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检索条件"机构=Shanghai Key Lab of Intelligent Information Processing and School of Computer Science"
1784 条 记 录,以下是31-40 订阅
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Double-Mix-Net: A Multimodal Music Emotion Recognition Network with Multi-layer Feature Mixing  10th
Double-Mix-Net: A Multimodal Music Emotion Recognition Netwo...
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10th Conference on Sound and Music Technology, CSMT 2023
作者: Li, Peilin Chen, Kairan Wei, Weixin Zhao, Jiahao Li, Wei School of Computer Science and Technology Fudan University Shanghai Shanghai200438 China Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai Shanghai200433 China
Computational music emotion recognition (MER) is an important task that aims to recognize emotional content in music tracks. Understanding the emotional content of music can help tailor therapeutic interventions to sp... 详细信息
来源: 评论
Audio-Driven Identity Manipulation for Face Inpainting  24
Audio-Driven Identity Manipulation for Face Inpainting
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32nd ACM International Conference on Multimedia, MM 2024
作者: Sun, Yuqi Lin, Qing Tan, Weimin Yan, Bo Shanghai Key Laboratory of Intelligent Information Processing School of Computer Science Fudan University Shanghai China Singapore Nanyang Technological University Singapore
Recent advances in multimodal artificial intelligence have greatly improved the integration of vision-language-audio cues to enrich the content creation process. Inspired by these developments, in this paper, we first... 详细信息
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Mixture of Experts for Audio-Visual Learning  38
Mixture of Experts for Audio-Visual Learning
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38th Conference on Neural information processing Systems, NeurIPS 2024
作者: Cheng, Ying Li, Yang He, Junjie Feng, Rui School of Computer Science Fudan University China Shanghai Key Laboratory of Intelligent Information Processing China Shanghai Collaborative Innovation Center of Intelligent Visual Computing China
With the rapid development of multimedia technology, audio-visual learning has emerged as a promising research topic within the field of multimodal analysis. In this paper, we explore parameter-efficient transfer lear...
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SPIKING CONVOLUTIONAL NEURAL NETWORKS FOR TEXT CLASSIFICATION  11
SPIKING CONVOLUTIONAL NEURAL NETWORKS FOR TEXT CLASSIFICATIO...
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11th International Conference on Learning Representations, ICLR 2023
作者: Lv, Changze Xu, Jianhan Zheng, Xiaoqing School of Computer Science Fudan University Shanghai 200433 China Shanghai Key Laboratory of Intelligent Information Processing
Spiking neural networks (SNNs) offer a promising pathway to implement deep neural networks (DNNs) in a more energy-efficient manner since their neurons are sparsely activated and inferences are event-driven. However, ... 详细信息
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A Power Consumption Forecasting Method Based on Knowledge Embedding Under the Influence of the COVID-19 Pandemic  8th
A Power Consumption Forecasting Method Based on Knowledge E...
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8th China National Conference on Big Data and Social Computing, BDSC 2023
作者: Zhang, Qifan Cao, Xiu Shanghai Key Lab of Intelligent Information Processing Department of Computer Science Fudan University Shanghai200433 China
This paper addresses the new challenges of power consumption forecasting under the COVID-19 pandemic by proposing a knowledge embedding-based method (PEC-19). This method constructs a multi-source enterprise knowledge... 详细信息
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CPT: a pre-trained unbalanced transformer for both Chinese language understanding and generation
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science China(information sciences) 2024年 第5期67卷 43-55页
作者: Yunfan SHAO Zhichao GENG Yitao LIU Junqi DAI Hang YAN Fei YANG Zhe LI Hujun BAO Xipeng QIU School of Computer Science Fudan University Shanghai Key Laboratory of Intelligent Information Processing Fudan University Zhejiang Lab
In this paper, we take the advantage of previous pre-trained models(PTMs) and propose a novel Chinese pre-trained unbalanced transformer(CPT). Different from previous Chinese PTMs, CPT is designed to utilize the share... 详细信息
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Calibrating the Confidence of Large Language Models by Eliciting Fidelity
Calibrating the Confidence of Large Language Models by Elici...
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2024 Conference on Empirical Methods in Natural Language processing, EMNLP 2024
作者: Zhang, Mozhi Huang, Mianqiu Shi, Rundong Guo, Linsen Peng, Chong Yan, Peng Zhou, Yaqian Qiu, Xipeng School of Computer Science Fudan University China Shanghai Key Laboratory of Intelligent Information Processing Fudan University China Meituan China
Large language models optimized with techniques like RLHF have achieved good alignment in being helpful and harmless. However, post-alignment, these language models often exhibit overconfidence, where the expressed co... 详细信息
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QS-Craft: Learning to Quantize, Scrabble and Craft for Conditional Human Motion Animation  16th
QS-Craft: Learning to Quantize, Scrabble and Craft for Co...
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16th Asian Conference on computer Vision, ACCV 2022
作者: Hong, Yuxin Qian, Xuelin Luo, Simian Guo, Guodong Xue, Xiangyang Fu, Yanwei School of Data Science and MOE Frontiers Center for Brain Science Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai China School of Computer Science Shanghai Key Lab of Intelligent Information Processing Fudan University Shanghai China Department of CSEE West Virginia University Morgantown United States
This paper studies the task of conditional Human Motion Animation (cHMA). Given a source image and a driving video, the model should animate the new frame sequence, in which the person in the source image should perfo... 详细信息
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UNRAVELING THE ENIGMA OF DOUBLE DESCENT: AN IN-DEPTH ANALYSIS THROUGH THE LENS OF LEARNED FEATURE SPACE  12
UNRAVELING THE ENIGMA OF DOUBLE DESCENT: AN IN-DEPTH ANALYSI...
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12th International Conference on Learning Representations, ICLR 2024
作者: Gu, Yufei Zheng, Xiaoqing Aste, Tomaso School of Computer Science Fudan University China Shanghai Key Laboratory of Intelligent Information Processing China Department of Computer Science University College London United Kingdom
Double descent presents a counter-intuitive aspect within the machine learning domain, and researchers have observed its manifestation in various models and tasks. While some theoretical explanations have been propose... 详细信息
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SCSGNet: Spatial-Correlated and Shape-Guided Network for Breast Mass Segmentation  48
SCSGNet: Spatial-Correlated and Shape-Guided Network for Bre...
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48th IEEE International Conference on Acoustics, Speech and Signal processing, ICASSP 2023
作者: Li, Qingqiu Xu, Jilan Yuan, Runtian Zhang, Yuejie Feng, Rui Fudan University School of Academy for Engineering and Technology Shanghai China Fudan University School of Computer Science Shanghai Key Lab of Intelligent Information Processing Shanghai China
Automatic and accurate breast mass segmentation plays a crucial role in the early diagnosis of breast cancer. However, it has been a challenging task for two main reasons: (1) Breast masses are diverse;and (2) The bou... 详细信息
来源: 评论