Large Language Models Can Follow Instructions, But Not Many at Once: Phase Transitions in Compositional Constraint Satisfaction
New benchmark research identifies a hard 'six-constraint wall' where LLM instruction following reliability collapses.
Large language models are increasingly deployed in settings that require simultaneous adherence to multiple explicit constraints - reasoning structure, safety boundaries, output schemas. Individual constraints are handled proficiently, but the compositional regime, where many mus...
ArXiv CS.AI
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This research reveals a critical bottleneck in LLM reliability where performance experiences a catastrophic collapse when balancing more than a few simultaneous constraints. Understanding these phase transitions is essential for developers aiming to build complex, rule-bound systems that require strict adherence to multi-layered output requirements.
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