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Soft Begging: Modular and Efficient Shielding of LLMs against Prompt
Injection and Jailbreaking based on Prompt Tuning

Soft Begging: Modular and Efficient Shielding of LLMs against Prompt Injection and Jailbreaking based on Prompt Tuning

3 July 2024

Simon Ostermann

Christoph Endres

ArXiv (abs)PDF HTML Github

Papers citing "Soft Begging: Modular and Efficient Shielding of LLMs against Prompt Injection and Jailbreaking based on Prompt Tuning"

3 / 3 papers shown

Detection Method for Prompt Injection by Integrating Pre-trained Model and Heuristic Feature Engineering

Detection Method for Prompt Injection by Integrating Pre-trained Model and Heuristic Feature Engineering

212

1

0

05 Jun 2025

Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?

Can LLMs Separate Instructions From Data? And What Do We Even Mean By That?International Conference on Learning Representations (ICLR), 2024

Sahar Abdelnabi

Mario Fritz

Christoph H. Lampert

483

54

0

11 Mar 2024

Hijacking Large Language Models via Adversarial In-Context Learning

Hijacking Large Language Models via Adversarial In-Context Learning

Saleh Zare Zade

Prashant Khanduri

639

50

0

16 Nov 2023

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