Cognaptus Insights

A new perspective on AI creativity separates rapid generation from the harder capabilities of evaluation, redirection, and changing the creative problem itself.

A soccer action-spotting study shows that preserving player identity through the model can matter more than simply adding features or temporal processing.

Controlled rewrites show that LLM judgments can move with linguistic form, making prompt structure a robustness variable rather than a cosmetic choice.

ELSAA shows that combining sparse and low-rank attention requires correcting how their separately normalized outputs are scaled, not merely adding two efficient branches.

A time-series model can win or lose because the evaluation window suppresses the zero-occurrence behavior that operations actually depend on.

Skill libraries can raise average agent performance while breaking workflows that already worked; paired evaluation reveals how large that reliability cost can be.

Why large attribution scores in forecasting models can reflect mediated autocorrelation or off-manifold sensitivity rather than a direct model dependency.

Agentic-DPO shows how expert traces can supervise the mistakes an agent is likely to make, without requiring full online rollouts during training.

SynthSite shows why safety-video anonymization should be judged by preserved task geometry and human-grounded hazard accuracy, not visual concealment or baseline-model consistency alone.

Multi-agent oversight improves only when valid critique changes the work that actually moves forward.