4 citations · 8 across the 20 of their papers we have counts for
10 papers · 1 filter
MMA-ASIA: A Multilingual and Multimodal Alignment Framework for Culturally-Grounded Evaluation
Weihua Zheng, Zhengyuan Liu, Tanmoy Chakraborty +32
Large language models (LLMs) are now used worldwide, yet their multimodal understanding and reasoning often degrade outside Western, high-resource settings. We propose MMA-ASIA, a…
Counterfactual Reasoning for Steerable Pluralistic Value Alignment of Large Language Models
Hanze Guo, Jing Yao, Xiao Zhou +2
As large language models (LLMs) become increasingly integrated into applications serving users across diverse cultures, communities and demographics, it is critical to align LLMs w…
MoVa: Towards Generalizable Classification of Human Morals and Values
Ziyu Chen, Junfei Sun, Chenxi Li +6
Identifying human morals and values embedded in language is essential to empirical studies of communication. However, researchers often face substantial difficulty navigating the d…
IROTE: Human-like Traits Elicitation of Large Language Model via In-Context Self-Reflective Optimization
Yuzhuo Bai, Shitong Duan, Muhua Huang +7
Trained on various human-authored corpora, Large Language Models (LLMs) have demonstrated a certain capability of reflecting specific human-like traits (e.g., personality or values…
MoHoBench: Assessing Honesty of Multimodal Large Language Models via Unanswerable Visual Questions
Yanxu Zhu, Shitong Duan, Xiangxu Zhang +7
Recently Multimodal Large Language Models (MLLMs) have achieved considerable advancements in vision-language tasks, yet produce potentially harmful or untrustworthy content. Despit…
Unintended Harms of Value-Aligned LLMs: Psychological and Empirical Insights
Sooyung Choi, Jaehyeok Lee, Xiaoyuan Yi +3
The application scope of Large Language Models (LLMs) continues to expand, leading to increasing interest in personalized LLMs that align with human values. However, aligning these…
AdAEM: An Adaptively and Automated Extensible Measurement of LLMs' Value Difference
Jing Yao, Shitong Duan, Xiaoyuan Yi +6
Assessing Large Language Models'(LLMs) underlying value differences enables comprehensive comparison of their misalignment, cultural adaptability, and biases. Nevertheless, current…
Beyond BFI: The CSI for Enhanced Reliability and Validity in Evaluating LLM Personality Traits
Huanhuan Ma, Haisong Gong, Xiaoyuan Yi +3
As large language models (LLMs) increasingly function as human-like assistants exhibiting human-like personality traits, understanding their behavioral characteristics becomes esse…
Research Superalignment Should Advance Now with Alternating Competence and Conformity Optimization
HyunJin Kim, Xiaoyuan Yi, Jing Yao +4
The recent leap in AI capabilities, driven by big generative models, has sparked the possibility of achieving Artificial General Intelligence (AGI) and further triggered discussion…
Value Compass Benchmarks: A Platform for Fundamental and Validated Evaluation of LLMs Values
Jing Yao, Xiaoyuan Yi, Shitong Duan +8
As Large Language Models (LLMs) achieve remarkable breakthroughs, aligning their values with humans has become imperative for their responsible development and customized applicati…