6 citations · 6 across the 5 of their papers we have counts for
5 papers
Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling
Changze Lv, Zhenghua Wang, Yiran Ding +9
Large Language Models (LLMs) still struggle with the ``lost-in-the-middle'' problem, where critical information located in the middle of long-context inputs is often underrepresent…
Layer-Specific Scaling of Positional Encodings for Superior Long-Context Modeling
Zhenghua Wang, Yiran Ding, Changze Lv +5
Although large language models (LLMs) have achieved significant progress in handling long-context inputs, they still suffer from the ``lost-in-the-middle'' problem, where crucial i…
Explainable Synthetic Image Detection through Diffusion Timestep Ensembling
Yixin Wu, Feiran Zhang, Tianyuan Shi +7
Recent advances in diffusion models have enabled the creation of deceptively real images, posing significant security risks when misused. In this study, we empirically show that di…
Searching for Best Practices in Retrieval-Augmented Generation
Xiaohua Wang, Zhenghua Wang, Xuan Gao +11
Retrieval-augmented generation (RAG) techniques have proven to be effective in integrating up-to-date information, mitigating hallucinations, and enhancing response quality, partic…
Towards Biologically Plausible Computing: A Comprehensive Comparison
Changze Lv, Yufei Gu, Zhengkang Guo +16
Backpropagation is a cornerstone algorithm in training neural networks for supervised learning, which uses a gradient descent method to update network weights by minimizing the dis…