6 citations · 7 across the 8 of their papers we have counts for
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cs.CL2024★ 1 cited
Enhancing Character-Level Understanding in LLMs through Token Internal Structure Learning
Zhu Xu, Zhiqiang Zhao, Zihan Zhang +6
Tokenization methods like Byte-Pair Encoding (BPE) enhance computational efficiency in large language models (LLMs) but often obscure internal character structures within tokens. T…
cs.IR2024
When SparseMoE Meets Noisy Interactions: An Ensemble View on Denoising Recommendation
Weipu Chen, Zhuangzhuang He, Fei Liu
Learning user preferences from implicit feedback is one of the core challenges in recommendation. The difficulty lies in the potential noise within implicit feedback. Therefore, va…
cs.DC2024★ 6 cited
Computing in the Era of Large Generative Models: From Cloud-Native to AI-Native
Yao Lu, Song Bian, Lequn Chen +19
In this paper, we investigate the intersection of large generative AI models and cloud-native computing architectures. Recent large models such as ChatGPT, while revolutionary in t…