Agent traces reveal hour-long costly 'super resolution' rabbit hole in continual learning study
yuxiangw_cs · x · 2026-09-12
Researchers comparing continual learning behavior across models found interesting agentic behaviors in traces: one agent fell into a costly hour-long "super resolution" rabbit hole. The quoted analysis notes Fable 5.1 and Astra shine in complex scenarios requiring sifting historical data or handling compositional challenges.
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