SPACE Cuts Agent LLM Calls by 78.9% While Boosting Success

SPACE, an Amazon-Microsoft paper accepted to EMNLP 2026, distills action-chunk boundaries from successful trajectories so agents can safely execute action sequences without per-step LLM calls. It cuts decision rounds by up to 78.9% while raising success from 35.9% to 67.2%.

2026-09-04 ~ 2026-09-04 · 3 related posts

• SPACE cuts agent LLM calls by 78.9% while raising success rate on long-horizon tasks — dair_ai · 2026-09-04
• Amazon-Microsoft paper: skill-guided action chunking lifts agent success to 67.2% while halving LLM calls — rohanpaul_ai · 2026-09-04
• SPACE (EMNLP 2026): learning chunk boundaries from trajectories cuts agent LLM rounds by up to 78.9% — rohanpaul_ai · 2026-09-04