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Peiqi Yu

2 accepted papers

2026

Emergent Neural Automaton Policies: Learning Symbolic Structure from Visuomotor Trajectories

RSS 2026poster

Scaling robot learning to long-horizon tasks remains a formidable challenge. While end-to-end policies often lack the structural priors needed for effective long-term reasoning, traditional neuro-symbolic methods rely heavily on hand-crafted symbolic priors. To address the issue, we introduce ENAP (…

Cited by 0SourceScholar
2025

Prompt-Guided Internal States for Hallucination Detection of Large Language Models

ACL 2025long

Large Language Models (LLMs) have demonstrated remarkable capabilities across a variety of tasks in different domains. However, they sometimes generate responses that are logically coherent but factually incorrect or misleading, which is known as LLM hallucinations. Data-driven supervised methods tr…