AI Research
Inference-Time Mitigation of Adversarial Political Bias in Large Language Models
New recursive self-correction techniques effectively shield LLM outputs from adversarial political bias injection.
As Large Language Models (LLMs) become the mainstay for information retrieval and summarization tasks, ensuring that they are always non-partisan and invulnerable to political bias is a critical step towards safer and more trustworthy Artificial Intelligence (AI). Current model a...
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ArXiv CS.CL
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ArXiv CS.CL
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This research introduces a robust framework to neutralize adversarial political manipulation in LLMs during the inference stage. By combining Chain of Thought prompting with Recursive Self-Correction, it significantly improves neutrality in automated content summarization.
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