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Spatial-Temporal Resource Utilization for Partially Connected Multi-AUV Broadcast Scheduling

IEEE Wireless Communications Letters 2025年第5期14卷 1321-1325页

作者： He, Hongyi Du, Jun Jiang, Chunxiao Wang, Jintao Song, Jian Niyato, Dusit Tsinghua University Beijing National Research Center for Information Science and Technology and State Key laboratory of Space Network and Communications Department of Electronic Engineering Beijing100084 China Tsinghua University Department of Electronic Engineering and State Key laboratory of Space Network and Communications Beijing100084 China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing100084 China Tsinghua University Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Beijing100084 China Tsinghua University Shenzhen International Graduate School Shenzhen518055 China Nanyang Technological University College of Computing and Data Science Singapore

The long propagation delays in underwater acoustic channels can be leveraged to improve communication efficiency using spatial-temporal reuse techniques. This work focuses on a system of partially connected AUVs that continuously broadcast packets. A central controller gathers the location information of the AUVs and designs a broadcast sequence exploiting propagation delays to minimize the broadcast cycle. Since finding optimal solutions is time-consuming, we propose a scheduling algorithm that uses heuristics based on partial connections to reduce computational complexity. Additionally, we allow collision tolerance to shorten the broadcast cycle further and investigate the trade-off of the shorter broadcast cycle and collision probability, resulting in a scheduling algorithm exhibiting receiving-alignment properties. Simulations demonstrate the effectiveness of the proposed algorithm in reducing broadcast cycles while maintaining low computational complexity. © 2012 IEEE.

关键词： Scheduling algorithms

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Generative Retrieval for Book Search

arXiv

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arXiv 2025年

作者： Tang, Yubao Zhang, Ruqing Guo, Jiafeng de Rijke, Maarten Liu, Shihao Wang, Shuaiqiang Yin, Dawei Cheng, Xueqi CAS Key Lab of Network Data Science and Technology ICT CAS University of Chinese Academy of Sciences University of Amsterdam Amsterdam Netherlands University of Amsterdam Amsterdam Netherlands CAS Key Lab of Network Data Science and Technology ICT CAS University of Chinese Academy of Sciences Beijing China Baidu Inc Beijing China

In book search, relevant book information should be returned in response to a query. Books contain complex, multi-faceted information such as metadata, outlines, and main text, where the outline provides hierarchical information between chapters and sections. Generative retrieval (GR) is a new retrieval paradigm that consolidates corpus information into a single model to generate identifiers of documents that are relevant to a given query. How can GR be applied to book search? Directly applying GR to book search is a challenge due to the unique characteristics of book search: (i) The model needs to retain the complex, multi-faceted information of the book, which increases the demand for labeled data. (ii) Splitting book information and treating it as a collection of separate segments for learning might result in a loss of hierarchical information. We propose an effective Generative retrieval framework for Book Search (GBS) that features two main components: (i) data augmentation and (ii) outline-oriented book encoding. For data augmentation, GBS constructs multiple query-book pairs for training;it constructs multiple book identifiers based on the outline, various forms of book contents, and simulates real book retrieval scenarios with varied pseudo-queries. This includes coverage-promoting book identifier augmentation, allowing the model to learn to index effectively, and diversity-enhanced query augmentation, allowing the model to learn to retrieve effectively. Outline-oriented book encoding improves length extrapolation through bi-level positional encoding and retentive attention mechanisms to maintain context over long sequences. Experiments on a proprietary Baidu dataset demonstrate that GBS outperforms strong baselines, achieving a 9.8% improvement in terms of MRR@20, over the state-of-the-art RIPOR method. Experiments on public datasets confirm the robustness and generalizability of GBS, highlighting its potential to enhance book retrieval. © 2025, CC BY.

关键词： Encoding (symbols)

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Unbiased Learning to Rank with Query-Level Click Propensity Estimation: Beyond Pointwise Observation and Relevance

arXiv

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arXiv 2025年

作者： Yu, Lulu Bi, Keping Guo, Jiafeng Liu, Shihao Yin, Dawei Cheng, Xueqi CAS Key Lab of Network Data Science and Technology ICT CAS University of Chinese Academy of Sciences Beijing China Baidu Inc Beijing China

