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researcher

Xiaolei Wang

4 papers here

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

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.IR1
  • cs.LG1
ORCID 0000-0003-3685-3606
same name
  • Xiaolei Wang — 3 papers, h 9
  • Xiaolei Wang — 3 papers
  • Xiaolei Wang — 3 papers
  • Xiaolei Wang — 1 paper
  • Xiaolei Wang — 1 paper, h 10
  • Xiaolei Wang — 1 paper

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

most citedAlleviating the Long-Tail Problem in Conversational Recommender Systems

17 citations · 18 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2024

YuLan: An Open-source Large Language Model

Yutao Zhu, Kun Zhou, Kelong Mao +35

Large language models (LLMs) have become the foundation of many applications, leveraging their extensive capabilities in processing and understanding natural language. While many o…

cs.LG2024

Investigating the Pre-Training Dynamics of In-Context Learning: Task Recognition vs. Task Learning

Xiaolei Wang, Xinyu Tang, Wayne Xin Zhao +1

The emergence of in-context learning (ICL) is potentially attributed to two major abilities: task recognition (TR) for recognizing the task from demonstrations and utilizing pre-tr…

cs.CL2024★ 1 cited

Are Large Language Models Good Prompt Optimizers?

Ruotian Ma, Xiaolei Wang, Xin Zhou +5

LLM-based Automatic Prompt Optimization, which typically utilizes LLMs as Prompt Optimizers to self-reflect and refine prompts, has shown promising performance in recent studies. D…

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…

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