Choosing before acting: comparative value estimation for long-horizon tool-use agents
Read the original at arxiv.org→arXiv:2610.02330v1 Announce Type: new Abstract: Large language models (LLMs) rely on long-horizon tool invocation sequences for complex tasks, where each invocation can alter the task state and condition subsequent...
Original headline: "Choosing Before Acting: Comparative Value Estimation for Long-Horizon Tool-Use Agents"
Coverage timeline
- Oct 5, 04:00 UTC arXiv cs.AI lead source Choosing Before Acting: Comparative Value Estimation for Long-Horizon Tool-Use Agents