Most existing unbiased learning-to-rank (ULTR) approaches are based on the user examination hypothesis, which assumes that users will click a result only if it is both relevant and observed (typically modeled by position). However, in real-world scenarios, users often click only one or two results after examining multiple relevant options, due to limited patience or because their information needs have already been satisfied. Motivated by this, we propose a query-level click propensity model to capture the probability that users will click on different result lists, allowing for nonzero probabilities that users may not click on an observed relevant result. We hypothesize that this propensity increases when more potentially relevant results are present, and refer to this user behavior as relevance saturation bias. Our method introduces a Dual Inverse Propensity Weighting (DualIPW) mechanism—combining query-level and position-level IPW—to address both relevance saturation and position bias. Through theoretical derivation, we prove that DualIPW can learn an unbiased ranking model. Experiments on the real-world Baidu-ULTR dataset demonstrate that our approach significantly outperforms state-of-the-art ULTR baselines. The code and dataset information can be found at https://***/Trustworthy-Information-Access/DualIPW. © 2025, CC BY.

关键词： Contrastive Learning

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CPSNet: Comprehensive Enhancement Representation for Polyp Segmentation Task

CPSNet: Comprehensive Enhancement Representation for Polyp S...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, IcasSP 2025

作者： Cai, Jiati Liu, Xiaogang Yang, Hongjie Ding, Yi Zhong, Ting Qin, Zhen Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Chengdu China Department of Gastroenterology and Hepatology University of Electronic Science and Technology of China Chengdu China School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350368741

Accurately segmenting polyp regions in colonoscopy images is crucial for the diagnosis and intervention of colorectal cancer. However, the task of polyp segmentation remains challenging due to the diverse size and shape variations among polyps, their extreme similarity to the background, and frequent rotation of the lens, which further increases the diversity in polyp presentation. To address these challenges effectively, we propose a comprehensive polyp segmentation network (CPSNet). Specifically, we introduce a Comprehensive Spatial Feature Extraction Module (CFEM) that progressively and densely integrates features while forming receptive windows with various shapes. This enables enhanced perception of polyps at manifold sizes and shapes. Additionally, we propose a Fine-grained Region Strengthen Module (FGSM) to supplement uncertain areas around polyps by mitigating background noise interference. In terms of training strategy, we further introduce a Rotation-augmented Constrained Loss (RC Loss), which reinforces consistency constraints on polyp images under multiple rotation angles. Qualitative and quantitative experiments conducted on five public datasets demonstrate both the plug-and-play capability of CFEM as well as the effectiveness and excellence achieved by CPSNet. © 2025 IEEE.

关键词： colonoscopy computer vision polyp segmentation representation enhancement

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Generative Retrieval for Book Search 25

Generative Retrieval for Book Search

引用

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and data Mining V.1

作者： Yubao Tang Ruqing Zhang Jiafeng Guo Maarten de Rijke Shihao Liu Shuaiqiang Wang Dawei Yin Xueqi Cheng CAS Key Lab of Network Data Science and Technology ICT CAS Beijing China University of the Chinese Academy of Sciences Beijing China & University of Amsterdam Amsterdam Netherlands CAS Key Lab of Network Data Science and Technology ICT CAS Beijing China & University of Chinese Academy of Sciences Beijing China University of Amsterdam Amsterdam Netherlands Baidu Inc. Beijing China

ISBN: (纸本)9798400712456

In book search, relevant book information should be returned in response to a query. Books contain complex, multi-faceted information such as metadata, outlines, and main text, where the outline provides hierarchical information between chapters and sections. Generative retrieval (GR) is a new retrieval paradigm that consolidates corpus information into a single model to generate identifiers of documents that are relevant to a given query. How can GR be applied to book search? Directly applying GR to book search is a challenge due to the unique characteristics of book search: The model needs to retain the complex, multi-faceted information of the book, which increases the demand for labeled data. Splitting book information and treating it as a collection of separate segments for learning might result in a loss of hierarchical *** propose an effective Generative retrieval framework for Book Search (GBS) that features two main components: data augmentation and outline-oriented book encoding. For data augmentation, GBS constructs multiple query-book pairs for training; it constructs multiple book identifiers based on the outline, various forms of book contents, and simulates real book retrieval scenarios with varied pseudo-queries. This includes coverage-promoting book identifier augmentation, allowing the model to learn to index effectively, and diversity-enhanced query augmentation, allowing the model to learn to retrieve effectively. Outline-oriented book encoding improves length extrapolation through bi-level positional encoding and retentive attention mechanisms to maintain context over long sequences. Experiments on a proprietary Baidu dataset demonstrate that GBS outperforms strong baselines, achieving a 9.8% improvement in terms of MRR@20, over the state-of-the-art RIPOR method. Experiments on public datasets confirm the robustness and generalizability of GBS, highlighting its potential to enhance book retrieval.

