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cs.CL20246 cited

EasyJailbreak: A Unified Framework for Jailbreaking Large Language Models

Weikang Zhou, Xiao Wang, Limao Xiong +18

Jailbreak attacks are crucial for identifying and mitigating the security vulnerabilities of Large Language Models (LLMs). They are designed to bypass safeguards and elicit prohibi…

cs.CL2024

Navigating the OverKill in Large Language Models

Chenyu Shi, Xiao Wang, Qiming Ge +7

Large language models are meticulously aligned to be both helpful and harmless. However, recent research points to a potential overkill which means models may refuse to answer beni…

cs.CL20231 cited

RealBehavior: A Framework for Faithfully Characterizing Foundation Models' Human-like Behavior Mechanisms

Enyu Zhou, Rui Zheng, Zhiheng Xi +7

Reports of human-like behaviors in foundation models are growing, with psychological theories providing enduring tools to investigate these behaviors. However, current research ten…

cs.CL20234 cited

TRACE: A Comprehensive Benchmark for Continual Learning in Large Language Models

Xiao Wang, Yuansen Zhang, Tianze Chen +9

Aligned large language models (LLMs) demonstrate exceptional capabilities in task-solving, following instructions, and ensuring safety. However, the continual learning aspect of th…

cs.CL202319 cited

Secrets of RLHF in Large Language Models Part I: PPO

Rui Zheng, Shihan Dou, Songyang Gao +24

Large language models (LLMs) have formulated a blueprint for the advancement of artificial general intelligence. Its primary objective is to function as a human-centric (helpful, h…

cs.CL2023

Farewell to Aimless Large-scale Pretraining: Influential Subset Selection for Language Model

Xiao Wang, Weikang Zhou, Qi Zhang +7

Pretrained language models have achieved remarkable success in various natural language processing tasks. However, pretraining has recently shifted toward larger models and larger…