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This paper introduces RADAR, a method that models large reasoning model generation as four states and uses dynamic attention responses to detect uncontrolled reasoning before repetition begins. It proposes Attention Realignment to correct abnormal attention distributions, reducing generation loops while preserving benign performance.
The author is soliciting stories about AI agents exhibiting runaway behavior, such as repeating fixes or burning credits, to gather insights and discuss improvements.
The user tested the Ternary Bonsai 2 27B AI model with a creative prompt, but it entered an infinite loop, repeating without progress for hours and causing disappointment.
Discusses workarounds for tool-call failures and looping issues in Qwen3.6-27B model.
Introduces six forms of AI agent workflows: classify and execute, fan-out and consolidate, adversarial validation, generate and filter, tournament, loop until done.
Users report that AI models, including Qwen 3.6 35B, enter infinite loops when integrated with Copilot Chat or Hermes, generating excessive tokens or incorrect tool calls.