关键词： book retrieval

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Get the Punchline: Headline-Centric Multi-View Learning for Personalized Headline Generation

IEEE Transactions on Audio, Speech and Language Processing

引用

IEEE Transactions on Audio, Speech and Language Processing 2025年 33卷 962-973页

作者： Wenya Guo Shenglong Yu Ying Zhang Zhengkun Zhang Xiaojie Yuan College of Computer Science Nankai University Tianjin China Tianjin Key Laboratory of Network and Data Security Technology College of Cyber Science Nankai University Tianjin China

Personalized news headline generation aims to generate a user-specific headline based on their reading histories. Existing approaches incorporate information from various aspects of news articles, which leads to a lack of focus on news headlines and fails to capture accurate information for guiding headline generation. As a result, the generated headlines lack differences across users and fail to reflect user-specific information. To address this problem, we propose a Headline-centric Multi- view Headline Generation network, denoted as HMvNet. HMvNet is an extraction-integration method that centers around the punchline, i.e. the user-specific information contained in history headlines. HMvNet extracts user-preferred entity tokens and syntactic structures from history headlines through the token-level view and the sequence-level view, respectively. Besides, we propose a reinforcement learning method specifically designed for personalized headline generation to train HMvNet. This method allows the model to fully leverage extracted information and ensures the fluency of the generated headlines. Experimental results demonstrate the superiority of the proposed personalization modeling method as well as the reinforcement learning framework.

关键词： History data mining Syntactics Reinforcement learning Recommender systems Generators Training User preference Speech processing Hybrid power systems

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Multi-scale Graph Convolution with Corrective Contrastive Learning for Skeleton-based Action Recognition

Multi-scale Graph Convolution with Corrective Contrastive Le...

引用

International Conference on Acoustics, Speech, and Signal Processing (IcasSP)

作者： Tianming Zhuang Erqiang Zhou Hanwen Zhang Yi Ding Ji Geng Zhen Qin Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

For pursuing accurate skeleton-based action recognition, many existing graph-based approaches deploy the higher-order polynomials of the skeletal adjacency matrix to model the node correlations of distant neighbours. To further capture robust graphical patterns, a novel multi-scale graph convolution operator is proposed, which enables to aggregate multi-scale dependencies and capture long-range joint relationships on human skeleton graph. Additionally, a novel corrective contrastive learning strategy is proposed, which aims to distinguish the representative clues and calibrate the confused action clips in the feature space. Comprehensive experiments validate the effectiveness and superiority of our proposed method over state-of-the-art approaches on three large-scale datasets: NTU RGB+D 60, NTU RGB+D 120, and Kinetics Skeleton 400.

关键词： Correlation Convolution Contrastive learning Speech recognition Benchmark testing Skeleton Polynomials Kinetic theory Speech processing Kernel

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An integrated laser system for manipulating trapped ions qubits

引用

Optics and Laser technology 2025年 186卷

作者： Ye, Wei-Ran Cui, Jin-Ming Chen, Yan Chen, Yi-Long Li, Rui-Rui Huang, Yun-Feng Li, Chuan-Feng Guo, Guang-Can CAS Key Laboratory of Quantum Information University of Science and Technology of China Hefei230026 China Anhui Province Key Laboratory of Quantum Network University of Science and Technology of China Hefei230026 China CAS Center For Excellence in Quantum Information and Quantum Physics University of Science and Technology of China Hefei230026 China Hefei National Laboratory University of Science and Technology of China Hefei230088 China

In experiments with atomic qubits encoded in the hyperfine levels of cold atoms or ions, the generation and control of multiple laser frequencies are often required for laser cooling and qubit manipulation. In this work, we demonstrate a laser system that integrates laser cooling, qubit initialization and detection, and Raman operations into a single setup, utilizing fiber laser technology and nonlinear optics. Specifically, a 369 nm laser for preparing and detecting 171Yb+ ions, and a 554 nm laser for qubit Raman manipulation, are generated by modulating a seed laser at 1108 nm through a fiber electro-optic modulator (EOM), amplified by a Yb-doped fiber amplifier, and then converted to 369 nm and 554 nm using two sequentially placed periodically-poled nonlinear crystals. This method offers significant flexibility and scalability, as different laser frequencies can be generated by adding specific radio-frequency signals to the electronic system, without altering the optical setup. The switching time between laser frequency channels is measured at 6.5 ns. With a modulation bandwidth of 20 GHz, this approach can accommodate the hyperfine splittings of various ion species. Overall, This scheme optimizes the optical configuration for atom and ion operations, minimizes insertion losses, and provides an efficient multi-channel laser frequency generation solution, making it highly beneficial for atomic and ionic quantum information experiments. © 2025

