Papers by Hengrui Cai

2 papers
Recognizing Limits: Investigating Infeasibility in Large Language Models (2025.findings-emnlp)

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Challenge: Large language models fail to handle queries that exceed their knowledge and capabilities, leading to incorrect or fabricated responses.
Approach: They conceptualize four main categories of infeasible tasks for LLMs which cover a broad spectrum of hallucination-related challenges identified in prior literature.
Outcome: The proposed models can handle requests exceeding their knowledge and capabilities and refuse them .
Beyond the Singular: Revealing the Value of Multiple Generations in Benchmark Evaluation (2026.findings-acl)

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Challenge: Existing evaluation methods for large language models overlook the inherent randomness of LLMs.
Approach: They propose a hierarchical statistical model that incorporates both benchmark characteristics and LLM randomness to provide a more comprehensive representation of benchmarking process.
Outcome: The proposed model improves the accuracy of estimating the benchmark score and reduces variance.

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