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arXiv 2024年

作者： Chen, Xiaodong Hu, Yuxuan Zhang, Xiaokang Wang, Yanling Li, Cuiping Chen, Hong Zhang, Jing School of Information Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering Beijing China Zhongguancun Laboratory China

Pruning has become a widely adopted technique for reducing the hardware requirements of large language models (LLMs). To recover model performance after pruning, post-training is commonly employed to mitigate the resulting performance degradation. While post-training benefits from larger datasets, once the dataset size is already substantial, increasing the training data provides only limited performance gains. To balance post-training cost and model performance, it is necessary to explore the optimal amount of post-training data. Through extensive experiments on the Llama-3 and Qwen-2.5 series models, pruned using various common pruning methods, we uncover the scaling Law for Post-training after model Pruning, referred to as the P2 Law. This law identifies four key factors for predicting the pruned model’s post-training loss: the model size before pruning, the number of post-training tokens, the pruning rate, and the model’s loss before pruning. Moreover, P2 Law can generalize to larger dataset sizes, larger model sizes, and higher pruning rates, offering valuable insights for the post-training of pruned LLMs. © 2024, CC BY.

关键词： Digital elevation model

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EEG-Based Joint Semi-supervised Learning for Major Depressive Disorder Detection 26th

EEG-Based Joint Semi-supervised Learning for Major Depressi...

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26th International Conference on Pattern Recognition, ICPR 2022

作者： Chen, Tao Zheng, Tong Shi, Jinlong Guo, Yanrong Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Hefei China School of Computer Science and Information Engineering Hefei University of Technology Hefei China

ISBN: (纸本)9783031376597

Major Depressive Disorder (MDD) has been a major mental disease in recent years, imposing huge negative impacts on both our society and individuals. The current clinical MDD detection methods, such as self-report scales and interviews, often suffer from their subjectiveness. In contrast, electroencephalography (EEG) signals reflect brain activity and can be used as an effective information source for MDD detection. However, the learning-based MDD detection methods with EEG data usually neglect the valuable information contained in the unlabeled data, therefore possibly suffering from the label scarcity issue. In this context, we propose a simple EEG-based Joint Semi-supervised Learning (JSL) model for the MDD detection task, which fully leverages the information from unlabeled data. Specifically, by equipping the unlabeled samples with the intermediately predicted pseudo labels, the accurate position of the class-specific centroids in the feature space can be gradually refined. Based on that, the auxiliary labels based on a heuristic centroid-based classifier can be obtained, which plays an effective complementary role in predicting the sample labels. The experiments on a public dataset demonstrate the effectivenes s of our method, showing an obvious performance gain via using the proposed semi-supervised strategy. © 2023, Springer Nature Switzerland AG.

关键词： Electroencephalography

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Optimization of Resource Allocation in Unmanned Aerial Vehicles Based on Swarm Intelligence Algorithms

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Computers, Materials & Continua 2023年第5期75卷 4341-4355页

作者： Siling Feng Yinjie Chen Mengxing Huang Feng Shu School of Information and Communication Engineering Hainan UniversityNo.58 Renmin AvenueHaikou570228China State Key Laboratory of Marine Resource Utilization in the South China Sea Hainan UniversityNo.58 Renmin AvenueHaikou570228China

Due to their adaptability,Unmanned Aerial Vehicles(UAVs)play an essential role in the Internet of Things(IoT).Using wireless power transfer(WPT)techniques,an UAV can be supplied with energy while in flight,thereby extending the lifetime of this energy-constrained *** paper investigates the optimization of resource allocation in light of the fact that power transfer and data transmission cannot be performed *** this paper,we propose an optimization strategy for the resource allocation of UAVs in sensor communication *** is a practical solution to the problem of marine sensor networks that are located far from shore and have limited power.A corresponding system model is summarized based on the scenario and existing theoretical *** minimum throughputmaximizing object is then formulated as an optimization *** swarm intelligence algorithms are utilized effectively in numerous fields,this paper chose to solve the formed optimization problem using the Harris Hawks Optimization and Whale Optimization *** paper introduces a method for translating multi-decisions into a row vector in order to adapt swarm intelligence algorithms to the problem,as joint time and energy optimization have two sets of *** proposed method performs well in terms of stability and ***,performance is evaluated through numerical *** results demonstrate that the proposed method performs admirably in the given scenario.

