SwapAnything is a new method that allows swapping any object in an image with personalized concepts given by a reference image.
Key points: 1️⃣ It uses pre-trained diffusion models to enable precise and high-fidelity object swapping in images. 2️⃣Targeted variable swapping ensures perfect background preservation while swapping specific areas. 3️⃣SwapAnything achieves good results in single-object, multi-object, partial-object, and cross-domain swapping tasks.
Anthropic introduces "Many-shot Jailbreaking" (MSJ), a new attack on large language models! MSJ exploits long context windows to override safety constraints.
Key Points: * Prompts LLMs with hundreds of examples of harmful behavior formatted as a dialogue * Generates malicious examples using an uninhibited "helpful-only" model * Effective at jailbreaking models like Claude 2.0, GPT-3.5, GPT-4 * Standard alignment techniques provide limited protection against long context attacks