Papers by Wenhui Lei

2 papers
Inspecting Unification of Encoding and Matching with Transformer: A Case Study of Machine Reading Comprehension (D19-58)

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Challenge: Experimental results show that unified model outperforms other models that treat encoding and matching separately.
Approach: They evaluate a unified model with Transformer layers for machine reading comprehension . they find that the model learns different modeling strategies compared with previous models .
Outcome: The unified model outperforms models with Transformer layers on the machine reading comprehension task.
Mis-prompt: Benchmarking Large Language Models for Proactive Error Handling (2025.acl-long)

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Challenge: Current error-handling works are performed in a passive manner, with explicit error- handling instructions.
Approach: They propose a new benchmark to analyze LLMs' performance on a mis-prompt benchmark and a dataset to promote further research.
Outcome: The proposed benchmark shows that current LLMs show poor performance on proactive error handling, and that SFT improves on error handling instances.

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