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Prematurely solving an author's immediate drafting problem with an LLM eliminates the exact cognitive friction required to uncover genuinely novel conceptual frameworks.
OrthoPilot outperformed seasoned orthopaedic experts in diagnostic reasoning, achieving a 10.6% increase in management success for complex musculoskeletal cases.
LRMs allocate more resources to problems they get wrong, while humans engage more with problems they expect to solve, revealing a fundamental difference in reasoning strategies.
Dynamic scheduling in SegFold unlocks nearly 2x speedup over traditional SpGEMM accelerators by optimizing data reuse and load balance.
SkillGrad's gradient-descent-inspired approach makes optimizing LLM agent skills as straightforward as training neural networks, achieving a 6.7% improvement over training-based baselines.
LLMs' impressive reasoning may be an illusion: truncating their reasoning steps reveals memorization-based shortcuts that current contamination detection methods miss.
