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Hui Xiong

6 papers hereh-index 6259 citations10 works total

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

author position
  • last author6

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

fields
  • cs.IR4
  • cs.AI1
  • cs.MA1
same name
  • Hui Xiong — 30 papers, h 73
  • Hui Xiong — 26 papers, h 34
  • Hui Xiong — 18 papers, h 16
  • Hui Xiong — 17 papers, h 6
  • Hui Xiong — 17 papers, h 3
  • Hui Xiong — 13 papers, h 7

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 citedDynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation

16 citations · 30 across the 5 of their papers we have counts for

collaborators
Showing cs.IRShow all

4 papers · 1 filter

cs.IR2025★ 13 cited

Unleashing the Power of Large Language Model for Denoising Recommendation

Shuyao Wang, Zhi Zheng, Yongduo Sui +1

Recommender systems are crucial for personalizing user experiences but often depend on implicit feedback data, which can be noisy and misleading. Existing denoising studies involve…

cs.IR2024

Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation

Yuyang Ye, Zhi Zheng, Yishan Shen +6

Recent advances in Large Language Models (LLMs) have demonstrated significant potential in the field of Recommendation Systems (RSs). Most existing studies have focused on converti…

cs.IR2024★ 1 cited

Harnessing Large Language Models for Text-Rich Sequential Recommendation

Zhi Zheng, Wenshuo Chao, Zhaopeng Qiu +2

Recent advances in Large Language Models (LLMs) have been changing the paradigm of Recommender Systems (RS). However, when items in the recommendation scenarios contain rich textua…

cs.IR2024★ 16 cited

Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation

Shuyao Wang, Yongduo Sui, Jiancan Wu +2

In the realm of deep learning-based recommendation systems, the increasing computational demands, driven by the growing number of users and items, pose a significant challenge to p…

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