Remarkably, the tunneling spectra show a sharp zero-bias peak (ZBP) with multiple integer-quantized states at the step edge under zero magnetic field. We propose that the increasing …

2024年10月22日 · 微软亚洲研究院的最新研究关键计划步骤学习 CPL（Critical Plan Step Learning），旨在将强化学习扩展到更广泛、更复杂的问题场景，并取得了突破性进展。 CPL …

2024年9月13日 · To address this, we propose searching within the action space on high-level abstract plans to enhance model generalization and introduce Critical Plan Step Learning …

In this section, we introduce our Critical Plan Step Learning (CPL), it boosts model performance via iterative process over plan-based search and step-level preference learning. We first …

CPL: Critical Plan Step Learning Boosts LLM Generalization in Reasoning Tasks Environment Setup Create a Python virtual environment and install the dependencies:

To tackle this challenge, we introduce Critical Planning Step Learning (CPL), which leverages Monte Carlo Tree Search (MCTS) to explore diverse planning steps in multi-step reasoning …

通过引入关键规划步骤学习（CPL）和逐步优势偏好优化（Step-APO），利用蒙特卡罗树搜索（MCTS）探索多步骤推理任务中的规划步骤，从而改善了模型的推理能力。

2024年9月17日 · A novel method called Critical Planning Step Learning (CPL) that leverages Monte Carlo Tree Search (MCTS) to explore planning steps in multi-step reasoning tasks,...

2024年9月13日 · To tackle this challenge, we introduce Critical Planning Step Learning (CPL), which leverages Monte Carlo Tree Search (MCTS) to explore diverse planning steps in multi …

2024年9月15日 · The paper introduces Critical Planning Step Learning (CPL), a novel approach that utilizes Monte Carlo Tree Search (MCTS) to enhance the generalization capabilities of …