3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient Learning
Bei Li, Tong Zheng, Rui Wang +8
Residual networks, as discrete approximations of Ordinary Differential Equations (ODEs), have inspired significant advancements in neural network design, including multistep method…
cs.CL2024
Mitigating Reversal Curse in Large Language Models via Semantic-aware Permutation Training
Qingyan Guo, Rui Wang, Junliang Guo +3
While large language models (LLMs) have achieved impressive performance across diverse tasks, recent studies showcase that causal LLMs suffer from the "reversal curse". It is a typ…
cs.LG2024★ 3 cited
Beyond Language Models: Byte Models are Digital World Simulators
Shangda Wu, Xu Tan, Zili Wang +3
Traditional deep learning often overlooks bytes, the basic units of the digital world, where all forms of information and operations are encoded and manipulated in binary format. I…