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Enhancing Multi-Agent Systems via Reinforcement Learning with LLM-based Planner and Graph-based Policy
TBD
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CycleFlow: Leveraging Cycle Consistency in Flow Matching for Speaker Style Adaptation
Voice Conversion (VC) aims to convert the style of a source speaker, such as timbre and pitch, to the style of any target speaker while …
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CycleFlow: Leveraging Cycle Consistency in Flow Matching for Speaker Style Adaptation
Graph Contrastive Learning with Decoupled Augmentation
Graph contrastive learning based on augmentation strategies has recently demonstrated remarkable performance. Existing methods …
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Graph Contrastive Learning with Decoupled Augmentation
Homogeneous Graph Extraction: An Approach to Learning Heterogeneous Graph Embedding
Heterogeneous Graph Neural Networks (HGNNs) aim to embed rich structural and semantic information of heterogeneous graphs into …
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Homogeneous Graph Extraction: An Approach to Learning Heterogeneous Graph Embedding
PointActionCLIP: Preventing Transfer Degradation in Point Cloud Action Recognition with a Triple-Path CLIP
Directly applying CLIP to point cloud action recognition can cause severe accuracy collapse. In this paper, we propose PointActionCLIP, …
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PointActionCLIP: Preventing Transfer Degradation in Point Cloud Action Recognition with a Triple-Path CLIP
VisTa: Visual-contextual and Text-augmented Zero-shot Object-level OOD Detection
As object detectors are increasingly deployed as black-box cloud services or pre-trained models with restricted access to the original …
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VisTa: Visual-contextual and Text-augmented Zero-shot Object-level OOD Detection
ACCon: Angle-Compensated Contrastive Regularizer for Deep Regression
In deep regression, capturing the relationship among continuous labels in feature space is a fundamental challenge that has attracted …
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ACCon: Angle-Compensated Contrastive Regularizer for Deep Regression
RUNA: Object-level Out-of-Distribution Detection via Regional Uncertainty Alignment of Multimodal Representations
TBD
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RUNA: Object-level Out-of-Distribution Detection via Regional Uncertainty Alignment of Multimodal Representations
Cocktait:Chunk-AdaptiveMixed-PrecisionOuanization for Long-Context LLM inference
TBD
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Incremental Label Distribution Learning With Scalable Graph Convolutional Networks
Label Distribution Learning (LDL) is an effective approach for handling label ambiguity, as it can analyze all labels at once and …
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Incremental Label Distribution Learning With Scalable Graph Convolutional Networks