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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Zhao, Weihao He, Weidong Wang, Hao Bi, Haoyang Wu, Han Zhu, Chen Xu, Tong Chen, Enhong University of Science and Technology of China State Key Laboratory of Cognitive Intelligence China Career Science Lab BOSS Zhipin China School of Management University of Science and Technology of China China

ISBN: (纸本)9782493814104

As a fresh way to improve the user viewing experience, videos of time-sync comments have attracted a lot of interest. Many efforts have been made to explore the effectiveness of time-sync comments for various applications. However, due to the complexity of interactions among users, videos, and comments, it still remains challenging to understand users' behavior on time-sync comments. Along this line, we study the problem of time-sync comment behavior prediction with considerations of both historical behaviors and multi-modal information of visual frames and textual comments. Specifically, we propose a novel Multi-modal short- and long-Range Temporal Convolutional Network model, namely MRT. Firstly, we design two amplified Temporal Convolutional Networks with different sizes of receptive fields, to capture both short- and long-range surrounding contexts for each frame and time-sync comments. Then, we design a bottle-neck fusion module to obtain the multi-modal enhanced representation. Furthermore, we take the user preferences into consideration to generate the personalized multi-model semantic representation at each timestamp. Finally, we utilize the binary cross-entropy loss to optimize MRT on the basis of users' historical records. Through comparing with representative baselines, we demonstrate the effectiveness of MRT and qualitatively verify the necessity and utility of short- and long-range contextual and multi-modal information through extensive experiments. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Bottles

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Human-machine shared control:New avenue to dexterous prosthetic hand manipulation

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Science China(Technological Sciences) 2021年第4期64卷 767-773页

作者： YANG DaPeng LIU Hong State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150080China Artificial Intelligence Laboratory Harbin Institute of TechnologyHarbin 150080China

At present,albeit the dexterous hand prostheses of multiple degrees of freedom(DOFs)have become prosperous on the market,the user’s demand on intuitively operating these devices have not been well addressed so that their acceptance rate is relatively *** unintuitive control method and inadequate sensory feedback are frequently cited as the two barriers to the successful application of these dexterous ***,driven by the wave of artificial intelligence(AI),a series of shared control methods have emerged,in which"bodily function"(myoelectric control)and"artificial intelligence"(local autonomy,computer vision,etc.)are tightly integrated,and provided a new conceptual solution for the intuitive operation of dexterous *** this paper,the background and development trends of this type of methods are described in detail,and the potential development directions and the key technologies that need breakthroughs are *** practice,we instantiate this shared control strategy by proposing a new method combining simultaneous myoelectric control,multi-finger grasp autonomy,and augmented reality(AR)feedback *** method"divides"the human sophisticated reach-and-grasp task into several subtasks,and then"conquers"them by using different strategies from either human or machine *** is highly expected that the shared control methods with hybrid human-machine intelligence could address the control problem of dexterous prostheses.

关键词： robotic hand dexterous prostheses shared control computer vision deep learning

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3D bioprinting of in vitro porous hepatoma models:establishment,evaluation,and anticancer drug testing

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Bio-Design and Manufacturing 2024年第2期7卷 137-152页

作者： Xiaoyuan Wang Zixian Liu Qianqian Duan Boye Zhang Yanyan Cao Zhizhong Shen Meng Li Yanfeng Xi Jianming Wang Shengbo Sang Shanxi Key Laboratory of Micro Nano Sensors and Artificial Intelligence Perception College of Electronic Information and Optical EngineeringTaiyuan University of TechnologyTaiyuan 030024China Key Lab of Advanced Transducers and Intelligent Control System of the Ministry of Education Taiyuan University of TechnologyTaiyuan 030024China Shanxi Institute of 6D Artificial Intelligence Biomedical Science Taiyuan 030031China Shanxi-Zheda Institute of Advanced Materials and Chemical Engineering Taiyuan 030024China Department of Pathology Shanxi Provincial Cancer HospitalTaiyuan 030024China General Hospital of Taiyuan Iron and Steel Company Taiyuan 030809China

