Papers by Qiqiang Lin

1 papers
HammerBench: Fine-Grained Function-Calling Evaluation in Real Mobile Assistant Scenarios (2025.findings-acl)

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Challenge: Evaluating the performance of LLMs in multi-turn interactions presents significant challenges due to the complexity and variability of user behavior.
Approach: They propose a benchmark framework for assessing LLMs’ function-calling capabilities in multi-turn dialogues.
Outcome: The proposed framework is based on a dataset derived from popular mobile apps and anonymized user logs.

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