CliffCompaction: Cost-Efficient Compaction for Long-Horizon Coding Agents

AI Digest - ArXiv AI

CliffCompaction: Cost-Efficient Compaction for Long-Horizon Coding Agents

Agents often work on complex problems that require millions of tokens of context, which necessitates compacting across sessions due to limited context windows. We develop CliffCompaction, an autocompaction technique that reduces cost by up to 50% under a bounded context while maintaining or improving performance on Terminal-Bench and achieving new levels of efficiency for test-time scaling and state-of-the-art results on KernelBench. The per-rollout savings of CliffCompaction make the performanc

Source: ArXiv AI