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Proceedings of the 38th International Conference on Neural Information processing Systems

作者： Zejia Weng Xitong Yang Zhen Xing Zuxuan Wu Yu-Gang Jiang Shanghai Key Lab of Intell. Info. Processing School of CS Fudan University and Shanghai Collaborative Innovation Center of Intelligent Visual Computing Department of Computer Science University of Maryland

ISBN: (纸本)9798331314385

Video diffusion models are able to generate high-quality videos by learning strong spatial-temporal priors on large-scale datasets. In this paper, we aim to investigate whether such priors derived from a generative process are suitable for video recognition, and eventually joint optimization of generation and recognition. Building upon Stable Video Diffusion, we introduce GenRec, the first unified framework trained with a random-frame conditioning process so as to learn generalized spatial-temporal representations. The resulting framework can naturally supports generation and recognition, and more importantly is robust even when visual inputs contain limited information. Extensive experiments demonstrate the efficacy of GenRec for both recognition and generation. In particular, GenRec achieves competitive recognition performance, offering 75.8% and 87.2% accuracy on SSV2 and K400, respectively. GenRec also performs the best on class-conditioned image-to-video generation, achieving 46.5 and 49.3 FVD scores on SSV2 and EK-100 datasets. Furthermore, GenRec demonstrates extraordinary robustness in scenarios that only limited frames can be observed. Code will be available at https://***/wengzejia1/GenRec.

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A Broadband Circularly Polarized Filtering Patch Antenna with Stacked Structure

A Broadband Circularly Polarized Filtering Patch Antenna wit...

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International Conference on Computer Science and Network Technology (ICCSNT)

作者： Jinping Zhang Dmitry Kholodnyak Zhixiang Huang Yingsong Li College of Information and Communication Engineering Harbin Engineering University Harbin China Department of Microwave Electronics Saint Petersburg Electrotechnical University Russia Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

ISBN: (数字)9798350350791

ISBN: (纸本)9798350350807

A double-layer stacked patch filtering antenna with broadband circular polarization performance is proposed in this paper. The main patch consists of a corner-truncated square patch with two shorting pins. The designed two shorting pins are located in the main patch and the upper stacked patch structure are introduced and designed, which can gain two radiation nulls for realizing the filtering effect of the proposed antenna. The circularly polarized (CP) operation is realized by corner-truncated square patch. In addition, to increase the axial ratio (AR) bandwidth, a rectangular slot is carved on the ground plane. The simulated results indicate that the researched antenna can provide the impedance bandwidth of 20.58% (2.68-3.29 GHz) and AR bandwidth of 9.5% (2.80-3.08 GHz). Moreover, The average realized gain of the simulation is 6.48 dBic over bandwidth.

关键词： Radio frequency Polarization Filtering Simulation Patch antennas Bandwidth Pins Broadband communication Broadband antennas Antennas

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pp2-linear codes: rank and kernel

arXiv

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arXiv 2022年

作者： Shi, Minjia Wang, Shukai Li, Xiaoxiao Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematics Sciences Anhui University Anhui Hefei China

A code C is called pp2-linear if it is the Gray image of a pp2-additive code, where p > 2 is prime. In this paper, the rank and the dimension of the kernel of pp2-linear codes are studied. Two bounds of the rank of a Z3Z9-linear code and the dimension of the kernel of a pp2-linear code are given, respectively. For each value of these bounds, we give detailed construction of the corresponding code. Finally, pairs of rank and the dimension of the kernel of 39-linear codes are also *** Codes 94B05 © 2022, CC0.

关键词： Additives

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Multi-Layer Visual Perception for No-Reference Image Quality Assessment 6

Multi-Layer Visual Perception for No-Reference Image Quality...

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6th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2023

作者： Qi, Junwei Wang, Yingzhen Wang, Qingchun Li, Yingsong College of Computer Science and Technology Harbin Engineering University Harbin150001 China College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Shanghai Yanding Information Technology Co. Ltd. Shanghai201210 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui Hefei230601 China

ISBN: (纸本)9798350399059

In this work, we propose a no-reference image quality evaluation approach, aiming to solve the problem that the traditional convolutional neural network is insufficient to express the global information of the image. Therefore, in order to make the captured image features have the coherence of global context information, we combine a Transformer structure widely used in NLP (natural language processing) with the traditional CNN to realize the attention mechanism in the human visual perception characteristics. Firstly, the self-attention mechanism of Transformer is used to learn the global representation of the image from the multi-layer features extracted from different levels of CNN. Additionally, to forecast the ultimate image quality score, the global and local attributes are combined. Finally, the proposed algorithm is evaluated on three public datasets commonly used in CSIQ [1], TID2013 [2] and LIVE [3]. Compared with eight traditional no-reference image quality evaluation algorithms and five methods based on deep learning, the proposed algorithm achieves competitive results. © 2023 IEEE.

