RESEARCH · RESEARCH · #1774
On the Clock: Time‑budgeted LLM agents can adhere to deadlines but struggle to use extra time productively
arXiv:2610.10833v1 ('On the Clock') studies whether small LLM agents (Qwen3.6-27B and Qwen3-4B) can both respect explicit wall-clock time budgets and use extra time to improve performance. The authors test harness-based timing/execution enforcement and budget-aware RL (GRPO) on MLE-Bench Lite tasks and Zork I (Jericho); harness timing signals improve budget adherence, GRPO achieves near-perfect adherence and generalizes to unseen budgets on Zork I, but agents still fail to translate extra time into better task performance and often repeat actions or collapse to short-budget strategies.
KEY POINTS
- arXiv:2610.10833v1 ('On the Clock') studies whether small LLM agents (Qwen3.6-27B and Qwen3-4B) can both respect explicit wall-clock time budgets and use extra time to improve performance.
- The authors test harness-based timing/execution enforcement and budget-aware RL (GRPO) on MLE-Bench Lite tasks and Zork I (Jericho); harness timing signals improve budget adherence, GRPO achieves near-perfect adherence and generalizes to unseen budgets on Zork I, but agents still fail to translate extra time into better task performance and often repeat actions or collapse to short-budget strategies.
- This paper identifies a practical gap between making agents respect runtime budgets and enabling them to allocate extra time productively—important for deploying time‑constrained AI agents.
WHY IT MATTERS
This paper identifies a practical gap between making agents respect runtime budgets and enabling them to allocate extra time productively—important for deploying time‑constrained AI agents.