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pro vyhledávání: '"Wehner, Jan"'
Autor:
Rosati, Domenic, Wehner, Jan, Williams, Kai, Bartoszcze, Łukasz, Atanasov, David, Gonzales, Robie, Majumdar, Subhabrata, Maple, Carsten, Sajjad, Hassan, Rudzicz, Frank
Releasing open-source large language models (LLMs) presents a dual-use risk since bad actors can easily fine-tune these models for harmful purposes. Even without the open release of weights, weight stealing and fine-tuning APIs make closed models vul
Externí odkaz:
http://arxiv.org/abs/2405.14577
Autor:
Rosati, Domenic, Wehner, Jan, Williams, Kai, Bartoszcze, Łukasz, Batzner, Jan, Sajjad, Hassan, Rudzicz, Frank
Large Language Models (LLMs) are often trained with safety guards intended to prevent harmful text generation. However, such safety training can be removed by fine-tuning the LLM on harmful datasets. While this emerging threat (harmful fine-tuning at
Externí odkaz:
http://arxiv.org/abs/2402.16382
Learning rewards from human behaviour or feedback is a promising approach to aligning AI systems with human values but fails to consistently extract correct reward functions. Interpretability tools could enable users to understand and evaluate possib
Externí odkaz:
http://arxiv.org/abs/2402.04856
Akademický článek
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Effects of sodium ascorbate, sodium saccharin and ammonium chloride on the male rat urinary bladder.
Autor:
Cohen, Samuel M., Garland, Emily M., Cano, Martin, John, Margaret K.St, Khachab, Mohamad, Wehner, Jan M., Arnold, Lora L.
Publikováno v:
Carcinogenesis; 1995, Vol. 16 Issue 11, p2743-2750, 8p
