Papers by Sui Xiaoyu

2 papers
PLAWBENCH: A Rubric-Based Benchmark for Evaluating LLMs in Real-World Legal Practice (2026.acl-long)

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Challenge: Existing benchmarks for large language models (LLMs) are coarse, single-dimensional metrics and do not explicitly assess fine-grained legal reasoning.
Approach: They propose a Practical Law Benchmark to evaluate large language models in real-world legal practice scenarios.
Outcome: The proposed model is based on 850 questions and 13 scenarios with expert-designed evaluation rubrics.
A Framework for Effective Invocation Methods of Various LLM Services (2025.coling-main)

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Challenge: Large Language Models (LLMs) are becoming a fundamental tool for various natural language processing tasks due to commercial reasons, the potential risk of misuse and expensive tuning cost.
Approach: They propose a framework for constructing an effective LLM services invocation strategy that best meets task demands.
Outcome: The proposed framework classifies existing methods into four categories: input abstraction, semantic cache, solution design, and output enhancement, which can be used separately or jointly during the invocation life cycle.

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