4 citations · 4 across the 3 of their papers we have counts for
4 papers
MAGE: Multimodal Alignment and Generation Enhancement via Bridging Visual and Semantic Spaces
Shaojun E, Yuchen Yang, Jiaheng Wu +3
In the latest advancements in multimodal learning, effectively addressing the spatial and semantic losses of visual data after encoding remains a critical challenge. This is becaus…
DynaThink: Fast or Slow? A Dynamic Decision-Making Framework for Large Language Models
Jiabao Pan, Yan Zhang, Chen Zhang +3
Large language models (LLMs) have demonstrated emergent capabilities across diverse reasoning tasks via popular Chains-of-Thought (COT) prompting. However, such a simple and fast C…
Retrieval Augmented Instruction Tuning for Open NER with Large Language Models
Tingyu Xie, Jian Zhang, Yan Zhang +3
The strong capability of large language models (LLMs) has been applied to information extraction (IE) through either retrieval augmented prompting or instruction tuning (IT). Howev…
Training and inference of large language models using 8-bit floating point
Sergio P. Perez, Yan Zhang, James Briggs +6
FP8 formats are gaining popularity to boost the computational efficiency for training and inference of large deep learning models. Their main challenge is that a careful choice of…