Papers by Qiuhai Zeng

2 papers
A Functionality-Grounded Benchmark for Evaluating Web Agents in E-commerce Domains (2026.acl-long)

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Challenge: Existing benchmarks focus on product search tasks, but ignore potential risks.
Approach: They propose a data generation pipeline that leverages webpage content and interactive elements to create diverse, functionality-grounded user queries.
Outcome: The proposed framework assesses the performance and safety of web agents under dynamic, real-world e-commerce environments.
AIRepr: An Analyst-Inspector Framework for Evaluating Reproducibility of LLMs in Data Science (2025.findings-emnlp)

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Challenge: Large language models are increasingly used to automate data analysis, but data science tasks often admit multiple statistically valid solutions.
Approach: They propose a framework to evaluate LLM-generated code and assess its reproducibility . they introduce two reproducibility-enhancing prompting strategies and benchmark them against standard prompting .
Outcome: The proposed framework improves reproducibility of large language models . it provides a foundation for transparent, reliable, and efficient human–AI collaboration in data science.

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