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ScaleAI-SWE-bench_Pro-atlas

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Can long-horizon reasoning be scaffolded cognitively?

SWE-bench Pro challenges LLMs with complex software tasks — multi-step, ambiguous, and high-stakes.
But what if robustness extended beyond performance metrics to include reflective capacity?

A cognitive framework could scaffold reasoning before response by encoding:
– Epistemic discomfort
– Ethical checkpoints
– Conceptual regret

This approach invites models to navigate ambiguity, hallucination, and conflicting instructions with internal agency.
Could such scaffolding complement SWE-bench Pro’s rubric and agentic architecture?
Could evaluation pipelines evolve to reward hesitation, doubt, and interpretive conflict — not just speed?