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Identity Inference from CLIP Models using Only Textual Data
To address these challenges, we propose a textual unimodal detector (TUNI) in CLIP models, a novel method for ID inference that 1) queries the target model with only text data; and 2) does not require training shadow models.
RLRF:Reinforcement Learning from Reflection through Debates as Feedback for Bias Mitigation in LLMs
Biases and stereotypes in Large Language Models (LLMs) can have negative implications for user experience and societal outcomes.
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