Yang Ouyang

Min-K%++: Improved Baseline for Detecting Pre-Training Data from Large Language Models

2024 · arXiv (Cornell University)

The problem of pre-training data detection for large language models (LLMs) has received growing attention due to its implications in critical issues like copyright violation and test data contamination. Despite improved performance, existing methods (including …

Plan Then Action:High-Level Planning Guidance Reinforcement Learning for LLM Reasoning

2025 · arXiv (Cornell University)

Large language models (LLMs) demonstrate strong reasoning abilities via Chain-of-Thought (CoT), but their token-level generation encourages local decisions and lacks global planning, often leading to redundant or inaccurate reasoning. Existing methods, such as tree-based search …