PICACO: Pluralistic In-Context Value Alignment of LLMs via Total Correlation Optimization

arXiv:2507.16679v3 Announce Type: replace Abstract: In-Context Learning has shown great potential for aligning Large Language Models (LLMs) with human values, helping reduce harmful outputs and accommodate diverse preferences without costly post-training, known as In-Context Alignment (ICA). However, LLMs' comprehension of input prompts remains agnostic, limiting ICA's ability to address value tensions--human values are inherently pluralistic, often imposing conflicting demands, e.g., stimulation vs. tradition. Current ICA methods therefore face the Instruction Bottleneck challenge, where LLMs

Source: arXiv cs.CL — read the full report at the original publisher.

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