Unverified50% confidenceFactExact time
Given the same input, an Agent run multiple times may produce different intermediate steps and final outputs, exhibiting non-determinism.
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50%
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Long-term
Relevance
9/26/2026
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Related Claims
VerifiedIn multi-Agent scenarios, hallucination problems are cascadingly amplified: the erroneous output of one Agent may become the input of the next, causing errors to accumulate continuously throughout the chain.73% similarUnverified由于LLM的输出带有不确定性，Agent场景下无法保证两次调用生成的参数完全一致，这使得幂等键的生成和匹配比传统系统更复杂71% similarUnverifiedWhen an agent falls into an error loop, debugging is often more time-consuming than writing the code oneself.70% similarUnverifiedAgent 评测中由于错误沿任务链累积传播，最终完成率的分差往往比传统 NLP 基准更难弥合70% similarUnverifiedLLM calls have inherent uncertainty: the same input may produce different outputs, token consumption and latency fluctuate significantly, and the reasoning path of an Agent is difficult to predict.69% similar
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