8 citations · 29 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
Cross-City Matters: A Multimodal Remote Sensing Benchmark Dataset for Cross-City Semantic Segmentation using High-Resolution Domain Adaptation Networks
Danfeng Hong, Bing Zhang, Hao Li +7
Artificial intelligence (AI) approaches nowadays have gained remarkable success in single-modality-dominated remote sensing (RS) applications, especially with an emphasis on indivi…
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…
Interpretable End-to-End Driving Model for Implicit Scene Understanding
Yiyang Sun, Xiaonian Wang, Yangyang Zhang +3
Driving scene understanding is to obtain comprehensive scene information through the sensor data and provide a basis for downstream tasks, which is indispensable for the safety of…