Changhao Li
THU Undergrad, NLPer
THU Undergrad, NLPer
Published in NeurIPS, 2023
The paper proposes a way to train Transformer architect models in 4-bit quantization. It can be implemented on current generation of GPU and is faster than FP16 counterparts
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Published in , 2024
The paper proposes a lightweight white-box LLM controller that guides large-scale black-box LLM generator by decomposing complex tasks. It can enhance capabilities of black-box LLMs in reasoning, planning and personalization tasks.
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