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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： Wu, Yexin Zhang, Zhuosheng Zhao, Hai College of Zhiyuan Shanghai Jiao Tong University China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9782493814104

Large language models have manifested remarkable capabilities by leveraging chain-of-thought (CoT) reasoning techniques to solve intricate questions through step-by-step reasoning chains. Despite its success, the efficacy of such reasoning is inherently contingent upon the quality of CoT. However, flawless CoT reasoning cannot be guaranteed due to the presence of indecomposable questions and the potential for erroneous reasoning chains, particularly in the case of small-scale language models. To tackle this challenge, we propose a novel approach called the selective filtering reasoner (SelF-Reasoner) that assesses the entailment relationship between the question and the candidate reasoning chain. Then, we proceed with CoT reasoning when the reasoning chain demonstrates confidence;otherwise, we opt to predict the answer directly. SelF-Reasoner improves the fine-tuned T5 baseline consistently over the scienceQA, ECQA, and LastLetter tasks. Code is available at https://***/LibroWu/SelF-Reasoner. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Computational linguistics

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The Bird Flight Movement Information Acquisition Equipment Design and Implementation Based on The STM32

The Bird Flight Movement Information Acquisition Equipment D...

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2022 International Conference on computer, Artificial Intelligence, and Control engineering, CAICE 2022

作者： Guo, Zhixin Yang, Long Ma, Erteng Li, Yang Shang, Zhigang School of Electrical Engineering Zhengzhou University Zhengzhou450001 China Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology Zhengzhou450001 China

ISBN: (纸本)9781510655942

Birds have excellent three-dimensional space movement ability. The research and design of small and lightweight bird flight movement behavior information collection equipment has important application value in the research of bird robots and other aspects. Based on STM32F103 series chips, this paper designs a low cost small lightweight bird flight movement information acquisition device, and uses FREERTOS multi-task real-time operating system to realize the acquisition and storage of movement behavior information on this device. © 2022 SPIE.

关键词： Birds

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Observation of frequency diffraction management in spoof plasmonic waveguides

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Physical Review B 2025年第3期111卷 035420-035420页

作者： Qingqing Cheng Qunchao Ma Zhenyu Jiang Zhuochao Tie Jingkun Zhuang Songlin Zhuang School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai 200093 China State Key Laboratory of Terahertz and Millimeter Waves City University of Hong Kong Hong Kong China

The engineering of electromagnetic waves in rf driving platforms is advancing rapidly, driven by advancements in topological photonics and waveguide technologies. However, challenges remain in achieving precise control over frequency diffraction and mode coupling in practical applications. Our work addresses these challenges by introducing an approach that incorporates a voltage-controlled, time-dependent varactor diode within a microwave spoof plasmonic waveguide. By employing periodic voltage modulations through square, sinusoidal, and sawtooth waveforms, we explore their distinct effects on discrete frequency diffraction, sideband suppression, and directional nondiffraction frequency shifts. Our findings demonstrate the efficacy of extended coupled mode equations, which include higher-order coupling terms, in facilitating harmonic control over electromagnetic spectra. Our research highlights potential applications in communication systems and signal processing technologies, paving the way for enhanced manipulation of electromagnetic waves in future integrated photonic devices.

关键词： Photonic devices

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General and Offset-Resistant Physical-Layer Acknowledgement Approach for Cross-Technology Communication

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IEEE Transactions on Communications 2025年

作者： Yao, Shumin Zhao, Qinglin Zhou, MengChu Feng, Li Zhang, Peiyun Albeshri, Aiiad Macau University of Science and Technology School of Computer Science and Engineering Avenida Wei Long Taipa China Pengcheng Laboratory Department of Broadband Communication Shenzhen518066 China New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States Nanjing University of Information Science & Technology Engineering Research Center of Digital Forensics of Ministry of Education School of Computer Science Nanjing210044 China King Abdulaziz University Department of Computer Science Jeddah21481 Saudi Arabia