关键词： Resource allocation unmanned aerial vehicles harris hawks optimization whale optimization algorithm

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SMEC:Scene Mining for E-Commerce

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Journal of Computer Science & Technology 2024年第1期39卷 192-210页

作者：王罡李翔郭子义殷大伟马帅 State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Data Science and Engineering East China Normal UniversityShanghai 200062China *** Inc.Beijing 100176China Baidu Inc.Beijing 100085China

Scene-based recommendation has proven its usefulness in E-commerce,by recommending commodities based on a given ***,scenes are typically unknown in advance,which necessitates scene discovery for *** this article,we study scene discovery for E-commerce *** first formalize a scene as a set of commodity cate-gories that occur simultaneously and frequently in real-world situations,and model an E-commerce platform as a heteroge-neous information network(HIN),whose nodes and links represent different types of objects and different types of rela-tionships between objects,*** then formulate the scene mining problem for E-commerce as an unsupervised learning problem that finds the overlapping clusters of commodity categories in the *** solve the problem,we pro-pose a non-negative matrix factorization based method SMEC(Scene Mining for E-Commerce),and theoretically prove its *** six real-world E-commerce datasets,we finally conduct an extensive experimental study to evaluate SMEC against 13 other methods,and show that SMEC consistently outperforms its competitors with regard to various evaluation measures.

关键词： graph clustering E-commerce heterogeneous information network(HIN) scene mining

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Sequential Fusion of Text-close and Text-far Representations for Multimodal Sentiment Analysis 31

Sequential Fusion of Text-close and Text-far Representations...

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31st International Conference on Computational Linguistics, COLING 2025

作者： Sun, Kaiwei Tian, Mi Key Laboratory of Data Engineering and Visual Computing Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9798891761964

Multimodal Sentiment Analysis (MSA) aims to identify human attitudes from diverse modalities such as visual, audio and text modalities. Recent studies suggest that the text modality tends to be the most effective, which has encouraged models to consider text as its core modality. However, previous methods primarily concentrate on projecting modalities other than text into a space close to the text modality and learning an identical representation, which does not fully make use of the auxiliary information provided by audio and visual modalities. In this paper, we propose a framework, Sequential Fusion of Text-close and Text-far Representations (SFTTR), aiming to refine multimodal representations from multimodal data which should contain both representations close to and far from the text modality. Specifically, we employ contrastive learning to sufficiently explore the information similarities and differences between text and audio/visual modalities. Moreover, to fuse the extracted representations more effectively, we design a sequential cross-modal encoder to sequentially fuse representations that are close to and far from the text modality. Experiments on three public benchmark datasets, MOSI, MOSEI, and CH-SIMS, demonstrate the superiority of the proposed method over the state-of-the-arts. © 2025 Association for Computational Linguistics.

关键词： Contrastive Learning

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A Linked List Encryption Scheme for Image Steganography without Embedding

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Computer Modeling in engineering & Sciences 2024年第10期141卷 331-352页

作者： Pengbiao Zhao Qi Zhong Jingxue Chen Xiaopei Wang Zhen Qin Erqiang Zhou Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of ChinaChengdu610054China Faculty of Data Science City University of MacaoMacao999078China Department of Computer Science and Engineering University of CaliforniaRiversideCA 92521USA

