8 papers
PICACO: Pluralistic In-Context Value Alignment of LLMs via Total Correlation Optimization
Han Jiang, Dongyao Zhu, Xiaoyuan Yi +3
In-Context Learning has shown great potential for aligning Large Language Models (LLMs) with human values, helping reduce harmful outputs and accommodate diverse preferences withou…
AI Evaluation Should Require Standardized Item-Level Data Releases
Han Jiang, Susu Zhang, Dongyao Zhu +6
This position paper argues that standardized item-level benchmark data should become the default infrastructure for AI evaluation. Current evaluations suffer from underspecified it…
CAReDiO: Cultural Alignment via Representativeness and Distinctiveness Guided Data Optimization
Jing Yao, Xiaoyuan Yi, Jindong Wang +2
As Large Language Models (LLMs) are deployed across diverse regions, aligning them with pluralistic cultures is crucial for improving user engagement and mitigating cultural confli…
On the Dynamics of Multi-Agent LLM Communities Driven by Value Diversity
Muhua Huang, Qinlin Zhao, Xiaoyuan Yi +1
As Large Language Models (LLM) based multi-agent systems become increasingly prevalent, the collective behaviors, e.g., collective intelligence, of such artificial communities have…
Knowing Your Uncertainty -- On the application of LLM in social sciences
Bolun Zhang, Linzhuo Li, Yunqi Chen +4
Large language models (LLMs) are rapidly being integrated into computational social science research, yet their blackboxed training and designed stochastic elements in inference po…
The Morality of Probability: How Implicit Moral Biases in LLMs May Shape the Future of Human-AI Symbiosis
Eoin O'Doherty, Nicole Weinrauch, Andrew Talone +4
Artificial intelligence (AI) is advancing at a pace that raises urgent questions about how to align machine decision-making with human moral values. This working paper investigates…