1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.AI2025
SPPD: Self-training with Process Preference Learning Using Dynamic Value Margin
Hao Yi, Qingyang Li, Yulan Hu +3
Recently, enhancing the numerical and logical reasoning capability of Large Language Models (LLMs) has emerged as a research hotspot. Existing methods face several limitations: inf…
cs.CL2024★ 1 cited
Investigating the Synergistic Effects of Dropout and Residual Connections on Language Model Training
Qingyang Li, Weimao Ke
This paper examines the pivotal role of dropout techniques in mitigating overfitting in language model training. It conducts a comprehensive investigation into the influence of var…
cs.LG2024
TSO: Self-Training with Scaled Preference Optimization
Kaihui Chen, Hao Yi, Qingyang Li +4
Enhancing the conformity of large language models (LLMs) to human preferences remains an ongoing research challenge. Recently, offline approaches such as Direct Preference Optimiza…