Grasping
发表于 2025-3-23 10:36:19
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periodontitis
发表于 2025-3-23 14:35:43
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把…比做
发表于 2025-3-23 19:37:28
L. Claes,C. Burri,R. Neugebauer,U. Gruberstems based on social network graphs. Combining social network graphs with user-item graphs can capture dynamic preference features, achieving more accurate recommendations. However, user behavioral data often contains noise and is sparse, which may result in suboptimal model performance. To address
maculated
发表于 2025-3-24 00:41:30
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Stagger
发表于 2025-3-24 05:41:33
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resistant
发表于 2025-3-24 07:02:09
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incision
发表于 2025-3-24 12:16:18
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VALID
发表于 2025-3-24 16:18:54
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宣誓书
发表于 2025-3-24 22:55:41
L. Claes,C. Burri,R. Neugebauer,U. Grubere opportunity to fully leverage pre-trained knowledge from single-pass models. This practice leads to increased training cost and complexity. In this paper, we propose a unified two-pass decoding framework comprising three core modules: a pre-trained Visual Encoder, a pre-trained Draft Decoder, and
EVEN
发表于 2025-3-24 23:38:23
L. Claes,C. Burri,R. Neugebauer,U. Gruberations from text. This task has become challenging when dealing with complex sentences that encompass overlapping sub-events. To address this issue, we propose a novel ontology-aware neural approach for extracting overlapping events. Our approach consists of an Ontology-Aware Semantic Encoder (OASE)