19 citations · 20 across the 5 of their papers we have counts for
5 papers
GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
V Team, Wenyi Hong, Wenmeng Yu +90
We present GLM-4.1V-Thinking, GLM-4.5V, and GLM-4.6V, a family of vision-language models (VLMs) designed to advance general-purpose multimodal understanding and reasoning. In this…
SocialEval: Evaluating Social Intelligence of Large Language Models
Jinfeng Zhou, Yuxuan Chen, Yihan Shi +13
LLMs exhibit promising Social Intelligence (SI) in modeling human behavior, raising the need to evaluate LLMs' SI and their discrepancy with humans. SI equips humans with interpers…
AISafetyLab: A Comprehensive Framework for AI Safety Evaluation and Improvement
Zhexin Zhang, Leqi Lei, Junxiao Yang +13
As AI models are increasingly deployed across diverse real-world scenarios, ensuring their safety remains a critical yet underexplored challenge. While substantial efforts have bee…
Global Challenge for Safe and Secure LLMs Track 1
Xiaojun Jia, Yihao Huang, Yang Liu +27
This paper introduces the Global Challenge for Safe and Secure Large Language Models (LLMs), a pioneering initiative organized by AI Singapore (AISG) and the CyberSG R&D Programme…
SafetyBench: Evaluating the Safety of Large Language Models
Zhexin Zhang, Leqi Lei, Lindong Wu +7
With the rapid development of Large Language Models (LLMs), increasing attention has been paid to their safety concerns. Consequently, evaluating the safety of LLMs has become an e…