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Language models struggle to recover research ideas from bibliographies, achieving only 3-15% accuracy, but a multi-agent approach boosts this to 23-42%.
Current AI research agents miss critical metacognitive checks, leading to pervasive failures across diverse scientific tasks.
Open-source Arabic-DeepSeek-R1 dethrones GPT-5.1 on Arabic language benchmarks, proving that culturally-informed adaptation of sparse MoE models can leapfrog proprietary giants without massive pretraining costs.
