25 citations · 30 across the 9 of their papers we have counts for
4 papers · 1 filter
How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs
Guhao Feng, Kai Yang, Yuntian Gu +6
Despite the remarkable success of Transformer-based large language models (LLMs) across various domains, understanding and enhancing their mathematical capabilities remains a signi…
DPO Meets PPO: Reinforced Token Optimization for RLHF
Han Zhong, Zikang Shan, Guhao Feng +6
In the classical Reinforcement Learning from Human Feedback (RLHF) framework, Proximal Policy Optimization (PPO) is employed to learn from sparse, sentence-level rewards -- a chall…
Do Efficient Transformers Really Save Computation?
Kai Yang, Jan Ackermann, Zhenyu He +6
As transformer-based language models are trained on increasingly large datasets and with vast numbers of parameters, finding more efficient alternatives to the standard Transformer…
Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation
Zhenyu He, Guhao Feng, Shengjie Luo +6
In this work, we leverage the intrinsic segmentation of language sequences and design a new positional encoding method called Bilevel Positional Encoding (BiPE). For each position,…