Papers by Xiongkuo Min

2 papers
Market-Bench: Benchmarking Large Language Models on Economic and Trade Competition (2026.acl-long)

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Challenge: Existing LLM benchmarks focus on semantic complexity or quantitative competition, but rarely both simultaneously under economic scarcity.
Approach: They propose a benchmark that evaluates the capabilities of large language models (LLMs) in economically-relevant tasks through economic and trade competition.
Outcome: The proposed model evaluates the capabilities of large language models in economically-relevant tasks through economic and trade competition.
Redundancy Principles for MLLMs Benchmarks (2025.acl-long)

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Challenge: Rapid growth of Multi-modality Large Language Models has led to significant redundancy among benchmarks.
Approach: They propose a framework to improve MLLM benchmark design by identifying redundancy at three levels: dimension, instance, and cross-benchmark redundancies.
Outcome: The proposed framework streamlines evaluations and enhances reliability.

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