299 citations · 326 across the 8 of their papers we have counts for
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cs.CL2026
Enhancing Numerical Prediction in LLMs via Smooth MMD Alignment
Zhuo Zuo, Li Yue, Wenhao Zheng +2
Despite their strong general capabilities, large language models (LLMs) often remain unreliable when outputs must be numerically precise. A key reason is the training objective: st…
cs.LG2026
Taming the Long Tail: Rebalancing Adversarial Training via Adaptive Perturbation
Lilin Zhang, Yimo Guo, Yue Li +2
Deep neural networks are highly vulnerable to adversarial examples, i.e.,small perturbations that can significantly degrade model performance. While adversarial training has become…