Information steganography has received more and more attention from scholars nowadays,especially in the area of image steganography,which uses image content to transmit information and makes the existence of secret information *** enhance concealment and security,the Steganography without Embedding(SWE)method has proven effective in avoiding image distortion resulting from cover *** this paper,a novel encrypted communication scheme for image SWE is *** reconstructs the image into a multi-linked list structure consisting of numerous nodes,where each pixel is transformed into a single node with data and pointer *** employing a special addressing algorithm,the optimal linked list corresponding to the secret information can be *** receiver can restore the secretmessage fromthe received image using only the list header position *** scheme is based on the concept of coverless steganography,eliminating the need for any modifications to the cover *** boasts high concealment and security,along with a complete message restoration rate,making it resistant to ***,this paper proposes linked-list construction schemeswithin theproposedframework,which caneffectively resist a variety of attacks,includingnoise attacks and image compression,demonstrating a certain degree of *** validate the proposed framework,practical tests and comparisons are conducted using multiple *** results affirm the framework’s commendable performance in terms of message reduction rate,hidden writing capacity,and robustness against diverse attacks.

关键词： Steganography encryption steganography without embedding coverless steganography

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Scalable and adaptive log manager in distributed systems

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Frontiers of Computer Science 2023年第2期17卷 45-62页

作者： Huan ZHOU Weining QIAN Xuan ZHOU Qiwen DONG Aoying ZHOU Wenrong TAN The Key Laboratory for Computer Systems of State Ethnic Affairs Commission Southwest Minzu UniversityChengdu 610041China School of Data Science and Engineering East China Normal UniversityShanghai 200062China

On-line transaction processing(OLTP)systems rely on transaction logging and quorum-based consensus protocol to guarantee durability,high availability and strong *** makes the log manager a key component of distributed database management systems(DDBMSs).The leader of DDBMSs commonly adopts a centralized logging method to writing log entries into a stable storage device and uses a constant log replication strategy to periodically synchronize its state to *** the advent of new hardware and high parallelism of transaction processing,the traditional centralized design of logging limits scalability,and the constant trigger condition of replication can not always maintain optimal performance under dynamic *** this paper,we propose a new log manager named Salmo with scalable logging and adaptive replication for distributed database *** scalable logging eliminates centralized contention by utilizing a highly concurrent data structure and speedy log hole *** kernel of adaptive replication is an adaptive log shipping method,which dynamically adjusts the number of log entries transmitted between leader and followers based on the real-time *** implemented and evaluated Salmo in the open-sourced transaction processing systems Cedar and *** results show that Salmo scales well by increasing the number of working threads,improves peak throughput by 1.56×and reduces latency by more than 4×over log replication of Raft,and maintains efficient and stable performance under dynamic workloads all the time.

关键词： distributed database systems transaction log-ging log replication scalable adaptive

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Adaptive multiscale convolutional neural network model for chemical process fault diagnosis

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Chinese Journal of Chemical engineering 2022年第10期50卷 398-411页

作者： Ruoshi Qin Jinsong Zhao State Key Laboratory of Chemical Engineering Department of Chemical EngineeringTsinghua UniversityBeijing 100084China Beijing Key Laboratory of Industrial Big Data System and Application Tsinghua UniversityBeijing 100084China

Intelligent fault recognition techniques are essential to ensure the long-term reliability of *** to the variations in material,equipment and environment,the process variables monitored by sensors contain diverse data characteristics at different time scales or in multiple operating *** much progress in statistical learning and deep learning for fault recognition,most models are constrained by abundant diagnostic expertise,inefficient multiscale feature extraction and unruly multimode *** overcome the above issues,a novel fault diagnosis model called adaptive multiscale convolutional neural network(AMCNN)is developed in this paper.A new multiscale convolutional learning structure is designed to automatically mine multiple-scale features from time-series data,embedding the adaptive attention module to adjust the selection of relevant fault pattern *** triplet loss optimization is adopted to increase the discrimination capability of the model under the multimode *** benchmarks CSTR simulation and Tennessee Eastman process are utilized to verify and illustrate the feasibility and efficiency of the proposed *** with other common models,AMCNN shows its outstanding fault diagnosis performance and great generalization ability.

