4 papers
Beyond Scaling Laws: Understanding Transformer Performance with Associative Memory
Xueyan Niu, Bo Bai, Lei Deng +1
Increasing the size of a Transformer does not always lead to enhanced performance. This phenomenon cannot be explained by the empirical scaling laws. Furthermore, the model's enhan…
High Perceptual Quality Wireless Image Delivery with Denoising Diffusion Models
Selim F. Yilmaz, Xueyan Niu, Bo Bai +3
We consider the image transmission problem over a noisy wireless channel via deep learning-based joint source-channel coding (DeepJSCC) along with a denoising diffusion probabilist…
A Mean Field Ansatz for Zero-Shot Weight Transfer
Xingyuan Chen, Wenwei Kuang, Lei Deng +3
The pre-training cost of large language models (LLMs) is prohibitive. One cutting-edge approach to reduce the cost is zero-shot weight transfer, also known as model growth for some…
Retrieval Meets Reasoning: Dynamic In-Context Editing for Long-Text Understanding
Weizhi Fei, Xueyan Niu, Guoqing Xie +4
Current Large Language Models (LLMs) face inherent limitations due to their pre-defined context lengths, which impede their capacity for multi-hop reasoning within extensive textua…