Traditional tumor models do not tend to accurately simulate tumor growth in vitro or enable personalized treatment and are particularly unable to discover more beneficial targeted *** address this,this study describes the use of threedimensional(3D)bioprinting technology to construct a 3D model with human hepatocarcinoma SMMC-7721 cells(3DP-7721)by combining gelatin methacrylate(GelMA)and poly(ethylene oxide)(PEO)as two immiscible aqueous phases to form a bioink and innovatively applying fluorescent carbon quantum dots for long-term tracking of *** GelMA(10%,mass fraction)and PEO(1.6%,mass fraction)hydrogel with 3:1 volume ratio offered distinct pore-forming characteristics,satisfactorymechanical properties,and biocompatibility for the creation of the 3DP-7721 *** analysis and quantitative real-time fluorescence polymerase chain reaction(PCR)were used to evaluate the biological properties of the *** with the two-dimensional culture cell model(2D-7721)and the 3D mixed culture cell model(3DM-7721),3DP-7721 significantly improved the proliferation of cells and expression of tumor-related proteins and ***,we evaluated the differences between the three culture models and the effectiveness of antitumor drugs in the three models and discovered that the efficacy of antitumor drugs varied because of significant differences in resistance proteins and genes between the three *** addition,the comparison of tumor formation in the three models found that the cells cultured by the 3DP-7721 model had strong tumorigenicity in nude *** evaluation of the levels of biochemical indicators related to the formation of solid tumors showed that the 3DP-7721 model group exhibited pathological characteristics of malignant tumors,the generated solid tumors were similar to actual tumors,and the deterioration was *** research therefore acts as a foundation for the application of 3DP-7721 models in drug devel

关键词： 3D bioprinting Hepatoma tumor models Drug screening Antitumor drug development

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Geochemical evolution of Mesozoic and Cenozoic mafic igneous rocks in the eastern Tethyan realm:Implications for the tectonic evolution of convergent plate margins

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Science China Earth Sciences 2025年第4期68卷 1116-1141页

作者： Long CHEN YongFei ZHENG Frontiers Science Center for Deep Ocean Multispheres and Earth System Key Lab of Submarine GeoSciences and Prospecting TechniquesMOE and College of Marine GeoSciencesOcean University of ChinaQingdao266100China Laoshan Laboratory Qingdao266237China State Key Laboratory of Lithospheric and Environmental Coevolution School of Earth and Space SciencesUniversity of Science and Technology of ChinaHefei230026China

The convergent plate margins of Paleo-Tethys Ocean and Neo-Tethys Ocean are the two orogenic belts in the eastern Tethyan realm with the best exposures of igneous *** studies have revealed that both belts have developed not only island arc basalts(IAB)-like mafic magmatism but also ocean island basalts(OIB)±mid-ocean ridge basalts(MORB)-like mafic magmatism in various stages of their formation and *** different types of mafic igneous rocks show both similarity and difference that were acquired in the various stages from oceanic subduction through continental collision to intracontinental *** examination and comparison of these igneous rocks can provide insights into the tectonic evolution of the eastern Tethyan *** study integrates the spatiotemporal distribution and geochemical compositions of Mesozoic and Cenozoic primitive mafic igneous rocks in the eastern Tethyan realm within *** results show:(1)in addition to the stage of oceanic subduction,the stages of continental collision and intracontinental reworking are the primary periods of mafic magmatic activity at convergent plate margins,consistent across the Paleo-Tethyan and Neo-Tethyan domains.(2)OIB(±MORB)-like mafic igneous rocks are present not only in the stage of continental collision in both domains but also in the stage of intracontinental reworking in the Paleo-Tethyan domain.(3)In the stages from oceanic subduction to continental collision,the compositions of IAB-like mafic igneous rocks in both domains exhibit continuous variations,with remarkable similarities in lithology,elemental and isotopic characteristics,indicating their formation through similar deep geodynamic processes—partial melting of the mantle wedge metasomatized by subducting slab-derived fluids in the forms of aqueous solution and/or hydrous *** a consequence,the mafic igneous rocks display more compositional inheritance than *** the stage of continental collision,

关键词： Convergent plate margin Oceanic subduction Continental collision Intracontinental reworking Mafic magma-tism Crust-mantle interaction

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Rethinking the Membrane Dynamics and Optimization Objectives of Spiking Neural Networks 38