关键词： Neural networks Multiscale Adaptive attentionmodule Triplet lossoptimization Fault diagnosis Chemical processes

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Bifunctional optical probe based on La_(3)Mg_(2)SbO_(9):Mn^(4+)phosphors for temperature and pressure sensing

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Journal of Materials Science & Technology 2024年第27期194卷 98-109页

作者： Zhanglin Chen Songmo Du Fei Li Shijia Zhang Shuo Zhao Zhaobo Tian Jie Zhang Xuanyi Yuan Guanghua Liu Kexin Chen State Key Laboratory of New Ceramics&Fine Processing School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China School of Microelectronics Southern University of Science and TechnologyShenzhen 518055China Advanced Ceramics and Structures Center Yongjiang LaboratoryNingbo 315021China Beijing Key Laboratory of Optoelectronic Functional Materials&Micro-nano Devices Department of PhysicsRenmin University of ChinaBeijing 100872China

Photoluminescent materials,serving as optical probes,constitute a significant medium for reliable re-mote sensing of fundamental state parameters such as temperature and ***,we report a novel Mn^(4+)-activated perovskite-type La_(3) Mg2 SbO9 phosphor(LMS:Mn^(4+))for bifunctional application in both thermometry and *** excitation with 341 nm,LMS:Mn^(4+)(0.7%Mn^(4+))emits a bright narrow-band red light peaking at 705 nm with an FWHM(full width at half maximum)of 32 *** a thermometer,when the temperature surpasses 298 K,non-radiative transitions from the ^(2)Eg excited state lead to a sharp decrease in decay lifetimes with increasing *** allows for lifetime-based luminescence thermometry with a relative sensitivity of 2.52%K^(−1) at 391 ***,LMS:Mn^(4+)was processed into a temperature-sensing coating and its non-contact thermometry functionality was *** manometry applications,the LMS:Mn^(4+)probe experiences substantial pressure-dependent redshift with a sensitivity of 1.20 nm GPa^(−1) in the testing range of 9.48 GPa,which is about 3.3 times that of conventional ruby ***,its FWHM consistently remains below 37 nm,which con-tributes to a high reliability of pressure *** above results indicate that the LMS:Mn^(4+)constitutes a promising bifunctional luminescence probe material in thermometry and manometry.

关键词： Perovskite Phosphors Thermometry Manometry

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CONSTRUCTURE: Benchmarking CONcept STRUCTUre REasoning for Multimodal Large Language Models

CONSTRUCTURE: Benchmarking CONcept STRUCTUre REasoning for M...

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2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Zha, Zhiwei Zhu, Xiangru Xu, Yuanyi Huang, Chenghua Liu, Jingping Li, Zhixu Wang, Xuwu Xiao, Yanghua Yang, Bei Xu, XiaoXiao Shanghai Key Laboratory of Data Science School of Computer Science Fudan University China School of Information Science and Engineering East China University of Science and Technology China Alibaba Group China School of Information Renmin University of China China Renmin University of China China

ISBN: (纸本)9798891761681

Multimodal Large Language Models (MLLMs) have shown promising results in various tasks, but their ability to perceive the visual world with deep, hierarchical understanding similar to humans remains uncertain. To address this gap, we introduce CONSTRUCTURE, a novel concept-level benchmark to assess MLLMs' hierarchical concept understanding and reasoning abilities. Our goal is to evaluate MLLMs across four key aspects: 1) Understanding atomic concepts at different levels of abstraction;2) Performing upward abstraction reasoning across concepts;3) Achieving downward concretization reasoning across concepts;and 4) Conducting multi-hop reasoning between sibling or common ancestor concepts. Our findings indicate that even state-of-the-art multimodal models struggle with concept structure reasoning (e.g., GPT-4o averages a score of 62.1%). We summarize key findings of MLLMs in concept structure reasoning evaluation. Morever, we provide key insights from experiments using CoT prompting and fine-tuning to enhance their abilities. © 2024 Association for Computational Linguistics.

关键词： Abstracting

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