◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Xiaolei Wang

Renmin University of China

16 papers hereh-index 105.2k citations19 works total

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

author position
  • first author5
  • middle author10

Across the 15 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CL10
  • cs.IR4
  • cs.AI1
  • cs.LG1
affiliations
  • Renmin University of China
same name
  • Xiaolei Wang — 5 papers, h 10
  • Xiaolei Wang — 4 papers, h 9
  • Xiaolei Wang — 4 papers, h 5
  • Xiaolei Wang — 4 papers, h 17
  • Xiaolei Wang — 3 papers, h 2
  • Xiaolei Wang — 2 papers, h 3

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
20212026
most citedA Survey of Large Language Models

1.5k citations · 1.8k across the 16 of their papers we have counts for

collaborators
Showing cs.IRShow all

4 papers · 1 filter

cs.IR2025

LARES: Latent Reasoning for Sequential Recommendation

Enze Liu, Bowen Zheng, Xiaolei Wang +4

Sequential recommender systems have become increasingly important in real-world applications that model user behavior sequences to predict their preferences. However, existing sequ…

cs.IR2025

DeepRec: Towards a Deep Dive Into the Item Space with Large Language Model Based Recommendation

Bowen Zheng, Xiaolei Wang, Enze Liu +5

Recently, large language models (LLMs) have been introduced into recommender systems (RSs), either to enhance traditional recommendation models (TRMs) or serve as recommendation ba…

cs.IR2025

Search-Based Interaction For Conversation Recommendation via Generative Reward Model Based Simulated User

Xiaolei Wang, Chunxuan Xia, Junyi Li +5

Conversational recommendation systems (CRSs) use multi-turn interaction to capture user preferences and provide personalized recommendations. A fundamental challenge in CRSs lies i…

cs.IR2023★ 17 cited

Alleviating the Long-Tail Problem in Conversational Recommender Systems

Zhipeng Zhao, Kun Zhou, Xiaolei Wang +4

Conversational recommender systems (CRS) aim to provide the recommendation service via natural language conversations. To develop an effective CRS, high-quality CRS datasets are ve…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.