Papers by Wanpeng Xu

2 papers
Lost in Execution: On the Multilingual Robustness of Tool Calling in Large Language Models (2026.acl-long)

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Challenge: Large Language Models (LLMs) are increasingly deployed as agents that invoke external tools through structured function calls.
Approach: They introduce a diagnostic benchmark and conduct a systematic evaluation of multilingual tool calling across Chinese, Hindi, and the low-resource language Igbo.
Outcome: The proposed benchmarks show that multilingual tool calling fails despite correct intent understanding and tool selection.
Instructional Agents: Reducing Teaching Faculty Workload through Multi-Agent Instructional Design (2026.eacl-long)

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Challenge: Existing AI-assisted educational tools focus on isolated tasks, but lack end-to-end workflows for instructional design.
Approach: They propose a multi-agent large language model framework to automate end-to-end course material generation.
Outcome: The proposed framework reduces development time and human workload while reducing human involvement.

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