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Qing Li

14 papers hereh-index 599 citations16 works total

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

author position
  • middle author2
  • last author12

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.IR6
  • cs.AI2
  • cs.CV2
  • cs.CE1
  • cs.CR1
  • cs.LG1
same name
  • Qing Li — 43 papers, h 56
  • Qing Li — 30 papers, h 15
  • Qing Li — 22 papers, h 16
  • Qing Li — 18 papers, h 7
  • Qing Li — 16 papers, h 19
  • Qing Li — 15 papers, h 23

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
20242026
most citedComputational Protein Science in the Era of Large Language Models (LLMs)

7 citations · 8 across the 13 of their papers we have counts for

collaborators
Showing 2025 · cs.IRShow all

4 papers · 2 filters

cs.IR2025

WebRec: Enhancing LLM-based Recommendations with Attention-guided RAG from Web

Zihuai Zhao, Yujuan Ding, Wenqi Fan +1

Recommender systems play a vital role in alleviating information overload and enriching users' online experience. In the era of large language models (LLMs), LLM-based recommender…

cs.IR2025

Continuous-time Discrete-space Diffusion Model for Recommendation

Chengyi Liu, Xiao Chen, Shijie Wang +2

In the era of information explosion, Recommender Systems (RS) are essential for alleviating information overload and providing personalized user experiences. Recent advances in dif…

cs.IR2025

Investigating and Mitigating Stereotype-aware Unfairness in LLM-based Recommendations

Zihuai Zhao, Wenqi Fan, Yao Wu +1

Large Language Models (LLMs) have demonstrated unprecedented language understanding and reasoning capabilities to capture diverse user preferences and advance personalized recommen…

cs.IR2025

Retrieval-Augmented Purifier for Robust LLM-Empowered Recommendation

Liangbo Ning, Wenqi Fan, Qing Li

Recently, Large Language Model (LLM)-empowered recommender systems have revolutionized personalized recommendation frameworks and attracted extensive attention. Despite the remarka…

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