Transformer-based Models
PulseAugur coverage of Transformer-based Models — every cluster mentioning Transformer-based Models across labs, papers, and developer communities, ranked by signal.
1 day(s) with sentiment data
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LeapTS framework reframes time series forecasting as adaptive scheduling
Researchers have introduced LeapTS, a new framework that reframes time series forecasting as an adaptive scheduling problem. This approach moves away from fixed mappings to a dynamic process where a hierarchical control…
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AI models learn physics of motion-to-radar spectrograms, study finds
Researchers have developed a new framework to assess whether data-driven models that convert motion capture data to radar spectrograms are learning the underlying physics. This framework uses two metrics to measure the …
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Directed Social Regard: Surfacing Targeted Advocacy, Opposition, Aid, Harms, and Victimization in Online Media
Researchers have developed a new approach called Directed Social Regard (DSR) to analyze sentiment in online text. Unlike traditional sentiment analysis tools that provide a single positive, neutral, or negative score, …
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Indonesian students show positive sentiment towards AI in higher education
A new study analyzed Indonesian student sentiment regarding AI adoption in higher education, comparing traditional machine learning with Transformer-based deep learning models. The research utilized a dataset of 2,295 l…