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Latest AI news, models and releases from Meta. ['Astryx', 'Business Agent', 'BYT5', 'CodeLlama', 'expressive voice AI', 'FAIRChem v2 UMA', 'Gemma 4', 'Gemma4:e2b', 'HuBERT', 'llama', 'Llama', 'LLaMA', 'Llama-2 70B', 'LLaMA2-chat-70B', 'Llama 3', 'Llama 3.1', 'Llama 3.1-405B', 'Llama-3.1-405B', 'LLaMA-3.1 405B', 'Llama 3.1-70B', 'Llama-3.1-70B', 'Llama 3.1 8B', 'Llama 3.1-8B', 'Llama-3.1-8B', 'Llama 3.2', 'LLaMA 3.2', 'Llama-3.2-1B-Instruct', 'Llama 3.3', 'llama-3.3-70b', 'Llama 3.3-70B', 'Llama 3 8B', 'Llama3-8B-Instruct', 'Llama 4', 'Llama 4 Maverick', 'LLaMA 65B', 'Llama 70B', 'M2M100', 'M**a AI', 'mBART', 'Meta AI']

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AI Safety 🇺🇸

StruQ and SecAlign: Defending Against Prompt Injection Attacks

Researchers from BAIR propose two fine-tuning defenses, StruQ and SecAlign, against prompt injection attacks in LLM-integrated applications. StruQ uses structured instruction tuning to ignore injected instructions, while SecAlign applies preference optimization to achieve better robustness, reducing attack success rates to near 0% for optimization-free attacks and below 15% for optimization-based attacks.

Beyond Standard LLMs: Linear Attention Hybrids, Text Diffusion, Code World Models, and Small Recursive Transformers

The article by Sebastian Raschka explores alternatives to standard autoregressive transformer LLMs, including linear attention hybrids (e.g., MiniMax-M1, Qwen3-Next, DeepSeek V3.2, Kimi Linear), text diffusion models, code world models, and small recursive transformers. It discusses the revival of linear attention mechanisms and challenges, such as MiniMax reverting to standard attention in its M2 model due to poor performance on reasoning tasks.

Moonshot AI

MiniMax

Alibaba/Qwen

DeepSeek

Google/DeepMind

Mistral