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Agentic AI systems can confidently generate plausible but wrong scientific results, even when given domain-specific context, highlighting a critical challenge for their integration into research workflows.
Hybrid architectures that combine attention and recurrence can maintain reasoning performance as task complexity increases, while transformers see a sharp performance drop-off.
