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Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Liang Yang Lina Kang Qiuliang Zhang Mengzhe Li Bingxin Niu Dongxiao He Zhen Wang Chuan Wang Xiaochun Cao Yuanfang Guo School of Artificial Intelligence Hebei University of Technology Tianjin China College of Intelligence and Computing Tianjin University Tianjin China School of Artificial Intelligence OPtics and ElectroNics (iOPEN) Northwestern Polytechnical University Xi'an China and School of Cybersecurity Northwestern Polytechnical University Xi'an China State Key Laboratory of Information Security IIE CAS Beijing China School of Cyber Science and Technology Sun Yat-sen University Shenzhen China School of Computer Science and Engineering Beihang University Beijing China and Zhongguancun Laboratory Beijing China

ISBN: (纸本)9781713871088

To alleviate the unfavorable effect of noisy topology in Graph Neural networks (GNNs), some efforts perform the local topology refinement through the pairwise propagation weight learning and the multi-channel extension. Unfortunately, most of them suffer a common and fatal drawback: irrelevant propagation to one node and in multi-channels. These two kinds of irrelevances make propagation weights in multi-channels free to be determined by the labeled data, and thus the GNNs are exposed to overfitting. To tackle this issue, a novel Orthogonal Propagation with Ego-Network modeling (OPEN) is proposed by modeling relevances between propagations. Specifically, the relevance between propagations to one node is modeled by whole ego-network modeling, while the relevance between propagations in multi-channels is modeled via diversity requirement. By interpreting the propagations to one node from the perspective of dimension reduction, propagation weights are inferred from principal components of the ego-network, which are orthogonal to each other. Theoretical analysis and experimental evaluations reveal four attractive characteristics of OPEN as modeling high-order relationships beyond pairwise one, preventing overfitting, robustness, and high efficiency.

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The DUDFTO Attack: Towards Down-to-UP Timeout Probing and Dynamically Flow Table Overflowing in SDN

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IEEE Transactions on Network and Service Management 2025年

作者： Li, Jiasong Cui, Yunhe Chen, Yi Shen, Guowei Guo, Chun Qian, Qing Guizhou University State Key Laboratory of Public Big Data Engineering Research Center of Text Computing and Cognitive Intelligence Ministry of Education College of Computer Science and Technology Guizhou Provincial Characteristic Key Laboratory of Software Engineering and Information Security Guiyang550000 China Guizhou University of Finance and Economics School of Information Guiyang550000 China

As a new network structure, the decoupling of the control plane and forwarding plane makes Software-Defined Networking (SDN) widely used in large-scale network scenarios. However, the decoupling network architecture also brings new vulnerabilities. The flow table overflow attack is an attack strategy that can overwhelm SDN switches. Nevertheless, the existing flow table overflow attacks may fail in probing timeouts and match fields of flow entries, due to link failure, measurement of the round-trip time (RTT) of different packets, interference of hard-timeout and idle-timeout. Meanwhile, the stealthiness of the existing attacks may also reduce, as these attacks use fixed attack rate. To improve the timeout probing accuracy and the stealthiness of attack, a new flow table overflow attack strategy, DUDFTO, is proposed to accurately probe timeout settings and match fields, then stealthily overflow SDN flow tables. Firstly, it probes the match fields by measuring the one-sided transmission delay of the packets. After that, DUDFTO designs a down-to-up feedback-based timeout probing algorithm to eliminate the issues caused by high RTT, link failure, interference between hard-timeout and idle-timeout. Then, DUDFTO designs a dynamic attack packets sending algorithm to improve its stealthiness. Finally, DUDFTO probes the flow table state to stop sending new attack packets. The evaluation results demonstrate that DUDFTO outperforms the existing attacks in terms of match fields probing ability, timeout probing relative error, number of packet_in and flow_mod messages generated by the attack, rate distribution of packet_in and flow_mod messages generated during the attack, and number of detected attack packets. © 2004-2012 IEEE.

