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researcher

Zhenyu Wu

4 papers here

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

author position
  • first author2
  • middle author1
  • last author1

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

fields
  • cs.CL2
  • cs.IR1
  • cs.LG1
ORCID 0000-0003-0981-5567
same name
  • Zhenyu Wu — 32 papers, h 21
  • Zhenyu Wu — 8 papers
  • Zhenyu Wu — 8 papers
  • Zhenyu Wu — 5 papers
  • Zhenyu Wu — 4 papers
  • Zhenyu Wu — 4 papers

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 citedOpenICL: An Open-Source Framework for In-context Learning

1 citations · 1 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2024

Instructing Large Language Models to Identify and Ignore Irrelevant Conditions

Zhenyu Wu, Chao Shen, Meng Jiang

Math word problem (MWP) solving requires generating a reasoning path based on a given problem description that often contains irrelevant conditions. Existing chain-of-thought (CoT)…

cs.LG2024

Decoupled Federated Learning on Long-Tailed and Non-IID data with Feature Statistics

Zhuoxin Chen, Zhenyu Wu, Yang Ji

Federated learning is designed to enhance data security and privacy, but faces challenges when dealing with heterogeneous data in long-tailed and non-IID distributions. This paper…

cs.IR2023

Improvements on Recommender System based on Mathematical Principles

Fu Chen, Junkang Zou, Lingfeng Zhou +2

In this article, we will research the Recommender System's implementation about how it works and the algorithms used. We will explain the Recommender System's algorithms based on m…

cs.CL2023★ 1 cited

OpenICL: An Open-Source Framework for In-context Learning

Zhenyu Wu, YaoXiang Wang, Jiacheng Ye +4

In recent years, In-context Learning (ICL) has gained increasing attention and emerged as the new paradigm for large language model (LLM) evaluation. Unlike traditional fine-tuning…

◍wovepaper

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