When AI-driven detection underperforms, the instinct is to tune the algorithm, retrain the model or push the vendor for a ...
Designing high-performance catalysts is essential for cleaner energy technologies, but the behavior of multi-element modern ...
Better simulations of raindrop formation could help improve climate and weather models. This newsletter rocks. Get the most ...
PM IST Pinarayi Vijayan alleged that Muslims had been living in these areas for many years and accused the Karnataka government of adopting the North Indian bulldozer justice model. Gazi Abbas Shahid ...
Abstract: Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interest and touches on many important applications ...
Abstract: The mining of network sensitive information is of great significance for understanding the social stability of the network. Obtaining the network public opinion of sensitive information is ...
ABSTRACT: With the rapid expansion of the new energy vehicle (NEV) market, charging and battery swapping have emerged as the two principal energy replenishment modes, and differences in consumer ...
Biterm Topic Model (BTM) is a word co-occurrence based topic model that learns topics by modeling word-word co-occurrences patterns (e.g., biterms). (In constrast, LDA and PLSA are word-document ...
Dynamic Topic Modeling (DTM)(Blei and Lafferty 2006) is an advanced machine learning technique for uncovering the latent topics in a corpus of documents over time. The goal of this project is to ...
Recent advances in few-shot learning have demonstrated the potential of prompt-based techniques with pre-trained models, eliminating the need for extensive fine-tuning. However, challenges such as ...
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