1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.AI2026★ 1 cited
Enhancing Causal Reasoning in Large Language Models: A Causal Attribution Model for Precision Fine-Tuning
Hengrui Cai, Shengjie Liu, Rui Song
This paper introduces a causal attribution model to enhance the interpretability of large language models (LLMs) and improve their causal reasoning abilities via precise fine-tunin…
cs.CV2025
Source-free Semantic Regularization Learning for Semi-supervised Domain Adaptation
Xinyang Huang, Chuang Zhu, Ruiying Ren +2
Semi-supervised domain adaptation (SSDA) has been extensively researched due to its ability to improve classification performance and generalization ability of models by using a sm…
cs.CV2024
Learning Robust Correlation with Foundation Model for Weakly-Supervised Few-Shot Segmentation
Xinyang Huang, Chuang Zhu, Kebin Liu +2
Existing few-shot segmentation (FSS) only considers learning support-query correlation and segmenting unseen categories under the precise pixel masks. However, the cost of a large…