Cross-technology communication (CTC) enables direct communications among devices with heterogeneous wireless technologies (e.g., Bluetooth, WiFi, ZigBee, etc.), thereby reducing the cost and complexity of their interconnections. However, CTC is essentially unreliable due to the technology heterogeneity, and most existing CTC designs do not provide acknowledgment (ACK) feedback to ensure reliable data transmission. Few ACK designs are only applicable to feedback for ZigBee-WiFi pair and are vulnerable to sampling offsets that inherently exist in CTC. In this work, we propose a General and Offset-resistant Physical-layer ACK approach, called GOP-ACK, to support reliable feedback with practical considerations. Its core idea lies in encoding ACK messages with offset-resistant signal that has two benefits: 1) it can be adapted to a wide range of CTC scenarios with minimal adjustment, and 2) it can be effortlessly and robustly detected even in the presence of sampling offsets. We offer practical guidelines to tackle key deployment challenges related to signal construction, efficient and robust transmission, and effective firmware module reuse, enabling the application of GOP-ACK to specific CTC scenarios. Based on these guidelines, we implement two design cases: ZigBee-to-BLE and ZigBee-to-WiFi feedback, and propose a theoretical model to analyze their performance. We then conduct real-world experiments and extensive simulations to verify its feasibility and superiority over the state of the art, thereby enhancing the practicality of CTC greatly. © 1972-2012 IEEE.

关键词： Firmware

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Multi-agent Cooperative Games Using Belief Map Assisted Training

arXiv

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arXiv 2024年

作者： Luo, Chen Huang, Qinwei Wu, Alex B. Khan, Simon Li, Hai Qiu, Qinru Department of Electrical Engineering & Computer Science Syracuse University United States Fayetteville-Manlius High School United States Air Force Research Laboratory United States Department of Electrical Engineering & Computer Science Duke University United States

In a multi-agent system, agents share their local observations to gain global situational awareness for decision making and collaboration using a message passing system. When to send a message, how to encode a message, and how to leverage the received messages directly affect the effectiveness of the collaboration among agents. When training a multi-agent cooperative game using reinforcement learning (RL), the message passing system needs to be optimized together with the agent policies. This consequently increases the model’s complexity and poses significant challenges to the convergence and performance of learning. To address this issue, we propose the Belief-map Assisted Multi-agent System (BAMS), which leverages a neuro-symbolic belief map to enhance training. The belief map decodes the agent’s hidden state to provide a symbolic representation of the agent’s understanding of the environment and other agents’ status. The simplicity of symbolic representation allows the gathering and comparison of the ground truth information with the belief, which provides an additional channel of feedback for the learning. Compared to the sporadic and delayed feedback coming from the reward in RL, the feedback from the belief map is more consistent and reliable. Agents using BAMS can learn a more effective message passing network to better understand each other, resulting in better performance in the game. We evaluate BAMS’s performance in a cooperative predator and prey game with varying levels of map complexity and compare it to previous multi-agent message passing models. The simulation results showed that BAMS reduced training epochs by 66%, and agents who apply the BAMS model completed the game with 34.62% fewer steps on average. © 2024, CC BY.

关键词： Multi agent systems

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A Dual-View Fusion Network for Automatic Spinal Keypoint Detection in Biplane X-ray Images

A Dual-View Fusion Network for Automatic Spinal Keypoint Det...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Zhou, Dandan Guo, Lijun Zhang, Rong He, Xiuchao Wang, Qiang Wang, Jianhua Ningbo University The Faculty of Electrical Engineering and Computer Science Ningbo China The Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo China The Affiliated Hospital of Medicine School of Ningbo University The Department of Radiology Ningbo China

