5 papers
BaRA: Bayesian Adaptive Rank Allocation for Parameter-Efficient Fine-Tuning
Zhibin Duan, Yuhong Wang, Jiahong Fu +3
While Low-rank adaptation (LoRA) enables highly efficient fine-tuning by constraining task-specific updates to fixed low-rank subspaces, this rigid design limits representational f…
Beyond Spectral Decomposition: Bayesian Contrastive Learning and its Non-negative Formulation via Factor Analysis
Zhibin Duan, Tiansheng Wen, Yifei Wang +3
Factor analysis, often regarded as a Bayesian variant of matrix factorization, offers superior capabilities in capturing uncertainty, modeling complex dependencies, and ensuring ro…
Mitigating Reward Hacking in RLHF via Bayesian Non-negative Reward Modeling
Zhibin Duan, Guowei Rong, Zhuo Li +3
Reward models learned from human preferences are central to aligning large language models (LLMs) via reinforcement learning from human feedback, yet they are often vulnerable to r…
Disentangled Generative Graph Representation Learning
Xinyue Hu, Zhibin Duan, Xinyang Liu +6
Recently, generative graph models have shown promising results in learning graph representations through self-supervised methods. However, most existing generative graph representa…
Enhancing Uncertainty Estimation and Interpretability via Bayesian Non-negative Decision Layer
Xinyue Hu, Zhibin Duan, Bo Chen +1
Although deep neural networks have demonstrated significant success due to their powerful expressiveness, most models struggle to meet practical requirements for uncertainty estima…