Search alternatives:
learning context » learning contexts (Expand Search)
context decrease » content decreased (Expand Search), content increase (Expand Search), contract decreases (Expand Search)
marked decrease » marked increase (Expand Search)
large decrease » larger decrease (Expand Search), large increases (Expand Search), large degree (Expand Search)
learning context » learning contexts (Expand Search)
context decrease » content decreased (Expand Search), content increase (Expand Search), contract decreases (Expand Search)
marked decrease » marked increase (Expand Search)
large decrease » larger decrease (Expand Search), large increases (Expand Search), large degree (Expand Search)
-
1
Data Sheet 1_Emotional prompting amplifies disinformation generation in AI large language models.docx
Published 2025“…Introduction<p>The emergence of artificial intelligence (AI) large language models (LLMs), which can produce text that closely resembles human-written content, presents both opportunities and risks. …”
-
2
-
3
-
4
-
5
Convolutional vs RNN context encoder
Published 2025“…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
-
6
-
7
Regions of significance for the simple block slopes on proportion of risky decisions as a function of past-month nonsuicidal self-injury (NSSI) and task.
Published 2024Subjects: “…simulated socioemotional contexts…”
-
8
Demographic and self-injury history characteristics for the sample.
Published 2024Subjects: “…simulated socioemotional contexts…”
-
9
Bivariate correlations and descriptive statistics for study variables.
Published 2024Subjects: “…simulated socioemotional contexts…”
-
10
Simple block slopes on proportion of risky decisions based on task.
Published 2024Subjects: “…simulated socioemotional contexts…”
-
11
-
12
-
13
Geometric manifold comparison visualization
Published 2025“…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
-
14
Hyperparameter ranges
Published 2025“…In this work, we propose to use a generative non-linear deep learning model, a disentangled variational autoencoder (DSVAE), that factorizes out window-specific (context) information from timestep-specific (local) information. …”
-
15
-
16
-
17
-
18
A novel RNN architecture to improve the precision of ship trajectory predictions
Published 2025“…This type of monitoring often relies on the use of navigation systems such as the Automatic Identification System (AIS). AIS data has been used to support the defense teams when identifying equipment defects, locating suspicious activity, ensuring ship collision avoidance, and detecting hazardous events. …”
-
19
-
20