Papers by Xin-Yu Xiao

2 papers
Lunar Twins: We Choose to Go to the Moon with Large Language Models (2025.findings-acl)

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Challenge: Lunar Twins is the first LLM designed specifically for lunar exploration . Lunar GenData is a multi-agent collaborative workflow for generating lunar instructions .
Approach: They propose a framework that combines both large and small LLMs and Lunar GenData, which integrates real data from Chang'e lunar missions.
Outcome: Experimental validation shows that the proposed framework enhances domain expertise and reveals indications of embodied intelligence potential.
Lunar-Bench: Towards Evaluating Task-Oriented Reasoning of LLMs in Lunar Exploration Scenarios (2026.findings-acl)

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Challenge: Existing benchmarks focus on static, context-independent reasoning tasks and fail to capture constraints and dependencies of lunar missions.
Approach: They propose a benchmark to assess the task-oriented reasoning and decision-making performance of large language models through 3,000 tasks derived from mission procedures and documentation.
Outcome: The proposed model achieves 47.8% accuracy compared with 65.1% for human experts on 36 representative missions.

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