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Qiang Yang

25 papers hereh-index 16842 citations53 works total

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

author position
  • middle author3
  • last author16

Across the 19 of 25 papers where every author was matched, so the position is known.

fields
  • cs.LG13
  • cs.CR5
  • cs.CL4
  • cs.AI1
  • cs.CV1
  • cs.DC1
same name
  • Qiang Yang — 43 papers, h 58
  • Qiang Yang — 21 papers, h 110
  • Qiang Yang — 11 papers
  • Qiang Yang — 6 papers, h 3
  • Qiang Yang — 4 papers, h 3
  • Qiang Yang — 4 papers, h 1

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
20222026
most citedFATE-LLM: A Industrial Grade Federated Learning Framework for Large Language Models

33 citations · 38 across the 11 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2025

PPC-GPT: Federated Task-Specific Compression of Large Language Models via Pruning and Chain-of-Thought Distillation

Tao Fan, Guoqiang Ma, Yuanfeng Song +2

Compressing Large Language Models (LLMs) into task-specific Small Language Models (SLMs) encounters two significant challenges: safeguarding domain-specific knowledge privacy and m…

cs.CL2024

Federated Co-tuning Framework for Large and Small Language Models

Tao Fan, Yan Kang, Guoqiang Ma +4

By adapting Large Language Models (LLMs) to domain-specific tasks or enriching them with domain-specific knowledge, we can fully harness the capabilities of LLMs. Nonetheless, a ga…

cs.CL2024

FedCoT: Federated Chain-of-Thought Distillation for Large Language Models

Tao Fan, Weijing Chen, Yan Kang +5

Large Language Models (LLMs) have emerged as a transformative force in artificial intelligence, demonstrating exceptional proficiency across various tasks. However, their deploymen…

cs.CL2024

FedMKT: Federated Mutual Knowledge Transfer for Large and Small Language Models

Tao Fan, Guoqiang Ma, Yan Kang +5

Recent research in federated large language models (LLMs) has primarily focused on enabling clients to fine-tune their locally deployed homogeneous LLMs collaboratively or on trans…

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