Social Meaning in Large Language Models: Structure, Magnitude, and Pragmatic Prompting

1. 1Introduce calibration-focused metrics to evaluate LLMs' structural fidelity and magnitude calibration
2. 2Investigate the impact of pragmatic prompting strategies on LLMs' approximation of human social meaning
3. 3Analyze the quantitative and qualitative aspects of LLMs' social reasoning and pragmatic abilities
4. 4Apply the findings to improve LLMs' performance and develop more effective prompting strategies

AI researchers and engineers working on LLMs can benefit from this research to improve their models' social understanding and reasoning capabilities, while product managers and designers can apply these findings to develop more effective and responsible AI-powered products

💡 Pragmatic prompting strategies can improve LLMs' approximation of human social meaning

💡 New research on LLMs' social meaning & pragmatic prompting!