关键词： flow table overflow attack information probing SDN switchs

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Culturally-embedded visual literacy: A study of impression management via emoticon, emoji, sticker, and meme on social media in China

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Proceedings of the ACM on Human-computer Interaction 2019年第CSCW期3卷 1-24页

作者： Wang, Yuan Li, Yukun Gui, Xinning Kou, Yubo Liu, Fenglian School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin300384 China Penn State State CollegePA United States

Social media is often analyzed as a "front stage" where social media users perform their identities and manage impressions through various forms of user-generated content: text, picture, video, as well as visual expression such as emoticon, emoji, sticker, and meme. Previous scholarship has suggested various functions of visual expression in supporting computer-mediated communication. In this study, we move beyond the utility perspective to ask what constitutes the literacy to utilize visual expression for impression management. Towards this goal, we conducted an interview study with 30 social media users in China. We found that visual literacy intersects with its cultural context. Our interviewees used text and visual expressions in sophisticated, skillful ways and tailored for different audiences in order to construct desired images. They also interacted with audience memory in order to perform their uniqueness and creativity. Lastly, we discuss culturally-embedded visual literacy and provide implications for design. Copyright is held by the owner/author(s).

关键词： Goffman backstage emoji emoticon front stage impression management meme performance social media sticker visual expression

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Removal Effect and Mechanism Analysis of Heavy Metals in Landfill Leachate by Weathered Coal

SSRN

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SSRN 2023年

作者： Song, Bo Guo, Hongyu Liu, Ang Chen, Zhenhong Li, Guofu Chen, Linyong Wei, Guoqin School of Energy Science and Engineering Henan Polytechnic University Jiaozuo454000 China Collaborative Innovation Center of Coal Work Safety and Clean High Efficiency Utilization Henan Polytechnic University Jiaozuo454000 China Department of Energy and Mineral Engineering G3 Center and Energy Institute The Pennsylvania State University University ParkPA16802 United States China National Petroleum Corporation China State Key Laboratory of Co-Mining Coal and Coalbed Methane Technology Jincheng048000 China College of Computer Science and Technology Henan Polytechnic University Jiaozuo454000 China Institute of Resources and Environment Henan Polytechnic University Jiaozuo454000 China

The aims of the present study are to reduce heavy metal content in landfill leachate as well as to improve the clean utilization of weathered coal wastes. Accordingly, landfill leachate and weathered coal were co-fermented. Using infrared spectroscopy, inducive coupling and metagenomics, the structural characteristics of heavy metal content, weathered coal functional group and gene expressions were analyzed in the fermentation system. Based on the obtained results, the co-fermentation significantly improved the formation of biological methane. Furthermore, while the absorption peaks of carboxyl and hydroxyl functional groups of weathered coal were weakened, Nitratireductor, Aquamicrobium and Paracoccus were found to be increased significantly. The heavy metal related transporter of the RND superfamily gene was also increased;this is while the heavy metal concentration was decreased. In addition, gene expression of copA, bepC, arrA, yfeC and cutO was observed to be obvious. The inhibitory effect of Mo, Cd and Cu were also reduced through the combined anaerobic fermentation. Hence, the findings of the study can be argued to offer a new approach for treating landfill leachate and utilizing weathered coal wastes. © 2023, The Authors. All rights reserved.

关键词： Heavy metals

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Large Language Models Could Be Rote Learners

arXiv

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arXiv 2025年

作者： Xu, Yuyang Hu, Renjun Ying, Haochao Wu, Jian Shi, Xing Lin, Wei College of Computer Science and Technology Zhejiang University China School of Data Science and Engineering East China Normal University China State Key Laboratory of Transvascular Implantation Devices The Second Affiliated Hospital Zhejiang University School of Medicine China School of Public Health Zhejiang University China Zhejiang Key Laboratory of Medical Imaging Artificial Intelligence China Alibaba Cloud Computing

