8 citations · 14 across the 20 of their papers we have counts for
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cs.CL2024★ 6 cited
On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey
Lin Long, Rui Wang, Ruixuan Xiao +4
Within the evolving landscape of deep learning, the dilemma of data quantity and quality has been a long-standing problem. The recent advent of Large Language Models (LLMs) offers…
cs.LG2024
Data Contamination Calibration for Black-box LLMs
Wentao Ye, Jiaqi Hu, Liyao Li +3
The rapid advancements of Large Language Models (LLMs) tightly associate with the expansion of the training data size. However, the unchecked ultra-large-scale training sets introd…
q-bio.QM2024
Physical formula enhanced multi-task learning for pharmacokinetics prediction
Ruifeng Li, Dongzhan Zhou, Ancheng Shen +9
Artificial intelligence (AI) technology has demonstrated remarkable potential in drug dis-covery, where pharmacokinetics plays a crucial role in determining the dosage, safety, and…