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cs.CL2025
TableEval: A Real-World Benchmark for Complex, Multilingual, and Multi-Structured Table Question Answering
Junnan Zhu, Jingyi Wang, Bohan Yu +4
LLMs have shown impressive progress in natural language processing. However, they still face significant challenges in TableQA, where real-world complexities such as diverse table…
cs.CL2025
ChartReasoner: Code-Driven Modality Bridging for Long-Chain Reasoning in Chart Question Answering
Caijun Jia, Nan Xu, Jingxuan Wei +4
Recently, large language models have shown remarkable reasoning capabilities through long-chain reasoning before responding. However, how to extend this capability to visual reason…
cs.CL2025
ChartMind: A Comprehensive Benchmark for Complex Real-world Multimodal Chart Question Answering
Jingxuan Wei, Nan Xu, Junnan Zhu +4
Chart question answering (CQA) has become a critical multimodal task for evaluating the reasoning capabilities of vision-language models. While early approaches have shown promisin…