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BERT-tiny-RAID

ShantanuT01

This model is used to detect AI-generated texts from the RAID dataset. The model outputs a score corresponding to the likelihood that the text is human.

Text analysis

Input Text→ Output Text

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gradient-ai-text-detector

ShantanuT01

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

Basic profile indexed · More details to follow

Text analysis

Input Text→ Output Text

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This model is a fine-tuned version of ModernBERT-large for binary classification of human-written vs. AI-generated text. It outputs a single probability, P(AI), indicating the likelihood that a given input was generated by a language model. Vanguard AI-text detector was part of the 2nd-place system at PAN-CLEF 2026's Voight-Kampff Generative AI Detection leaderboard. This model was trained on approximately 1.1 million texts from three datasets: DACTYL 2.0, LLMTrace, and MAGA-Bench. The model was evaluated against two leading open-source AI text detectors, Fakespot and Desklib, across ten benchmark datasets. Three of these (dactyl-v2.0, llm-trace-eng, maga) are in-distribution with respect to this model's training data; the remaining seven (beemo, coconuts, detectrl, dolly-cosmopedia, originalityai, realdet, uchicago) are out-of-distribution and were not seen during training.

Text analysis

Input Text→ Output Text

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Adjust monthly token usage to compare estimated API costs.

Monthly input tokens 10 MMonthly output tokens 2 M1 M = 1 million tokens · USD
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Explore AI models 3

BERT-tiny-RAID

gradient-ai-text-detector

vanguard-ai-text-detector

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