1 citations · 1 across the 4 of their papers we have counts for
4 papers
Deconfounded Causality-aware Parameter-Efficient Fine-Tuning for Problem-Solving Improvement of LLMs
Ruoyu Wang, Xiaoxuan Li, Lina Yao
Large Language Models (LLMs) have demonstrated remarkable efficiency in tackling various tasks based on human instructions, but studies reveal that they often struggle with tasks r…
Independence Constrained Disentangled Representation Learning from Epistemological Perspective
Ruoyu Wang, Lina Yao
Disentangled Representation Learning aims to improve the explainability of deep learning methods by training a data encoder that identifies semantically meaningful latent variables…
Causality-Aware Transformer Networks for Robotic Navigation
Ruoyu Wang, Yao Liu, Yuanjiang Cao +1
Current research in Visual Navigation reveals opportunities for improvement. First, the direct adoption of RNNs and Transformers often overlooks the specific differences between Em…
ASFT: Aligned Supervised Fine-Tuning through Absolute Likelihood
Ruoyu Wang, Jiachen Sun, Shaowei Hua +1
Direct Preference Optimization (DPO) is a method for enhancing model performance by directly optimizing for the preferences or rankings of outcomes, instead of traditional loss fun…