103 citations · 182 across the 14 of their papers we have counts for
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cs.CL2024
Uncertainty is Fragile: Manipulating Uncertainty in Large Language Models
Qingcheng Zeng, Mingyu Jin, Qinkai Yu +12
Large Language Models (LLMs) are employed across various high-stakes domains, where the reliability of their outputs is crucial. One commonly used method to assess the reliability…
cs.CL2024★ 4 cited
Empowering Large Language Models for Textual Data Augmentation
Yichuan Li, Kaize Ding, Jianling Wang +1
With the capabilities of understanding and executing natural language instructions, Large language models (LLMs) can potentially act as a powerful tool for textual data augmentatio…
cs.CL2023
GRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed Graphs
Yichuan Li, Kaize Ding, Kyumin Lee
Self-supervised representation learning on text-attributed graphs, which aims to create expressive and generalizable representations for various downstream tasks, has received incr…