conditions.
1 code implementation • 27 Feb 2025 • Zhenyu Liu, Yunxin Li, Baotian Hu, Wenhan Luo, YaoWei Wang, Min Zhang
Specifically, our approach consists of 1) an image information quantification method via visual agents collaboration to select images with rich visual information, and 2) a visual-centric instruction quality assessment method to select high-quality instruction data related to high-quality images.
no code implementations • 22 Feb 2025 • Yi Ma, Chunmei Xu, Zhenyu Liu, Siqi Zhang, Rahim Tafazolli
This paper explores the concept of information importance in multi-modal task-oriented semantic communication systems, emphasizing the need for high accuracy and efficiency to fulfill task-specific objectives.
no code implementations • 10 Feb 2025 • Zongyao Zhao, Zhenyu Liu, Wei Dai, Xinke Tang, Xiao-Ping Zhang, Yuhan Dong
The uncertainty of the sensing target brings great challenge to the beamforming design of the integrated sensing and communication (ISAC) system.
no code implementations • 27 Jan 2025 • Yipeng Li, Xinchen Lyu, Zhenyu Liu
Using the general assumption, we develop a unified framework for permutation-based SGD with arbitrary permutations of examples, incorporating all the aforementioned representative algorithms.
no code implementations • 20 Jan 2025 • Zhuangzhuang Yan, Xinyu Gu, Zhenyu Liu, Liyang Lu
To address this demand, 5G-Advanced has introduced sidelink communication over the unlicensed spectrum (SL-U) to increase data rates.
no code implementations • 20 Jan 2025 • Zhuangzhuang Yan, Xinyu Gu, Shilong Fan, Zhenyu Liu
In this paper, we propose GAT-LLM, a novel multivariate wireless link quality prediction model that combines Large Language Models (LLMs) with Graph Attention Networks (GAT) to enable accurate and reliable multivariate LQP of wireless communications.
1 code implementation • 2 Jan 2025 • Xinshuo Hu, Zifei Shan, Xinping Zhao, Zetian Sun, Zhenyu Liu, Dongfang Li, Shaolin Ye, Xinyuan Wei, Qian Chen, Baotian Hu, Haofen Wang, Jun Yu, Min Zhang
As retrieval-augmented generation prevails in large language models, embedding models are becoming increasingly crucial.
no code implementations • 20 Nov 2024 • Zhilin Du, Zhenyu Liu, Haozhen Li, Shilong Fan, Xinyu Gu, Lin Zhang
The application of deep learning (DL)-based channel state information (CSI) feedback frameworks in massive multiple-input multiple-output (MIMO) systems has significantly improved reconstruction accuracy.
no code implementations • 1 Nov 2024 • Zongyao Zhao, Zhenyu Liu, Rui Jiang, Zhongyi Li, Xiao-Ping Zhang, Xinke Tang, Yuhan Dong
Sensing and communication suffer from a performance trade-off in ISAC systems.
no code implementations • 21 Oct 2024 • Jianfei He, Lilin Wang, Jiaying Wang, Zhenyu Liu, Hongbin Na, Zimu Wang, Wei Wang, Qi Chen
Identifying offensive language is essential for maintaining safety and sustainability in the social media era.
no code implementations • 14 Oct 2024 • Xinping Zhao, Jindi Yu, Zhenyu Liu, Jifang Wang, Dongfang Li, Yibin Chen, Baotian Hu, Min Zhang
Therefore, it is necessary to resort to external knowledge to detect and correct the hallucinated content.
no code implementations • 14 Oct 2024 • Xinping Zhao, Yan Zhong, Zetian Sun, Xinshuo Hu, Zhenyu Liu, Dongfang Li, Baotian Hu, Min Zhang
In this work, we propose a progressive retrieval paradigm with coarse-to-fine granularity for RAG, termed FunnelRAG, so as to balance effectiveness and efficiency.
