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cs.CL2026
Modality Fault Lines: Structural Corruptions Reveal Fragile Omni-Modal Reasoning
Zhaolu Kang, Meixin Wu, Yu Xue +6
Omni-modal large language models are increasingly evaluated on clean text--vision--audio inputs, where every channel is present, synchronized, and readily interpretable. Such score…
cs.CL2026
QuantEval: A Benchmark for Financial Quantitative Tasks in Large Language Models
Zhaolu Kang, Junhao Gong, Wenqing Hu +15
Large Language Models (LLMs) have shown strong capabilities in finance-oriented question answering, yet their evaluation on professional quantitative workflows remains fragmented a…
cs.CL2026
How Order-Sensitive Are LLMs? OrderProbe for Deterministic Structural Reconstruction
Zhaolu Kang, Yingjie He, Kehan Jiang +18
Large language models (LLMs) excel at semantic understanding, yet their ability to reconstruct internal structure from scrambled inputs remains underexplored. Sentence-level restor…