Multiple-choice question (MCQ) benchmarks are widely used for evaluating Large Language Models (LLMs), yet their reliability is undermined by benchmark contamination. In this study, we reframe contamination as an inherent aspect of learning and seek to disentangle genuine capability acquisition from superficial memorization in LLM evaluation. First, by analyzing model performance under different memorization conditions, we uncover a counterintuitive trend: LLMs perform worse on memorized MCQs than on non-memorized ones, indicating the coexistence of two distinct learning phenomena, i.e., rote memorization and genuine capability learning. To disentangle them, we propose TrinEval, a novel evaluation framework that reformulates MCQs into an alternative trinity format, reducing memorization while preserving knowledge assessment. Experiments validate TrinEval’s effectiveness in reformulation, and its evaluation reveals that common LLMs may memorize by rote 20.5% of knowledge points (in MMLU on average). Copyright © 2025, The Authors. All rights reserved.

关键词： Teaching

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A Deep Concept-aware Model for predicting and explaining restaurant future status

A Deep Concept-aware Model for predicting and explaining res...

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IEEE International Conference on Web Services (ICWS)

作者： Hao Liao Xiaojie Zhang Xin Li Mingyang Zhou Alexandre Vidmer Rui Mao Guangdong Province Key Laboratory of Popular High Performance Computers College of Computer Science and Software Engineering Shenzhen University Guangdong Province Engineering Center of China-made High Performance Data Computing System Shenzhen City Key Laboratory of Service Computing and Application Shenzhen China Institute of Big Data Intelligent Management and Decision Shenzhen University Shenzhen China

ISBN: (数字)9781728187860

ISBN: (纸本)9781728187877

Nowadays, with the development of web services, the survival of online service has captured public attention significantly. Future prediction of business is crucial to the shopkeepers. Predicting how the business will develop and explaining what key factors are leading to it are two most important tasks. Existing literatures usually tackle only one of these two tasks, ignoring that they are two closely related tasks and complement each other. In this paper, we propose a review-based neural model, named Deep Concept-aware Model (DCA), to predict restaurants' future status and provide explainable sentences simultaneously in an end2end framework. Specifically, we use co-attention to select concepts and implement prediction and explanation tasks through Factorization Machine and Gated Recurrent Unit, respectively. We conduct extensive experiments on three Chinese cities' datasets. The proposed joint model outperforms the state-of-the-art baseline methods for both prediction (average 40.96% improvement in AUC) and explanation (average 9.72% improvement in BLEU and 86.05% in Precision metric of ROUGE).

关键词： Web services Urban areas Predictive models Prediction algorithms Data models Task analysis Business

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Simulation of serial RRAM cell based on a Verilog-A compact model

Simulation of serial RRAM cell based on a Verilog-A compact ...

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Conference on Design of Circuits and Integrated Circuits (DCIS)

作者： Binbin Yang Daniel Arumí Salvador Manich Alvaro Gómez-Pau Rosa Rodríguez-Montañés Juan Bautista Roldan Mireia Bargalló González Francesca Campabadal Liang Fang Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha China Universitat Politècnica de Catalunya Barcelona Spain Universidad de Granada (UGR) Granada Spain Institut de Microelectrònica de Barcelona-Centre Nacional de Microelectrònica Consejo Superior de Investigaciones Cientificas Bellaterra Spain

ISBN: (纸本)9781665421171

Model-based simulation is one of the effective methods of scientific research. The inherent variability of resistive switching mechanisms has been an obstacle for the massive commercial implementation of the resistive random access memory (RRAM) devices. In this work, we simulated the resistive switching behavior based on an existing RRAM Verilog-A model, in which the simulated switching parameters demonstrated a satisfactory fit with the experimental data by introducing variability into the model. Moreover, a potential application of the troublesome variability was explored in the serial configuration of two RRAM devices, a cell which had been demonstrated to generate unpredictable bits with potential applications in hardware security. Realistic simulation of RRAM based circuits is key for the future development of RRAM based applications.

