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Yemin Shi

7 papers hereh-index 6744 citations13 works total

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

author position
  • first author1
  • middle author3
  • last author2

Across the 6 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • cs.AI2
  • cs.CV1
  • cs.SD1
same name
  • Yemin Shi — 8 papers, h 9
  • Yemin Shi — 3 papers, h 3
  • Yemin Shi — 2 papers, h 2
  • Yemin Shi — 1 paper

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
20232026
most citedMERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training

28 citations · 54 across the 7 of their papers we have counts for

collaborators
Showing 2023Show all

4 papers · 1 filter

cs.CL2023★ 6 cited

LLaSM: Large Language and Speech Model

Yu Shu, Siwei Dong, Guangyao Chen +5

Multi-modal large language models have garnered significant interest recently. Though, most of the works focus on vision-language multi-modal models providing strong capabilities i…

cs.AI2023★ 7 cited

AutoAgents: A Framework for Automatic Agent Generation

Guangyao Chen, Siwei Dong, Yu Shu +5

Large language models (LLMs) have enabled remarkable advances in automated task-solving with multi-agent systems. However, most existing LLM-based multi-agent approaches rely on pr…

cs.SD2023★ 28 cited

MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training

Yizhi Li, Ruibin Yuan, Ge Zhang +17

Self-supervised learning (SSL) has recently emerged as a promising paradigm for training generalisable models on large-scale data in the fields of vision, text, and speech. Althoug…

cs.CL2023★ 10 cited

Chinese Open Instruction Generalist: A Preliminary Release

Ge Zhang, Yemin Shi, Ruibo Liu +9

Instruction tuning is widely recognized as a key technique for building generalist language models, which has attracted the attention of researchers and the public with the release…

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