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pro vyhledávání: '"Jain, Hemang"'
Toxicity identification in online multimodal environments remains a challenging task due to the complexity of contextual connections across modalities (e.g., textual and visual). In this paper, we propose a novel framework that integrates Knowledge D
Externí odkaz:
http://arxiv.org/abs/2411.12174
Autor:
Govil, Priyanshul, Jain, Hemang, Bonagiri, Vamshi Krishna, Chadha, Aman, Kumaraguru, Ponnurangam, Gaur, Manas, Dey, Sanorita
Large Language Models (LLMs) often inherit biases from the web data they are trained on, which contains stereotypes and prejudices. Current methods for evaluating and mitigating these biases rely on bias-benchmark datasets. These benchmarks measure b
Externí odkaz:
http://arxiv.org/abs/2402.14889