关键词： Resistive RAM Switches Data models Hardware Security Integrated circuit modeling Hardware design languages

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Extending the limit of molecular dynamics with ab initio accuracy to 10 billion atoms

arXiv

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arXiv 2022年

作者： Guo, Zhuoqiang Lu, Denghui Yan, Yujin Hu, Siyu Liu, Rongrong Tan, Guangming Sun, Ninghui Jiang, Wanrun Liu, Lijun Chen, Yixiao Zhang, Linfeng Chen, Mohan Wang, Han Jia, Weile Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Architecture ICT Chinese Academy of Sciences Beijing China HEDPS CAPT College of Engineering Peking University Beijing China AI for Science Institute Beijing China Osaka University Osaka Japan Princeton University Princeton United States DP Technology Beijing China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing China

high-performance computing, together with a neural network model trained from data generated with first-principles methods, has greatly boosted applications of ab initio molecular dynamics in terms of spatial and temporal scales on modern supercomputers. Previous state-of-the-art can achieve 1 − 2 nanoseconds molecular dynamics simulation per day for 100-million atoms on the entire Summit supercomputer. In this paper, we have significantly reduced the memory footprint and computational time by a comprehensive approach with both algorithmic and system innovations. The neural network model is compressed by model tabulation, kernel fusion, and redundancy removal. Then optimizations such as acceleration of customized kernel, tabulation of activation function, MPI+OpenMP parallelization are implemented on GPU and ARM architectures. Testing results of the copper system show that the optimized code can scale up to the entire machine of both Fugaku and Summit, and the corresponding system size can be extended by a factor of 134 to an © 2022, CC BY-NC-SA.

关键词： Supercomputers

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Topological phase transition in Sb-doped Mg3Bi2 monocrystalline thin films

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Physical Review B 2021年第12期103卷 125405-125405页

作者： Tong Zhou Mingyu Tong Yun Zhang Xiangnan Xie Zhen-Yu Wang Tian Jiang Xie-Gang Zhu Xin-Chun Lai Science and Technology on Surface Physics and Chemistry Laboratory Jiangyou 621908 Sichuan People's Republic of China State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha 410073 People's Republic of China Beijing Institute for Advanced Study National University of Defense Technology Beijing 100020 People's Republic of China Institute of Materials China Academy of Engineering Physics Mianyang 621700 Sichuan People's Republic of China College of Advanced Interdisciplinary Studies National University of Defense Technology Changsha 410073 People's Republic of China National Innovation Institute of Defense Technology Academy of Military Sciences PLA China Beijing 100010 People's Republic of China Beijing Academy of Quantum Information Sciences Beijing 100193 People's Republic of China

Mg3Bi2 has been proved to be a semimetal with topological surface states (referred to as a topological semimetal, TSM) in the presence of spin-orbit coupling (SOC), and predicted to be a type-II nodal line semimetal (NSM) in the absence of SOC. It is possible to tune the effective SOC in Mg3Bi2 by substituting the heavy Bi atom with lighter atoms, such as Sb or As, which results in topological phase transitions. Here in our work we investigate the evolution of the transport properties and band structures of Mg3Bi2 by doping different concentrations of Sb through molecular beam epitaxy. Our results demonstrate the existence of phase transitions of TSM to trivial semimetal (SM) and SM to trivial insulator, with Sb concentration x at x1≈0.44–0.64 and x2≈1.39, respectively. Further theoretical calculations give values of x1≈0.523 and x2≈1.10, which agrees well with our experimental results. And all these results are concluded into a Mg3Bi2−xSbx phase diagram. Our work will stimulate more explorations to the possibilities of the realization of type-II NSM in Mg3Bi2 by various elements substitution.

