3 citations · 6 across the 5 of their papers we have counts for
5 papers
Rethinking Personalization in Large Language Models at the Token Level
Chenheng Zhang, Yijun Lu, Lizhe Fang +7
With large language models (LLMs) now performing strongly across diverse tasks, there is growing demand for them to personalize outputs for individual users. Personalization is typ…
Language Ranker: A Lightweight Ranking framework for LLM Decoding
Chenheng Zhang, Tianqi Du, Jizhe Zhang +4
Conventional research on large language models (LLMs) has primarily focused on refining output distributions, while paying less attention to the decoding process that transforms th…
Generalist++: A Meta-learning Framework for Mitigating Trade-off in Adversarial Training
Yisen Wang, Yichuan Mo, Hongjun Wang +2
Despite the rapid progress of neural networks, they remain highly vulnerable to adversarial examples, for which adversarial training (AT) is currently the most effective defense. W…
Incorporating Arbitrary Matrix Group Equivariance into KANs
Lexiang Hu, Yisen Wang, Zhouchen Lin
Kolmogorov-Arnold Networks (KANs) have seen great success in scientific domains thanks to spline activation functions, becoming an alternative to Multi-Layer Perceptrons (MLPs). Ho…
Do Generated Data Always Help Contrastive Learning?
Yifei Wang, Jizhe Zhang, Yisen Wang
Contrastive Learning (CL) has emerged as one of the most successful paradigms for unsupervised visual representation learning, yet it often depends on intensive manual data augment…