94 citations · 245 across the 21 of their papers we have counts for
6 papers · 1 filter
Scaling Law for Language Models Training Considering Batch Size
Xian Shuai, Yiding Wang, Yimeng Wu +2
Large language models (LLMs) have made remarkable advances in recent years, with scaling laws playing a critical role in this rapid progress. In this paper, we empirically investig…
SepLLM: Accelerate Large Language Models by Compressing One Segment into One Separator
Guoxuan Chen, Han Shi, Jiawei Li +7
Large Language Models (LLMs) have exhibited exceptional performance across a spectrum of natural language processing tasks. However, their substantial sizes pose considerable chall…
DAPE V2: Process Attention Score as Feature Map for Length Extrapolation
Chuanyang Zheng, Yihang Gao, Han Shi +9
The attention mechanism is a fundamental component of the Transformer model, contributing to interactions among distinct tokens, in contrast to earlier feed-forward neural networks…
DAPE: Data-Adaptive Positional Encoding for Length Extrapolation
Chuanyang Zheng, Yihang Gao, Han Shi +8
Positional encoding plays a crucial role in transformers, significantly impacting model performance and length generalization. Prior research has introduced absolute positional enc…
PixArt-Σ: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation
Junsong Chen, Chongjian Ge, Enze Xie +7
In this paper, we introduce PixArt-Σ, a Diffusion Transformer model~(DiT) capable of directly generating images at 4K resolution. PixArt-Σrepresents a significant advancement over…
A Survey of Reasoning with Foundation Models
Jiankai Sun, Chuanyang Zheng, Enze Xie +31
Reasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-world settings such as negotiation, medical diagnosis, and criminal investigation. It…