19 citations · 49 across the 9 of their papers we have counts for
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cs.CL2023
Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer
Yuandong Tian, Yiping Wang, Beidi Chen +1
Transformer architecture has shown impressive performance in multiple research domains and has become the backbone of many neural network models. However, there is limited understa…
cs.CL2023
Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt
Zhaozhuo Xu, Zirui Liu, Beidi Chen +5
While the numerous parameters in Large Language Models (LLMs) contribute to their superior performance, this massive scale makes them inefficient and memory-hungry. Thus, they are…