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cs.AI2026
BizFinBench.v2: Towards Reliable LLMs in Finance via Real-User Data and Offline/Online Bilingual Evaluation
Xin Guo, Rongjunchen Zhang, Guilong Lu +4
Large language models are becoming increasingly significant in financial applications. Nevertheless, prevailing benchmarks are largely dependent on simulated or generic data, which…
cs.AI2026
PuzzleClone: A DSL-Powered Framework for Synthesizing Verifiable Data
Kai Xiong, Yanwei Huang, Rongjunchen Zhang +3
High-quality mathematical and logical datasets with verifiable answers are essential for strengthening the reasoning capabilities of large language models (LLMs). While recent data…
cs.AI2025
BizFinBench: A Business-Driven Real-World Financial Benchmark for Evaluating LLMs
Guilong Lu, Xuntao Guo, Rongjunchen Zhang +2
Large language models excel in general tasks, yet assessing their reliability in logic-heavy, precision-critical domains like finance, law, and healthcare remains challenging. To a…