↩ ↩2 Project Gungnir, the world 1st LLM for time-series multitask modeling, will meet you soon. 🚀 Missing values and variable lengths in your datasets? Hard to perform multitask learning with your time series? Not problems no longer. We'll open application for public beta test ...
Jan 6, 2023 benchmarks [Performance] Fused sampling with compaction (#5924) Jul 20, 2023 cmake [Build] Organize cmake file (Fixed) (#7715) Aug 18, 2024 conda/dgl [release] bump version to 2.5 for nightly (#7762) Sep 2, 2024 ...
M. The power of successive relearning: improving performance on course exams and long-term retention. Educ. Psychol. Rev. 25, 523–548 (2013). Article Google Scholar Morris, P. E. & Fritz, C. O. The name game: using retrieval practice to improve the learning of names. J. Exp. ...
(2) What deep learning model architectures were included in reported studies? (3) How were these deep learning model architectures used in reported studies? (4) What classification performance has been achieved? (5) What were the mainstreams and limitations of reported studies?Materials...
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Multitask Learning is an approach to inductive transfer that improves generalization by using the domain information contained in the training signals of related tasks as an inductive bias. It does this by learning tasks in parallel while using a shared.
It is challenging to obtain extensive annotated data for under-resourced languages, so we investigate whether it is beneficial to train models using multi-task learning. Sentiment analysis and offensive language identification share similar discourse properties. The selection of these tasks is motivated ...
Finally, we evaluate the proposed framework by analyzing several multi-task datasets, and the experimental results demonstrate that our FCL3 model can achieve better performance than most lifelong learning frameworks, even batch clustered multi-task learning models. 展开 ...
In the pathogenicity prediction task, the pathogenicity of variants may be caused by multiple types of features. To enhance the model’s performance, we aimed to integrate these multimodal features. By incorporating the autoFE component, MAGPIE has the capability to handle the complexity of the ...
TaskDatasetModel TypeExample Keyword Spottinghey-snipsMDTCmdtc-hey-snips Speaker Verification TaskDatasetModel TypeExample Speaker VerificationVoxCeleb1/2ECAPA-TDNNecapa-tdnn-voxceleb12 Speaker Diarization TaskDatasetModel TypeExample Speaker DiarizationAMIECAPA-TDNN + AHC / SCecapa-tdnn-ami ...