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Mu Li

21 papers hereh-index 203.6k citations33 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author14
  • last author5

Across the 20 of 21 papers where every author was matched, so the position is known.

fields
  • cs.CV7
  • cs.CL6
  • cs.LG6
  • cs.DC1
  • cs.MM1
same name
  • Mu Li — 28 papers, h 26
  • Mu Li — 9 papers, h 30
  • Mu Li — 9 papers, h 10
  • Mu Li — 7 papers, h 15
  • Mu Li — 5 papers, h 8
  • Mu Li — 5 papers, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20142023
most citedAutomatic Chain of Thought Prompting in Large Language Models

237 citations · 652 across the 21 of their papers we have counts for

collaborators
Showing 2023 · cs.CLShow all

4 papers · 2 filters

cs.CL2023

Tailoring Instructions to Student's Learning Levels Boosts Knowledge Distillation

Yuxin Ren, Zihan Zhong, Xingjian Shi +3

It has been commonly observed that a teacher model with superior performance does not necessarily result in a stronger student, highlighting a discrepancy between current teacher t…

cs.CL2023★ 1 cited

A Cheaper and Better Diffusion Language Model with Soft-Masked Noise

Jiaao Chen, Aston Zhang, Mu Li +2

Diffusion models that are based on iterative denoising have been recently proposed and leveraged in various generation tasks like image generation. Whereas, as a way inherently bui…

cs.CL2023★ 100 cited

Multimodal Chain-of-Thought Reasoning in Language Models

Zhuosheng Zhang, Aston Zhang, Mu Li +3

Large language models (LLMs) have shown impressive performance on complex reasoning by leveraging chain-of-thought (CoT) prompting to generate intermediate reasoning chains as the…

cs.CL2023★ 17 cited

Parameter-Efficient Fine-Tuning Design Spaces

Jiaao Chen, Aston Zhang, Xingjian Shi +3

Parameter-efficient fine-tuning aims to achieve performance comparable to fine-tuning, using fewer trainable parameters. Several strategies (e.g., Adapters, prefix tuning, BitFit,…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.