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Evidence record 16128 · automatically gathered

DeBERTa-Sentinel: Toward Transparent and Trustworthy Detection of AI-Generated Text

The rapid spread of large language models (LLMs) across the web raises concerns about misinformation, academic integrity, automated content manipulation, and risks to vulnerable online communities. Existing transformer-based detectors, such as GPT-Sentinel, show promise but struggle to generalize to diverse model outputs and paraphrasing attacks, limiting their role in building trustworthy web ecosystems. This work introduces DeBERTa-Sentinel, a responsible AI-generated text detection framework

Record details

Published: 2 August 2026
Source: arXiv cs.CL (ethics-relevant NLP)
Category: Research
Topics: Misinformation · Transparency
Retrieved: 4 August 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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Shared topic: Misinformation · Shared topic: Transparency

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How to cite this record

ethics.ai (2 August 2026), “DeBERTa-Sentinel: Toward Transparent and Trustworthy Detection of AI-Generated Text,” evidence record 16128, https://ethics.ai/record/16128 (originally published by arXiv cs.CL (ethics-relevant NLP)).

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