关键词： Surface states Topological materials Topological phase transition Weak antilocalization Angle-resolved photoemission spectroscopy

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Stringent Tests of Lorentz Invariance Violation from LHAASO Observations of GRB 221009A

arXiv

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arXiv 2024年

作者： Cao, Zhen Aharonian, F. Axikegu Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Bian, W. Bukevich, A.V. Cao, Q. Cao, W.Y. Cao, Zhe Chang, J. Chang, J.F. Chen, A.M. Chen, E.S. Chen, H.X. Chen, Liang Chen, Lin Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, M.Y. Cui, S.W. Cui, X.H. Cui, Y.D. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu Dong, X.Q. Duan, K.K. Fan, J.H. Fan, Y.Z. Fang, J. Fang, J.H. Fang, K. Feng, C.F. Feng, H. Feng, L. Feng, S.H. Feng, X.T. Feng, Y. Feng, Y.L. Gabici, S. Gao, B. Gao, C.D. Gao, Q. Gao, W. Gao, W.K. Ge, M.M. Geng, L.S. Giacinti, G. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. Hasan, M. He, H.H. He, H.N. He, J.Y. He, Y. Hor, Y.K. Hou, B.W. Hou, C. Hou, X. Hu, H.B. Hu, Q. Hu, S.C. Huang, D.H. Huang, T.Q. Huang, W.J. Huang, X.T. Huang, X.Y. Huang, Y. Ji, X.L. Jia, H.Y. Jia, K. Jiang, K. Jiang, X.W. Jiang, Z.J. Jin, M. Kang, M.M. Karpikov, I. Kuleshov, D. Kurinov, K. Li, B.B. Li, C.M. Li, Cheng Li, Cong Li, D. Li, F. Li, H.B. Li, H.C. Li, Jian Li, Jie Li, K. Li, S.D. Li, W.L. Li, W.L. Li, X.R. Li, Xin Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, D.B. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Luo, Q. Luo, Y. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Min, Z. Mitthumsiri, W. Mu, H.J. Nan, Y.C. Neronov, A. Ou, L.J. Pattarakijwanich, P. Pei, Z.Y. Qi, J.C. Qi, M.Y. Qiao, B.Q. Qin, J.J. Raza, A. Ruffolo, D. Sáiz, A. Saeed, M. Semikoz, D. Shao, L. Shchegolev, O. Sheng, X.D. Shu, F.W. Song, H.C. Stenkin, Yu.V. Stepanov, V. Su, Y. Sun, D.X. Sun, Q.N. Sun, X.N. Sun, Z.B. Takata, J. Tam, P.H.T. Key Laboratory of Particle Astrophysics & Experimental Physics Division & Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China Tianfu Cosmic Ray Research Center Sichuan Chengdu610000 China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China Tsung-Dao Lee Institute School of Physics and Astronomy Shanghai Jiao Tong University Shanghai200240 China Institute for Nuclear Research Russian Academy of Sciences Moscow117312 Russia Hebei Normal University Hebei Shijiazhuang050024 China University of Science and Technology of China Anhui Hefei230026 China State Key Laboratory of Particle Detection and Electronics China Key Laboratory of Dark Matter and Space Astronomy Key Laboratory of Radio Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Research Center for Astronomical Computing Zhejiang Laboratory Zhejiang Hangzhou311121 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China School of Physics and Astronomy Yunnan University Yunnan Kunming650091 China Key Laboratory of Cosmic Rays Tibet University Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Sun Yat-sen University Zhuhai519000 China Guangdong Guangzhou510275 China Institute of Frontier and Interdisciplinary Science Shandong University Shandong Qingdao2

On October 9, 2022, the Large high Altitude Air Shower Observatory (LHAASO) reported the observation of the very early TeV afterglow of the brightest-of-all-time GRB 221009A, recording the highest photon statistics in the TeV band ever obtained from a Gamma-ray burst. We use this unique observation to place stringent constraints on an energy dependence of the speed of light in vacuum, a manifestation of Lorentz invariance violation (LIV) predicted by some quantum gravity (QG) theories. Our results show that the 95% confidence level lower limits on the QG energy scales are EQG,1 > 10 times of the Planck energy EPl for the linear, and EQG,2 > 6 × 10−8EPl for the quadratic LIV effects, respectively. Our limits on the quadratic LIV case improve previous best bounds by factors of 5–7. Copyright © 2024, The Authors. All rights reserved.

关键词： Light velocity

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