Rethinking the Membrane Dynamics and Optimization Objectives...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Shen, Hangchi Zheng, Qian Wang, Huamin Pan, Gang College of Artificial Intelligence Southwest University China Chongqing Key Laboratory of Brain Inspired Computing and Intelligent Chips China The State Key Lab of Brain-Machine Intelligence Zhejiang University China College of Computer Science and Technology Zhejiang University China

Despite spiking neural networks (SNNs) have demonstrated notable energy efficiency across various fields, the limited firing patterns of spiking neurons within fixed time steps restrict the expression of information, which impedes further improvement of SNN performance. In addition, current implementations of SNNs typically consider the firing rate or average membrane potential of the last layer as the output, lacking exploration of other possibilities. In this paper, we identify that the limited spike patterns of spiking neurons stem from the initial membrane potential (IMP), which is set to 0. By adjusting the IMP, the spiking neurons can generate additional firing patterns and pattern mappings. Furthermore, we find that in static tasks, the accuracy of SNNs at each time step increases as the membrane potential evolves from zero. This observation inspires us to propose a learnable IMP, which can accelerate the evolution of membrane potential and enables higher performance within a limited number of time steps. Additionally, we introduce the last time step (LTS) approach to accelerate convergence in static tasks, and we propose a label smooth temporal efficient training (TET) loss to mitigate the conflicts between optimization objective and regularization term in the vanilla TET. Our methods improve the accuracy by 4.05% on ImageNet compared to baseline and achieve state-of-the-art performance of 87.80% on CIFAR10-DVS and 87.86% on N-Caltech101. The code is available at https://***/StephenTaylor1998/IMP-SNN. © 2024 Neural information processing systems foundation. All rights reserved.

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FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Models 38

FIRE: A Dataset for Feedback Integration and Refinement Eval...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Li, Pengxiang Gao, Zhi Zhang, Bofei Yuan, Tao Wu, Yuwei Harandi, Mehrtash Jia, Yunde Zhu, Song-Chun Li, Qing Beijing Key Laboratory of Intelligent Information Technology School of Computer Science & Technology Beijing Institute of Technology China State Key Laboratory of General Artificial Intelligence BIGAI China State Key Laboratory of General Artificial Intelligence Peking University China Department of Electrical and Computer System Engineering Monash University Australia Guangdong Laboratory of Machine Perception and Intelligent Computing Shenzhen MSU-BIT University China Department of Automation Tsinghua University China

Vision language models (VLMs) have achieved impressive progress in diverse applications, becoming a prevalent research direction. In this paper, we build FIRE, a feedback-refinement dataset, consisting of 1.1M multi-turn conversations that are derived from 27 source datasets, empowering VLMs to spontaneously refine their responses based on user feedback across diverse tasks. To scale up the data collection, FIRE is collected in two components: FIRE-100K and FIRE-1M, where FIRE-100K is generated by GPT-4V, and FIRE-1M is freely generated via models trained on FIRE-100K. Then, we build FIRE-Bench, a benchmark to comprehensively evaluate the feedback-refining capability of VLMs, which contains 11K feedback-refinement conversations as the test data, two evaluation settings, and a model to provide feedback for VLMs. We develop the FIRE-LLaVA model by fine-tuning LLaVA on FIRE-100K and FIRE-1M, which shows remarkable feedback-refining capability on FIRE-Bench and outperforms untrained VLMs by 50%, making more efficient user-agent interactions and underscoring the significance of the FIRE dataset. © 2024 Neural information processing systems foundation. All rights reserved.

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Optimizing over Multiple Distributions under Generalized Quasar-Convexity Condition 38

Optimizing over Multiple Distributions under Generalized Qua...

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Ding, Shihong Yang, Long Luo, Luo Fang, Cong State Key Lab of General AI School of Intelligence Science and Technology Peking University China School of Data Science Fudan University China Institute for Artificial Intelligence Peking University China Shanghai Key Laboratory for Contemporary Applied Mathematics China

