亚麻制品
发表于 2025-3-23 11:10:18
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外向者
发表于 2025-3-23 15:58:56
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Ordeal
发表于 2025-3-23 20:31:47
Sanjay W. Pimplikar,Anupama Suryanarayanar complicated training strategies, . curates a smaller yet more feature-balanced data subset, fostering the development of spuriousness-robust models. Experimental validations across key benchmarks demonstrate that . competes with or exceeds the performance of leading methods while significantly red
Proclaim
发表于 2025-3-23 22:49:58
Mathew A. Sherman,Sylvain E. Lesnétruggle to accurately estimate uncertainty when processing inputs drawn from the wild dataset. To address this issue, we introduce a novel instance-wise calibration method based on an energy model. Our method incorporates energy scores instead of softmax confidence scores, allowing for adaptive cons
不遵守
发表于 2025-3-24 03:39:57
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CROW
发表于 2025-3-24 07:59:30
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excrete
发表于 2025-3-24 14:04:04
Alzheimer: 100 Years and Beyondth the proposed encoder layer and DyHead, a new dynamic TAD model, DyFADet, achieves promising performance on a series of challenging TAD benchmarks, including HACS-Segment, THUMOS14, ActivityNet-1.3, Epic-Kitchen 100, Ego4D-Moment QueriesV1.0, and FineAction. Code is released to ..
panorama
发表于 2025-3-24 17:42:12
,Teddy: Efficient Large-Scale Dataset Distillation via Taylor-Approximated Matching,ents to a . one. On the other hand, rather than repeatedly training a novel model in each iteration, we unveil that employing a pre-cached pool of . models, which can be generated from a . base model, enhances both time efficiency and performance concurrently, particularly when dealing with large-sc
Instinctive
发表于 2025-3-24 22:42:35
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睨视
发表于 2025-3-25 02:09:00
,-VTON: Dynamic Semantics Disentangling for Differential Diffusion Based Virtual Try-On,to handle multiple degradations independently, thereby minimizing learning ambiguities and achieving realistic results with minimal overhead. Extensive experiments demonstrate that .-VTON significantly outperforms existing methods in both quantitative metrics and qualitative evaluations, demonstrati