12 citations · 26 across the 9 of their papers we have counts for
3 papers · 1 filter
Jailbreak Distillation: Renewable Safety Benchmarking
Jingyu Zhang, Ahmed Elgohary, Xiawei Wang +5
Large language models (LLMs) are rapidly deployed in critical applications, raising urgent needs for robust safety benchmarking. We propose Jailbreak Distillation (JBDistill), a no…
Is In-Context Learning Sufficient for Instruction Following in LLMs?
Hao Zhao, Maksym Andriushchenko, Francesco Croce +1
In-context learning (ICL) allows LLMs to learn from examples without changing their weights: this is a particularly promising capability for long-context LLMs that can potentially…
Competition Report: Finding Universal Jailbreak Backdoors in Aligned LLMs
Javier Rando, Francesco Croce, Kryštof Mitka +4
Large language models are aligned to be safe, preventing users from generating harmful content like misinformation or instructions for illegal activities. However, previous work ha…