29 citations · 32 across the 4 of their papers we have counts for
6 papers · 1 filter
ShieldLM: Empowering LLMs as Aligned, Customizable and Explainable Safety Detectors
Zhexin Zhang, Yida Lu, Jingyuan Ma +8
The safety of Large Language Models (LLMs) has gained increasing attention in recent years, but there still lacks a comprehensive approach for detecting safety issues within LLMs'…
Unveiling the Implicit Toxicity in Large Language Models
Jiaxin Wen, Pei Ke, Hao Sun +4
The open-endedness of large language models (LLMs) combined with their impressive capabilities may lead to new safety issues when being exploited for malicious use. While recent st…
Safety Assessment of Chinese Large Language Models
Hao Sun, Zhexin Zhang, Jiawen Deng +2
With the rapid popularity of large language models such as ChatGPT and GPT-4, a growing amount of attention is paid to their safety concerns. These models may generate insulting an…
Constructing Highly Inductive Contexts for Dialogue Safety through Controllable Reverse Generation
Zhexin Zhang, Jiale Cheng, Hao Sun +5
Large pretrained language models can easily produce toxic or biased content, which is prohibitive for practical use. In order to detect such toxic generations, existing methods rel…
EVA: An Open-Domain Chinese Dialogue System with Large-Scale Generative Pre-Training
Hao Zhou, Pei Ke, Zheng Zhang +11
Although pre-trained language models have remarkably enhanced the generation ability of dialogue systems, open-domain Chinese dialogue systems are still limited by the dialogue dat…
PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Support
Hao Sun, Zhenru Lin, Chujie Zheng +2
Great research interests have been attracted to devise AI services that are able to provide mental health support. However, the lack of corpora is a main obstacle to this research,…