Researchers introduce PlanFlip, a framework to attack multi-agent LLM systems via planning-phase prompt injection, revealing vulnerabilities in popular models like GPT-5 and Llama-3.3-70B. The study highlights the importance of heterogeneous model diversity for security. PlanFlip's four attacks can corrupt downstream sub-tasks, evading keyword filters and compromising system integrity.

DeepSeek has unveiled a groundbreaking approach to abstract reasoning on ARC-AGI-1, leveraging an open-weight model (DeepSeek V3.2) in a 'non-thinking' mode, augmented by innovative agentic harnesses. This method achieves impressive generalization and pattern discovery, reaching up to 67.25% pass@2 with unprecedented cost-efficiency, sidestepping heavy compute or benchmark-specific fine-tuning.

DeepSeek introduces FirstResearch, a groundbreaking framework that tackles the auditability challenge in LLM-driven scientific discovery. By generating a structured 'Research Question Certificate,' FirstResearch ensures AI-proposed research questions are transparent, inspectable, and based on explicit mechanisms and assumptions, significantly enhancing trust in AI-powered scientific ideation.