Papers by Sicheng Wan

1 papers
Graph Explorer: Training Faithful KG Agents with Visibility-Grounded Supervision (2026.findings-acl)

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Challenge: Large language models (LLMs) are strong reasoners but still hallucinate and make unreliable decisions on knowledge-intensive questions.
Approach: They propose a pipeline that turns LLM into executable tool supervision without manual trace labeling.
Outcome: The proposed model improves over a reproduced prompting baseline by +22.5/+16.2 points . it is based on a Graph Explorer pipeline that turns SPARQL into executable tool supervision without manual trace labeling.

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