关键词： Trapped ions

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A Model-Agnostic Hierarchical Framework Towards Trajectory Prediction

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Journal of Computer science and technology 2025年第2期40卷 322-339页

作者： Qian, Tang-Wen Wang, Yuan Xu, Yong-Jun Zhang, Zhao Wu, Lin Qiu, Qiang Wang, Fei Domain-Oriented Intelligent System Research Center Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China

Predicting the future trajectories of multiple agents is essential for various applications in real life, such as surveillance systems, autonomous driving, and social robots. The trajectory prediction task is influenced by many factors, including the individual historical trajectory, interactions between agents, and the fuzzy nature of the observed agents’ motion. While existing methods have made great progress on the topic of trajectory prediction, they treat all the information uniformly, which limits the effectiveness of information utilization. To this end, in this paper, we propose and utilize a model-agnostic framework to regard all the information in a two-level hierarchical view. Particularly, the first-level view is the inter-trajectory view. In this level, we observe that the difficulty in predicting different trajectory samples varies. We define trajectory difficulty and train the proposed framework in an “easy-to-hard” schema. The second-level view is the intra-trajectory level. We find the influencing factors for a particular trajectory can be divided into two parts. The first part is global features, which keep stable within a trajectory, i.e., the expected destination. The second part is local features, which change over time, i.e., the current position. We believe that the two types of information should be handled in different ways. The hierarchical view is beneficial to take full advantage of the information in a fine-grained way. Experimental results validate the effectiveness of the proposed model-agnostic framework.

关键词： hierarchical framework model-agnostic spatial-temporal data mining trajectory prediction

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A review on global spatial distribution,sources and toxicity of perfluoroalkyl acid and prospect in the cryosphere

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Journal of Mountain science 2025年第1期22卷 167-183页

作者： LI Bowen Du Wentao KANG Shichang CHEN Jizu JIANG Youyan YIN Lichen LU Changsheng LIU Hongyi State Key Laboratory of Cryospheric Science and frozen soil engineering Northwest Institute of Eco-Environment and ResourcesChinese Academy of Sciences(CAS)Lanzhou 730000China University of Chinese Academy of Sciences Beijing 100049China Gansu Provincial Industry Technology Center of Intelligent Equipment and Big Data for Disaster Prevention Northwest Institute of Eco-Environment and ResourcesChinese Academy of Sciences(CAS)Lanzhou 730000China Lanzhou Regional Climate Center Lanzhou 730000China School of Earth Sciences and Spatial Information Engineering Hunan University of Science and TechnologyXiangtan 411201China School of Energy and Power Engineering Lanzhou University of TechnologyLanzhou 730000China Zhangye Meteorological Service Zhangye 734000China

Perfluoroalkyl acid analogs(PFAAs)are a class of chemically stable environmentally persistent organic pollutants(POPs)that are difficult to degrade and have a strong capacity to accumulate in the human *** have been found to be biotoxic to humans and have been detected in various environmental media,especially in the cryosphere at trace *** cryosphere,sensitively responds to climate change,plays a crucial role in the global water,carbon and energy ***,researches on cryosphere PFAAs especially in Tibetan Plateau(TP)is ***,we summarize the physicochemical properties,physiological toxicity,spatiotemporal distribution,sources,diffusion and migration pathways,as well as analysis and removal methods of PFAAs in the cryosphere *** results show that PFAAs pollutants are mainly produced and distributed in the more economically developed countries in Europe and the United States,as well as in East Asia,and PFAAs can be transported by atmospheric circulation and water cycle to remote regions including cryosphere *** current detection methods for PFAAs in cryosphere need to be further refined for increased accuracy and *** is also a need to develop more effective removal methods that will reduce the environmental and human threats posed by these ***,we propose key scientific questions for future research in cryosphere including PFAAs redistribution influenced by cryosphere changes,human activities,and the interaction of other spheres.

关键词： Perfluoroalkyl acid Cryosphere Physiological toxicity Analytical method Removal method

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