Papers with agent-based LLM methods
AgentPro: Enhancing LLM Agents with Automated Process Supervision (2025.emnlp-main)
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| Challenge: | Existing frameworks lack explicit supervision during the reasoning process, which may lead to error propagation across reasoning chains. |
| Approach: | They propose a framework which automates process supervision for large language model agents by automatically generating step-level annotations and developing a process reward model based on these annotations. |
| Outcome: | The proposed framework outperforms existing agent-based methods on four datasets and achieves a 6.32% increase in accuracy. |