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researcher

Xueqi Cheng

8 papers here

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

author position
  • last author6

Across the 6 of 8 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.IR2
  • cs.AI1
  • cs.CV1
  • cs.LG1
  • cs.SI1
ORCID 0000-0002-5201-8195
same name
  • Xueqi Cheng — 123 papers, h 75
  • Xueqi Cheng — 99 papers, h 14
  • Xueqi Cheng — 90 papers, h 22
  • Xueqi Cheng — 24 papers, h 13
  • Xueqi Cheng — 9 papers, h 2
  • Xueqi Cheng — 7 papers, h 14

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
20132025
most citedExploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis

6 citations · 10 across the 8 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.IR2025

LLM4MEA: Data-free Model Extraction Attacks on Sequential Recommenders via Large Language Models

Shilong Zhao, Fei Sun, Kaike Zhang +6

Recent studies have demonstrated the vulnerability of sequential recommender systems to Model Extraction Attacks (MEAs). MEAs collect responses from recommender systems to replicat…

cs.AI2025

A Survey of Link Prediction in N-ary Knowledge Graphs

Jiyao Wei, Saiping Guan, Da Li +3

N-ary Knowledge Graphs (NKGs) are a specialized type of knowledge graph designed to efficiently represent complex real-world facts. Unlike traditional knowledge graphs, where a fac…

cs.IR2025

Unleashing the Power of LLMs in Dense Retrieval with Query Likelihood Modeling

Hengran Zhang, Keping Bi, Jiafeng Guo +5

Dense retrieval is a crucial task in Information Retrieval (IR), serving as the basis for downstream tasks such as re-ranking and augmenting generation. Recently, large language mo…

cs.CL2025

Estimating Commonsense Plausibility through Semantic Shifts

Wanqing Cui, Wei Huang, Keping Bi +2

Commonsense plausibility estimation is critical for evaluating language models (LMs), yet existing generative approaches--reliant on likelihoods or verbalized judgments--struggle w…

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