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Wenqi Fan

The Hong Kong Polytechnic University

32 papers hereh-index 295.9k citations60 works total

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

author position
  • first author10
  • middle author20

Across the 30 of 32 papers where every author was matched, so the position is known.

fields
  • cs.IR17
  • cs.LG7
  • cs.CL4
  • cs.SI2
  • cs.AI1
  • cs.MM1
affiliations
  • The Hong Kong Polytechnic University
same name
  • Wenqi Fan — 35 papers, h 13
  • Wenqi Fan — 14 papers, h 3
  • Wenqi Fan — 11 papers, h 7
  • Wenqi Fan — 10 papers, h 8
  • Wenqi Fan — 4 papers, h 1
  • Wenqi Fan — 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
20192024
most citedRecommender Systems in the Era of Large Language Models (LLMs)

422 citations · 732 across the 27 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2024★ 3 cited

Large Language Models are In-Context Molecule Learners

Jiatong Li, Wei Liu, Zhihao Ding +3

Large Language Models (LLMs) have demonstrated exceptional performance in biochemical tasks, especially the molecule caption translation task, which aims to bridge the gap between…

cs.CL2023★ 5 cited

Certified Robustness for Large Language Models with Self-Denoising

Zhen Zhang, Guanhua Zhang, Bairu Hou +5

Although large language models (LLMs) have achieved great success in vast real-world applications, their vulnerabilities towards noisy inputs have significantly limited their uses,…

cs.CL2023★ 64 cited

Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective

Jiatong Li, Yunqing Liu, Wenqi Fan +4

Molecule discovery plays a crucial role in various scientific fields, advancing the design of tailored materials and drugs. However, most of the existing methods heavily rely on do…

cs.CL2019

Does Gender Matter? Towards Fairness in Dialogue Systems

Haochen Liu, Jamell Dacon, Wenqi Fan +3

Recently there are increasing concerns about the fairness of Artificial Intelligence (AI) in real-world applications such as computer vision and recommendations. For example, recog…

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