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Morph Reflexes: Efficient Multi-Head Classifiers for Agent Behavior
Morph Reflexes uses a modern LLM with hybrid attention and removes the decode step to enable 99% reuse of prefill compute across reflexes. This approach addresses common agent failures like looping and reasoning leakage without the high cost of judging every turn with frontier models.
By significantly reducing inference costs and latency, Morph Reflexes allows scalable real-time evaluation of agent behavior. This can improve production agent reliability and user experience without relying on expensive models for every interaction.
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Score 75
Source Type rss
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Topic Quality 61
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