关键词： Convolutional neural networks

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Design of Ultra-Wideband Terahertz Wavelength Division Multiplexer Based on Inverse Design Algorithm

Design of Ultra-Wideband Terahertz Wavelength Division Multi...

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2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Xiao, Zhicheng Song, Kaihong Fang, Ming The Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Anhui Hefei230039 China Anhui Province Key Laboratory of Target Recognition and Feature Extraction Anhui Luan237000 China The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China State Key Laboratory of Millimeter Waves Southeast University Nanjing214135 China

ISBN: (纸本)9781665452366

Integrated photonic gadgets play a key function in lots of fields. The process of designing silicon optical devices mostly relies on experience to manually adjust the subtle parameters, which is laborious and ineffective. The proposed inverse design algorithms can simplify the design process of silicon optical devices, improve the design efficiency, and realize multifunctional compact devices. In this paper, two inverse design based methods are proposed to design terahertz band wavelength division multiplexer(WDM). One is based on topology optimization to design a 4-channel ultra-wideband WDM and the other employs a direct binary search technique to create a 3-channel ultra-wideband terahertz WDM, both of which have high transmission, low interference and high integration. Multifunctional photonics devices are predicted to be increasingly used in modern photonic integrated circuits due to these advantages. © 2022 IEEE.

关键词： Optical devices

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Broadband infrared absorber based on metamaterial

Broadband infrared absorber based on metamaterial

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2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Kang, Meijun Feng, Jian Rong, Mandi Fang, Ming The Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Anhui Hefei230039 China Anhui Province Key Laboratory of Target Recognition and Feature Extraction Anhui Luan237000 China The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China State Key Laboratory of Millimeter Waves Southeast University Nanjing214135 China

ISBN: (纸本)9781665452366

In order to obtain an absorber with high absorption efficiency and wide absorption band, a metamaterial structure by Metal-ENZ-Insulator-Metal (MEIM) is designed, and its absorption in the 130-230 THz band is calculated using the simulation software frequency-domain solver. By rotating the upper metal layer and the lower hollow layer, the simulation results can be slightly disturbed. In addition, the introduction of the epsilon-near-zero (ENZ) media will also affect the bandwidth and absorption of the absorber. Therefore, the high absorption and wide bandwidth of the absorber are achieved by the size of the structure, the rotation angle of the corresponding structure,and the clever application of the ITO layer. © 2022 IEEE.

关键词： Metamaterials

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Improving Event-Level Financial Sentiment Analysis with Retrieval-Augmented Multipath Chain-of-Thought Prompting 12th

Improving Event-Level Financial Sentiment Analysis with Ret...

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12th CCF Conference on BigData, BigData 2024

作者： Zhang, Yiming Ao, Xiang Yu, Guoxin He, Qing Henan Institute of Advanced Technology Zhengzhou University Zhengzhou450002 China Beijing100190 China Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing100190 China

ISBN: (纸本)9789819610235

Event-level Financial Sentiment Analysis (EFSA) aims to extract all the quintuples containing five sentiment elements from a given financial news text, which has gained prominence as an emerging domain recently. The present study utilizes a 4-hop Chain-of-Thought (CoT) prompting based on LLMs to predict sentiment elements in a fixed order, which neglects the interdependencies among the sentiment elements within a quintuple. Inspired by recent multi-view prompting (MvP) and CoT ideas, we propose a novel framework termed Retrieval-Augmented Multipath Chain-of-Thought (RMP-CoT) that aggregates quintuples generated by LLMs through different reasoning paths, leveraging a retrieval-augmented mechanism. Specifically, RMP-CoT integrates different element orders into CoT prompting to guide LLMs in generating multiple sentiment quintuples through the utilization of retrieval-augmented mechanism, and then selects the most plausible quintuples by voting. To investigate the effectiveness of our framework, we conduct extensive experiments on four benchmark tasks of EFSA. RMP-CoT pushes the state-of-the-art by over 6% F1 on the EFSA task and also performs quite effectively on the other sub-tasks of EFSA. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Chain-of-Thought Event-level Sentiment Analysis Financial Sentiment Analysis