no code implementations • 4 Sep 2024 • Zongyao Zhao, Tiankuo Wei, Zhenyu Liu, Xinke Tang, Xiao-Ping Zhang, Yuhan Dong
Integrated sensing and communication (ISAC) is a key technology of next generation wireless communication.
no code implementations • 26 Aug 2024 • Kailin Tan, Jincheng Dai, Zhenyu Liu, Sixian Wang, Xiaoqi Qin, Wenjun Xu, Kai Niu, Ping Zhang
Based on this framework, we introduce a distortion-perception controllable transmission (DPCT) model, which addresses the variation in the perception-distortion trade-off.
no code implementations • 23 Aug 2024 • Zhenyu Liu, Haoran Duan, HuiZhi Liang, Yang Long, Vaclav Snasel, Guiseppe Nicosia, Rajiv Ranjan, Varun Ojha
Additionally, we found that a budgeted dimension of inner optimization for the target model may contribute to the trade-off between clean accuracy and robust accuracy.
no code implementations • 15 Aug 2024 • Shilong Fan, Zhenyu Liu, Xinyu Gu, Haozhen Li
In this work, we introduce Csi-LLM, a novel LLM-powered downlink channel prediction technique that models variable-step historical sequences.
no code implementations • 27 Jul 2024 • Zongyao Zhao, Yuhan Dong, Tiankuo Wei, Xinke Tang, Xiao-Ping Zhang, Zhenyu Liu
In this paper, we propose a novel cognitive wireless system called backscatter-ISAC (B-ISAC) and develop a joint beamforming framework for different stages (task modes).
1 code implementation • 17 Apr 2024 • Dongfang Li, Zhenyu Liu, Xinshuo Hu, Zetian Sun, Baotian Hu, Min Zhang
In this paper, we address this gap by presenting a comprehensive analysis of these compressed vectors, drawing parallels to the parameters trained with gradient descent, and introduce the concept of state vector.
no code implementations • Robotics and Computer-Integrated Manufacturing 2024 • Yu Huang, Daxin Liu *, Zhenyu Liu, Ke Wang, Qide Wang, Jianrong Tan
In real- world experiments on grasping objects in different shapes and trajectories, the average grasping prediction success rate (GPSR) and grasping reaching success rate (GRSR) of MA-TD3H are above 90 percent and 80 percent respectively, and the average GRSR is improved by 20–30 percent compared with the other algorithms.
no code implementations • 27 Mar 2024 • Dongfang Li, Zetian Sun, Baotian Hu, Zhenyu Liu, Xinshuo Hu, Xuebo Liu, Min Zhang
Large language models have been widely adopted in natural language processing, yet they face the challenge of generating unreliable content.
no code implementations • 13 Mar 2024 • Shuangjian Li, Tao Zhu, Mingxing Nie, Huansheng Ning, Zhenyu Liu, Liming Chen
Traditional deep learning methods struggle to simultaneously segment, recognize, and forecast human activities from sensor data.
no code implementations • 6 Feb 2024 • Zhenyu Liu, Garrett Gagnon, Swagath Venkataramani, Liu Liu
Deep Neural Networks (DNNs) have revolutionized a wide range of industries, from healthcare and finance to automotive, by offering unparalleled capabilities in data analysis and decision-making.
1 code implementation • 11 Dec 2023 • Bao Li, Zhenyu Liu, Lizhi Shao, Bensheng Qiu, Hong Bu, Jie Tian
Furthermore, we demonstrate that our model can generalize to two unseen sites with 229 WSIs.
no code implementations • 10 Dec 2023 • Zhilin Du, Haozhen Li, Zhenyu Liu, Shilong Fan, Xinyu Gu, Lin Zhang
The advent of deep learning (DL)-based models has significantly advanced Channel State Information (CSI) feedback mechanisms in wireless communication systems.
