Unverified50% confidenceTradeoffExact time
Reflection mechanisms increase the number of inference calls and latency, so in practice a maximum number of iterations or a quality threshold is often set as the stopping condition.
1
Sources
50%
Confidence
Long-term
Relevance
10/29/2026
First Seen
Sources
Understand Agentic AI in 1 Hour: Architecture, Design Patterns, and Hands-On Building
bilibiliAIDeepCoder10/25/2026
Related Entities
Related Claims
UnverifiedAn interrupted tool call may cause subsequent reasoning to continue planning based on an unfinished action, or cause duplicate writes or missed checks in non-idempotent operation scenarios.78% similarUnverifiedSetting a maximum token limit for the reasoning process and incorporating repetitive content detection to interrupt generation upon detecting consecutively repeated segments is a solution for addressing reasoning infinite loops.78% similarUnverifiedThe Reflexion architecture is most sensitive to token consumption, as the self-evaluation loop may bring several times the cost increase; it is recommended to enable it only in scenarios with strict requirements on result accuracy and to set a maximum number of reflection rounds.76% similarUnverifiedThe study introduces a confidence threshold to dynamically adjust the quality–latency trade-off at inference time, providing the widest and consistently competitive operating range.76% similarUnverifiedThe inference side focuses on latency, throughput, and memory usage during deployment, involving engineering means such as quantization, operator replacement, and runtime scheduling.75% similar
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