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Fact-Preserved Personalized News Headline Generation

Fact-Preserved Personalized News Headline Generation

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IEEE International Conference on Data Mining (ICDM)

作者： Zhao Yang Junhong Lian Xiang Ao Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing China University of Chinese Academy of Sciences Beijing China Institute of Intelligent Computing Technology Suzhou CAS

Personalized news headline generation, aiming at generating user-specific headlines based on readers’ preferences, burgeons a recent flourishing research direction. Existing studies generally inject a user interest embedding into an encoder-decoder headline generator to make the output personalized, while the factual consistency of headlines is inadequate to be verified. In this paper, we propose a framework Fact-Preserved Personalized News Headline Generation (short for FPG), to prompt a tradeoff between personalization and consistency. In FPG, the similarity between the candidate news to be exposed and the historical clicked news is used to give different levels of attention to key facts in the candidate news, and the similarity scores help to learn a fact-aware global user embedding. Besides, an additional training procedure based on contrastive learning is devised to further enhance the factual consistency of generated headlines. Extensive experiments conducted on a real-world benchmark PENS 1 validate the superiority of FPG, especially on the tradeoff between personalization and factual consistency. 1 https://***/***

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Low Coupling Sparse Array Based on Uniform Linear Array Fitting Method

Low Coupling Sparse Array Based on Uniform Linear Array Fitt...

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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Yichang Yao Yingsong Li Liping Li Nikola Zlatanov College of Information and Communication Engineering Harbin Engineering University Harbin China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Faculty of Computer and Engineering Sciences Innopolis University Innopolis Russia

ISBN: (数字)9798350384437

ISBN: (纸本)9798350384444

In order to solve the problem that traditional sparse arrays only emphasize high degrees of freedom and ignore low coupling, uniform array fitting method can design arrays with low coupling. However, the existing array coupling based on uniform array fitting method still has room for decline, and the value of weight function is not the minimum, so the performance of array DOA estimation needs to be further optimized. Therefore, based on the uniform matrix fitting method, a uniform matrix fitting 6-base-layer array is designed. By extending the spacing of each subarray of the uniform subarray in the base layer, the number of small array element spacing pairs in the differential cooperative array is reduced, and the coupling between the elements of the whole sparse array is reduced as a whole. The performance of DOA estimation of the designed array is simulated and analyzed by using spatial smoothing multiple signal classification algorithm.

关键词： Couplings Mutual coupling Direction-of-arrival estimation Smoothing methods Simulation Fitting Estimation

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Hyperbolic Hierarchical Knowledge Graph Embeddings for Link Prediction in Low Dimensions

arXiv

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arXiv 2022年

作者： Zheng, Wenjie Wang, Wenxue Zhao, Shu Qian, Fulan Nanjing University of Science and Technology China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

Knowledge graph embeddings (KGE) have been validated as powerful methods for inferring missing links in knowledge graphs (KGs) that they typically map entities into Euclidean space and treat relations as transformations of entities. Recently, some Euclidean KGE methods have been enhanced to model semantic hierarchies commonly found in KGs, improving the performance of link prediction. To embed hierarchical data, hyperbolic space has emerged as a promising alternative to traditional Euclidean space, offering high fidelity and lower memory consumption. Unlike Euclidean, hyperbolic space provides countless curvatures to choose from. However, it is difficult for existing hyperbolic KGE methods to obtain the optimal curvature settings manually, thereby limiting their ability to effectively model semantic hierarchies. To address this limitation, we propose a novel KGE model called Hyperbolic Hierarchical KGE (HypHKGE). This model introduces attention-based learnable curvatures for hyperbolic space, which helps preserve rich semantic hierarchies. Furthermore, to utilize the preserved hierarchies for inferring missing links, we define hyperbolic hierarchical transformations based on the theory of hyperbolic geometry, including both inter-level and intra-level modeling. Experiments demonstrate the effectiveness of the proposed HypHKGE model on the three benchmark datasets (WN18RR, FB15K-237, and YAGO3-10). The source code will be publicly released at https://***/wjzheng96/HypHKGE. Copyright © 2022, The Authors. All rights reserved.

关键词： Knowledge graph

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