A Data-Centric Approach for Safe and Secure Large Language Models against Threatening and Toxic Content

19 April 2025

Papers citing "A Data-Centric Approach for Safe and Secure Large Language Models against Threatening and Toxic Content"

5 / 5 papers shown

Title
N-Critics: Self-Refinement of Large Language Models with Ensemble of Critics Sajad Mousavi Ricardo Luna Gutierrez Desik Rengarajan Vineet Gundecha Ashwin Ramesh Babu Avisek Naug Antonio Guillen-Perez Soumyendu Sarkar LRM HILM KELM 39 7 0 28 Oct 2023
CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing Zhibin Gou Zhihong Shao Yeyun Gong Yelong Shen Yujiu Yang Nan Duan Weizhu Chen KELM LRM 81 394 0 19 May 2023
Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervision Zhiqing Sun Songlin Yang Qinhong Zhou Hongxin Zhang Zhenfang Chen David D. Cox Yiming Yang Chuang Gan SyDa ALM 99 337 0 04 May 2023
Large Language Models Can Self-Improve Jiaxin Huang S. Gu Le Hou Yuexin Wu Xuezhi Wang Hongkun Yu Jiawei Han ReLM AI4MH LRM 199 612 0 20 Oct 2022
HateBERT: Retraining BERT for Abusive Language Detection in English Tommaso Caselli Valerio Basile Jelena Mitrović Michael Granitzer 82 373 0 23 Oct 2020