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20232026
most citedKnowledge Plugins: Enhancing Large Language Models for Domain-Specific Recommendations

7 citations · 25 across the 38 of their papers we have counts for

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6 papers · 1 filter

cs.CL2023

ToViLaG: Your Visual-Language Generative Model is Also An Evildoer

Xinpeng Wang, Xiaoyuan Yi, Han Jiang +3

Warning: this paper includes model outputs showing offensive content. Recent large-scale Visual-Language Generative Models (VLGMs) have achieved unprecedented improvement in multim…

cs.IR2023★ 7 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.CL2023★ 3 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.CL2023

CDEval: A Benchmark for Measuring the Cultural Dimensions of Large Language Models

Yuhang Wang, Yanxu Zhu, Chao Kong +4

As the scaling of Large Language Models (LLMs) has dramatically enhanced their capabilities, there has been a growing focus on the alignment problem to ensure their responsible and…

cs.CY2023★ 5 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.CL2023

Denevil: Towards Deciphering and Navigating the Ethical Values of Large Language Models via Instruction Learning

Shitong Duan, Xiaoyuan Yi, Peng Zhang +3

Large Language Models (LLMs) have made unprecedented breakthroughs, yet their increasing integration into everyday life might raise societal risks due to generated unethical conten…