ISBN: (纸本)9798350337488

Accurate keypoint detection in medical images of the spine is critical for the assessment, diagnosis, treatment planning, and clinical investigation of spinal deformities. However, due to severe occlusions of spinal structures in lateral X-ray images, accurate keypoint detection can be hardly achieved in lateral X-ray images based on single-view information. Thus, methods based on both the anterior-posterior (AP) and lateral (LAT) X-ray image views have been proposed to alleviate occlusion problems and achieve better keypoint detection performance. Although some progress has been made with these dual-view methods, they do not effectively exploit a priori knowledge of the spine and hence cannot adequately account for the structural correlation of the vertebrae across views. In this paper, a new dual-view fusion network (DVFNet) framework is proposed for keypoint detection in spinal X-ray images. This framework obtains structural correlations between AP and LAT views of the spine based on a priori spine knowledge represented by high-level semantic features. Meanwhile, the proposed framework combines local and global features extracted respectively by a local subnetwork and a global subnetwork. On the one hand, the local subnetwork is constructed as an enhanced codec structure based on both the AP and LAT views. This subnetwork is trained to output local features that contain both joint semantic features of the two views and independent fine-grained features of each individual view. This scheme leads to accurate keypoint estimation locally. On the other hand, the global subnetwork utilizes a self-attention mechanism to extract view-specific global features based on either the AP view or the LAT view in order to eliminate ambiguity, and reduce confusion on keypoint locations. Further, we propose a weighted feature fusion (WFF) module for adaptive fusion of the local and global features. We evaluated the DVFNet model on a private dataset and found that our proposed metho

关键词： biplane X-ray images dual-view feature fusion spinal keypoint detection

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Structural color printing via polymer-assisted photochemical deposition

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Light(science & Applications) 2022年第5期11卷 796-807页

作者： Shinhyuk Choi Zhi Zhao Jiawei Zuo Hossain Mansur Resalat Faruque Yu Yao Chao Wang School of Electrical Computer and Energy EngineeringArizona State UniversityTempeAZ 85287USA Biodesign Center for Molecular Design and Biomimetics Arizona State UniversityTempeAZ 85287USA College of Materials Science and Engineering Key Laboratory of Advanced Functional MaterialsEducation Ministry of ChinaBeijing University of TechnologyBeijing 100124China

Structural color printings have broad applications due to their advantages of long-term sustainability,eco-friendly manufacturing,and ultra-high ***,most of them require costly and time-consuming fabrication processes from nanolithography to vacuum deposition and ***,we demonstrate a new color printing technology based on polymer-assisted photochemical metal deposition(PPD),a room temperature,ambient,and additive manufacturing process without requiring heating,vacuum deposition or *** PPD-printed silver films comprise densely aggregated silver nanoparticles filled with a small amount(estimated<20%volume)of polymers,producing a smooth surface(roughness 2.5 nm)even better than vacuum-deposited silver films(roughness 2.8 nm)at~4 nm ***,the printed composite films have a much larger effective refractive index n(~1.90)and a smaller extinction coefficient k(~0.92)than PVD ones in the visible wavelength range(400 to 800 nm),therefore modulating the surface reflection and the phase *** capability of PPD in printing both ultra-thin(~5 nm)composite films and highly reflective thicker film greatly benefit the design and construction of multilayered Fabry–Perot(FP)cavity structures to exhibit vivid and saturated *** demonstrated programmed printing of complex pictures of different color schemes at a high spatial resolution of~6.5μm by three-dimensionally modulating the top composite film geometries and dielectric spacer thicknesses(75 to 200 nm).Finally,PPD-based color picture printing is demonstrated on a wide range of substrates,including glass,PDMS,and plastic,proving its broad potential in future applications from security labeling to color displays.

关键词： composite printing silver

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Realistic Sketch Face Generation via Sketch-Guided Incomplete Restoration 29

Realistic Sketch Face Generation via Sketch-Guided Incomplet...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Liu, Zijie Gu, Chunhua Xie, Ying Zhang, Huichen Pei, Songwen University of Shanghai for Science and Technology School of Optical-Electrical and Computer Engineering Shanghai China Traffic Management Research Institute of the Ministry of Public Security Key Laboratory of Ministry of Public Security for Road Traffic Safety Wuxi China

ISBN: (纸本)9798350330717

Generating realistic sketches of human faces is an important research direction in the fields of computer vision and computer graphics. However, generating high-quality sketch faces remains challenging, especially when dealing with incomplete input sketch images. In this paper, we propose a framework based on the U-Net generative network, which progressively optimizes network performance through a three-stage training strategy. We introduce the Sketch Guidance and Completion Network (SGCN), which is capable of restoring missing features, completing blurry edges, and handling occluded regions in sketch images. By employing multiple discriminators and adversarial training strategies, we enhance the realism and preserve fine details in the generated results. Through experiments on publicly available sketch face datasets, we demonstrate significant improvements in reconstructing incomplete sketch faces using our approach. The generated images exhibit enhanced completeness, realism, and retain fine details and important facial features. Quantitative evaluations validate the effectiveness and superiority of our method. © 2023 IEEE.

