Papers by Shichang Meng

2 papers
BizCompass: Benchmarking the Reasoning Capabilities of LLMs in Business Knowledge and Applications (2026.findings-acl)

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Challenge: Existing benchmarks focus on narrow tasks and leave a fundamental question unanswered . Existing models only focus on specific tasks, requiring rigorous reasoning and knowledge .
Approach: They propose a benchmark to connect theoretical foundations with practical business knowledge and applications.
Outcome: The benchmark systematically evaluates both open-source and commercial LLMs . it reveals how theoretical knowledge translates into practical performance in business .
AlphaQT-Bench: Diagnosing the Gap between Financial Code Generation and Quantitative Reasoning in LLMs (2026.findings-acl)

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Challenge: Existing benchmarks rely on outcome-driven metrics such as profitability and look-ahead bias.
Approach: They propose a diagnostic benchmark for instruction-grounded financial code generation under strict semantic and temporal constraints.
Outcome: The proposed benchmarks show that the models fail under causal, structural, or functional constraints.

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