4 citations · 5 across the 4 of their papers we have counts for
4 papers
Kwai Summary Attention Technical Report
Chenglong Chu, Guorui Zhou, Guowang Zhang +35
Long-context ability, has become one of the most important iteration direction of next-generation Large Language Models, particularly in semantic understanding/reasoning, code agen…
Retrieval Head Mechanistically Explains Long-Context Factuality
Wenhao Wu, Yizhong Wang, Guangxuan Xiao +2
Despite the recent progress in long-context language models, it remains elusive how transformer-based models exhibit the capability to retrieve relevant information from arbitrary…
Data Engineering for Scaling Language Models to 128K Context
Yao Fu, Rameswar Panda, Xinyao Niu +4
We study the continual pretraining recipe for scaling language models' context lengths to 128K, with a focus on data engineering. We hypothesize that long context modeling, in part…
FiLM: Fill-in Language Models for Any-Order Generation
Tianxiao Shen, Hao Peng, Ruoqi Shen +3
Language models have become the backbone of today's AI systems. However, their predominant left-to-right generation limits the use of bidirectional context, which is essential for…