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Titlebook: Advances in Knowledge Discovery and Data Mining; 28th Pacific-Asia Co De-Nian Yang,Xing Xie,Jerry Chun-Wei Lin Conference proceedings 2024

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發(fā)表于 2025-3-23 12:52:00 | 只看該作者
Human Reproduction: Religious Perspectivesing both fine-tuning and p-tuning to CMed-GPT, we lowered the PPL from 8.44 to 7.35. This study not only confirms the exceptional performance of the CMed-GPT model in generating Chinese biomedical text but also highlights the advantages of p-tuning over traditional fine-tuning with prefix prompts. F
12#
發(fā)表于 2025-3-23 16:02:53 | 只看該作者
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發(fā)表于 2025-3-23 21:35:18 | 只看該作者
https://doi.org/10.1007/978-1-4613-3813-0enowned standard benchmarks for the image retrieval task. The results demonstrate that SEE consistently enhances the performance of conventional methods when integrated with them, setting a new benchmark for deep metric learning performance across all settings. Particularly, the proposed method reve
14#
發(fā)表于 2025-3-23 22:43:02 | 只看該作者
15#
發(fā)表于 2025-3-24 04:48:50 | 只看該作者
Clinical Management of Melanomacation efficiency by filtering out redundant local updates based on the estimation of agent utilities. A centralized aggregator rectifies these estimations conditioned on global information to improve cooperation and reduce non-. impact by maximizing the composite system objectives. For a comprehens
16#
發(fā)表于 2025-3-24 07:15:56 | 只看該作者
17#
發(fā)表于 2025-3-24 12:01:48 | 只看該作者
The development of group memory therapy,ions. We adopt knowledge distillation for our bi-CryptoNets by transferring representations from a well-trained teacher neural network. Empirical studies show the effectiveness and decrease of inference latency for our bi-CryptoNets.
18#
發(fā)表于 2025-3-24 18:02:02 | 只看該作者
19#
發(fā)表于 2025-3-24 21:15:28 | 只看該作者
20#
發(fā)表于 2025-3-24 23:28:03 | 只看該作者
Treatment Effect Estimation Under Unknown Interference978-3-662-31494-4
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