We study a typical optimization model where the optimization variable is composed of multiple probability distributions. Though the model appears frequently in practice, such as for policy problems, it lacks specific analysis in the general setting. For this optimization problem, we propose a new structural condition/landscape description named generalized quasar-convexity (GQC) beyond the realms of convexity. In contrast to original quasar-convexity [24], GQC allows an individual quasar-convex parameter γi for each variable block i and the smaller of γi implies less block-convexity. To minimize the objective function, we consider a generalized oracle termed as the internal function that includes the standard gradient oracle as a special case. We provide optimistic mirror descent (OMD) for multiple distributions and prove that the algorithm can achieve an adaptive (Equation presented) iteration complexity to find an Ε-suboptimal global solution without pre-known the exact values of γi when the objective admits "polynomial-like" structural. Notably, it achieves iteration complexity that does not explicitly depend on the number of distributions and strictly faster (Equation presented) than mirror decent methods. We also extend GQC to the minimax optimization problem proposing the generalized quasar-convexity-concavity (GQCC) condition and a decentralized variant of OMD with regularization. Finally, we show the applications of our algorithmic framework on discounted Markov Decision Processes problem and Markov games, which bring new insights on the landscape analysis of reinforcement learning. © 2024 Neural information processing systems foundation. All rights reserved.

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Xu, Ruijie Chen, Shichao Sun, Wenqiao Lv, Yisheng Luo, Jialiang Tang, Ying Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences China University of Geosciences Beijing School of Information Engineering The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Rowan University Department of Electrical and Computer Engineering Glassboro United States

ISBN: (纸本)9798350337020

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance. © 2023 IEEE.

关键词： Cubature Kalman Filter Inertial Pedestrian Navigation Zero-Velocity Update

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LG-LSTM: Modeling LSTM-Based Interactions for Multi-Agent Trajectory Prediction

LG-LSTM: Modeling LSTM-Based Interactions for Multi-Agent Tr...

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2022 IEEE International Conference on Multimedia and Expo, ICME 2022

作者： Sun, Hanbing Chen, Runfa Liu, Tianyu Wang, Haiwen Sun, Fuchun State Key Lab on Intelligence Technology and Systems Department of Computer Science and Technology Beijing China

ISBN: (数字)9781665485630

ISBN: (纸本)9781665485630

Predicting the future trajectory of multi-agent in dynamic scenarios is a crucial part of autonomous driving. Despite fruitful progress, existing methods still suffer from immatu-rity in tackling social interaction modeling, which is essential for trajectory prediction. A key reason is that the previous works only consider the interaction of a single category of agents while ignoring the influence between different types of agents. This paper contends a novel framework LG-LSTM to model local and global social interactions between different types of agents by scenario graph and attention fusion. It is mainly composed of two functional components: 1. LSTM-based interaction architecture consists of LSTM-based en-coding function, graph-aware encoding function, attention-fusion encoding function, and LSTM-based decoding function. 2. Multi-task training, which conducts trajectory pre-diction and multi-agent classification. Extensive experiments on two public autonomous driving benchmarks verify the ef-ficacy of the proposed techniques and achieve superior per-formance against state-of-the-art approaches. © 2022 IEEE.

关键词： Trajectories

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The Effect of Coherent Frequency Diverse Array on Watson-Watt Direction-Finding system 4

The Effect of Coherent Frequency Diverse Array on Watson-Wat...

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4th International Conference on Neural Networks, Information and Communication Engineering, NNICE 2024

作者： Liu, Qiang Xiong, Kunlai Guo, Fucheng Xu, Tao National University of Defense Technology State Key Lab. of Complex Electromagnetic Environment Effects on Electronics and Information System College of Electronic Science and Technology Hunan Changsha410073 China

ISBN: (纸本)9798350394375

Frequency diverse array(FDA) offer potential applications for enhancing the RF safety performance of FDA systems. This is due to the time-varying angle-distance coupling characteristics of the transmit beam map, which are caused by small frequency shifts between subarray elements. In this paper, we investigate the impact of coherent FDA signals on amplitude-based direction-finding systems, taking the Watson-Watt direction-finding system as an example. Firstly, we establish receiving model for direction finding of FDA signals. Secondly, we evaluate the error of the direction-finding system when using coherent FDA signals and analyze it with the Cramér-Rao lower bound(CRLB). Finally, we conduct a simulation analysis to validate the proposed theory. Both the theoretical analysis and simulation results demonstrate that coherent FDA signals can improve the radio frequency(RF) stealth performance. Specifically, the analysis and simulation results reveal that coherent FDA signals exhibit superior low-intercept performance for the Watson-Watt direction-finding system. These findings can be applied to all amplitude direction-finding systems. © 2024 IEEE.

关键词： Radio direction finding systems

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