关键词： Face synthesis GAN Sketch-based image synthesis

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Sparkling hot spots in perovskite solar cells under reverse bias

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ChemPhysMater 2022年第1期1卷 71-76页

作者： Weiqi Li Keqing Huang Jianhui Chang Caiqi Hu Caoyu Long Hai Zhang Xavier Maldague Biao Liu Jianqiao Meng Yuxia Duan Junliang Yang School of Physics and Electronics Central South UniversityChangsha 410083China Computer Vision and Systems Laboratory Department of Electrical and Computer EngineeringUniversitéLaval1065av.de la MédecineQuébec(QC)Canada G1V 0A6

Perovskite solar cells(PSCs)are attracting much attention and are on the way to ***,some modules are subject to reverse bias in actual fields,so it is meaningful to investigate the reverse-bias behav-ior of ***,an in-situ temperature and current measurement technique was ***,some hot spots were observed and then quickly disappeared in the reverse biased PSCs,along with the simultaneous increase in the current and local ***,the potential mechanism has been revealed and *** abnormal bulge in the perovskite film was found at the hot ***,the appearance and disappearance of hot spots were perfectly explained by band bending and tunneling current caused by ion ***-tionally,statistical analysis suggested that sparkling hot spots were related to reverse voltage and efficiencies of *** research provides a great significance for the study of PSCs under reverse bias.

关键词： Perovskite solar cells Reverse bias Hot spots Stability

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Carrying Out CNN Channel Pruning in a White Box

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IEEE Transactions on Neural Networks and Learning Systems 2023年第10期34卷 7946-7955页

作者： Zhang, Yuxin Lin, Mingbao Lin, Chia-Wen Chen, Jie Wu, Yongjian Tian, Yonghong Ji, Rongrong Xiamen University Media Analytics and Computing Laboratory Department of Artificial Intelligence School of Informatics Xiamen361005 China Youtu Laboratory Tencent Shanghai200233 China National Tsing Hua University Department of Electrical Engineering The Institute of Communications Engineering Hsinchu30013 Taiwan Peng Cheng Laboratory Shenzhen518000 China Peking University Department of Computer Science and Technology Beijing100871 China School of Informatics and the Institute of Artificial Intelligence Xiamen University Media Analytics and Computing Laboratory Department of Artificial Intelligence Xiamen361005 China

Channel pruning has been long studied to compress convolutional neural networks (CNNs), which significantly reduces the overall computation. Prior works implement channel pruning in an unexplainable manner, which tends to reduce the final classification errors while failing to consider the internal influence of each channel. In this article, we conduct channel pruning in a white box. Through deep visualization of feature maps activated by different channels, we observe that different channels have a varying contribution to different categories in image classification. Inspired by this, we choose to preserve channels contributing to most categories. Specifically, to model the contribution of each channel to differentiating categories, we develop a class-wise mask for each channel, implemented in a dynamic training manner with respect to the input image's category. On the basis of the learned class-wise mask, we perform a global voting mechanism to remove channels with less category discrimination. Lastly, a fine-tuning process is conducted to recover the performance of the pruned model. To our best knowledge, it is the first time that CNN interpretability theory is considered to guide channel pruning. Extensive experiments on representative image classification tasks demonstrate the superiority of our White-Box over many state-of-the-arts (SOTAs). For instance, on CIFAR-10, it reduces 65.23% floating point operations per seconds (FLOPs) with even 0.62% accuracy improvement for ResNet-110. On ILSVRC-2012, White-Box achieves a 45.6% FLOP reduction with only a small loss of 0.83% in the top-1 accuracy for ResNet-50. Code is available at https://***/zyxxμWhite-Box. © 2012 IEEE.

关键词： Visualization

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