AIBullisharXiv – CS AI · 15h ago6/10
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AGORA: Adapter-Grounded Observation-Action Retention for Inference-Free Prompt Compression in LLM Agents
Researchers introduce AGORA, a new compression method for LLM agents that addresses critical failures in existing token-level compressors. Unlike general-purpose compression techniques that destroy action semantics by removing low-entropy tokens, AGORA operates at step-granularity with structural awareness, achieving 1.0-11.5x compression while retaining 75%+ performance across most test scenarios.