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It will be viewed as the standard model of the task and, hence, will likely be a source of a great deal of future research.
These inputs can be de-emphasized, and, in turn, a new, improved, model of the task created.
As a model of the task is learned, the model is simultaneously extended to create task-specific predictions of the future values of inputs.
Task decomposition through menu selection is a powerful technique for simplifying and guiding plan development, but can backfire if the decomposition does not match the user's mental model of the task.
The upper part of Figure 3 shows the RDF model of the task context model, and the lower part shows the task context data that are generated according to the task context model.
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The results prove the effectiveness of the proposed model on the task of answer selection in CQA.
It also outperforms an n-gram language model on the task of pitch accent detection.
Similarly, in Cohen et al.'s (1990) connectionist model of the Stroop task, "task demand" units exert a unidirectional influence over the activation levels of competing word reading and color naming pathways (but see Cohen and Huston 1994).
Finally, an exploratory comparison between the models on the task of continuous speech recognition was made.
We show that, using the same features, log-linear dependency grammar models trained using CE can drastically outperform EM-trained generative models
An ACT-R model of the tasks successfully predicted behavioral performance and BOLD responses.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com