A Survey on Self-Improving Test-Time Intelligence: Feedback-Driven Adapting, Learning, and Scaling at Inference
This story is from 2026-09-03. It is preserved in the archive; the latest stories are on the live feed.
arXiv:2609.01679v1 Announce Type: new Abstract: The ability of AI systems to improve their behavior during deployment is becoming increasingly important. As inference moves beyond the static execution of a fixed trained model, a growing body of work studies how models can refine their behavior on t…
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- 2026-09-03 04:00 · arXiv cs.LG
A Survey on Self-Improving Test-Time Intelligence: Feedback-Driven Adapting, Learning, and Scaling at Inference
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