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The purpose of this model is to provide an indication of whether a given text in Bulgarian potentially represents automatically generated texts with the models GPT-2 and ChatGPT. It outputs a probability label for the class "0" (the text is written by a HUMAN) and for the class "1" (the text has been potentially generated by a GPT-2 or the CahtGPT model). It can be combined with models, recognizing untrue information, misinformation, or disinformation, in order to identify textual deepfakes. The model has been trained on Bulgarian social media messages, automatically generated by GPT-2 and ChatGPT, starting from examples of Bulgarian social media messages. It uses a tfidf vectorizer, also supplied. The model achieves these values: Accuracy: 0.8860630722278738 Precision: 0.87 Recall: 0.9024896265560166 F1-score: 0.8859470468431772
This model was created within the TRACES project (https://traces.gate-ai.eu/), which has indirectly received funding from the European Union's Horizon 2020 research and innovation action programme, via the AI4Media Open Call #1 issued and executed under the AI4Media project (Grant Agreement no. 951911).
ChatGPT, textual deepfakes, GPT-2
ChatGPT, textual deepfakes, GPT-2
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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