activity
20172026
most citedInteractive Steering of Hierarchical Clustering

54 citations · 123 across the 41 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

cs.IR20237 cited

Knowledge Plugins: Enhancing Large Language Models for Domain-Specific Recommendations

Jing Yao, Wei Xu, Jianxun Lian +3

The significant progress of large language models (LLMs) provides a promising opportunity to build human-like systems for various practical applications. However, when applied to s…

cs.CL20233 cited

Value FULCRA: Mapping Large Language Models to the Multidimensional Spectrum of Basic Human Values

Jing Yao, Xiaoyuan Yi, Xiting Wang +2

The rapid advancement of Large Language Models (LLMs) has attracted much attention to value alignment for their responsible development. However, how to define values in this conte…

cs.CY20235 cited

Unpacking the Ethical Value Alignment in Big Models

Xiaoyuan Yi, Jing Yao, Xiting Wang +1

Big models have greatly advanced AI's ability to understand, generate, and manipulate information and content, enabling numerous applications. However, as these models become incre…

cs.AI2023

Evaluating General-Purpose AI with Psychometrics

Xiting Wang, Liming Jiang, Jose Hernandez-Orallo +4

Comprehensive and accurate evaluation of general-purpose AI systems such as large language models allows for effective mitigation of their risks and deepened understanding of their…

cs.AI20236 cited

From Instructions to Intrinsic Human Values -- A Survey of Alignment Goals for Big Models

Jing Yao, Xiaoyuan Yi, Xiting Wang +2

Big models, exemplified by Large Language Models (LLMs), are models typically pre-trained on massive data and comprised of enormous parameters, which not only obtain significantly…