1 code implementation • 7 Nov 2023 • Dongfang Li, Zetian Sun, Xinshuo Hu, Zhenyu Liu, Ziyang Chen, Baotian Hu, Aiguo Wu, Min Zhang
Open-domain generative systems have gained significant attention in the field of conversational AI (e. g., generative search engines).
no code implementations • 15 Oct 2023 • Huilin Zhou, Huijie Tang, Mingjie Li, Hao Zhang, Zhenyu Liu, Quanshi Zhang
The AI model has surpassed human players in the game of Go, and it is widely believed that the AI model has encoded new knowledge about the Go game beyond human players.
1 code implementation • 16 Aug 2023 • Xinshuo Hu, Dongfang Li, Baotian Hu, Zihao Zheng, Zhenyu Liu, Min Zhang
To evaluate the effectiveness of our approach in terms of truthfulness and detoxification, we conduct extensive experiments on LLMs, encompassing additional abilities such as language modeling and mathematical reasoning.
no code implementations • 30 Mar 2023 • Haozhen Li, Xinyu Gu, Boyuan Zhang, Dongliang Li, Zhenyu Liu, Lin Zhang
Deep Learning (DL)-based channel state information (CSI) feedback is a promising technique for the transmitter to accurately acquire the CSI of massive multiple-input multiple-output (MIMO) systems.
no code implementations • 5 Aug 2022 • Ruining Tang, Zhenyu Liu, Yangguang Li, Yiguo Song, Hui Liu, Qide Wang, Jing Shao, Guifang Duan, Jianrong Tan
To alleviate this problem, a novel Task-decoupled Feature Distillation (TFD) is proposed by flexibly balancing the contributions of classification and regression tasks.
no code implementations • 10 Nov 2021 • Yunkun Xu, Zhenyu Liu, Guifang Duan, Jiangcheng Zhu, Xiaolong Bai, Jianrong Tan
Safety has become one of the main challenges of applying deep reinforcement learning to real world systems.
no code implementations • 21 Dec 2020 • Zhenyu Liu, Jian Cheng
Time series classification problems exist in many fields and have been explored for a couple of decades.
no code implementations • 20 Sep 2020 • Zhenyu Liu, Mason del Rosario, Zhi Ding
Forward channel state information (CSI) often plays a vital role in scheduling and capacity-approaching transmission optimization for massive multiple-input multiple-output (MIMO) communication systems.
no code implementations • 12 Aug 2020 • Zhenyu Liu, Chaohong Lu, Haiwei Huang, Shengfei Lyu, Zhenchao Tao
Conventionally, there are two mainstream neural architectures for NLP tasks: the recurrent neural network (RNN) and the convolution neural network (ConvNet).
no code implementations • 29 Jun 2020 • Zhenyu Liu, Haiwei Huang, Chaohong Lu, Shengfei Lyu
Alternatively, CNN is able to capture n-gram features of texts by utilizing convolutional filters.
no code implementations • 29 Jun 2020 • Zhenyu Liu, Yaqiang Yao, Yan Liu, Yuening Zhu, Zhenchao Tao, Lei Wang, Yuhong Feng
In the proposed method, an activity is divided into several successive actions represented by spatio temporal patterns, and the evolution of these actions are captured by a sequential model.
no code implementations • 22 Feb 2020 • Zhenyu Liu, Dongyu Wang, Lan Zhang, Bin Hu
Depression is a common mental disorder worldwide which causes a range of serious outcomes.
no code implementations • 20 Feb 2020 • Hanshu Cai, Yiwen Gao, Shuting Sun, Na Li, Fuze Tian, Han Xiao, Jianxiu Li, Zhengwu Yang, Xiaowei Li, Qinglin Zhao, Zhenyu Liu, Zhijun Yao, Minqiang Yang, Hong Peng, Jing Zhu, Xiaowei Zhang, Guoping Gao, Fang Zheng, Rui Li, Zhihua Guo, Rong Ma, Jing Yang, Lan Zhang, Xiping Hu, Yumin Li, Bin Hu
The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications.
no code implementations • 22 Sep 2017 • Zhourui Song, Zhenyu Liu, Dongsheng Wang
The heavy burdens of computation and off-chip traffic impede deploying the large scale convolution neural network on embedded platforms.