---
title: "Yicheng Fu — papers of 2022 — 1 paper, the most cited first"
description: "Yicheng Fu — papers of 2022: 1 paper on Elamur Research, the most cited first — what each work is about in our own words."
canonical: "https://research.elamur.ai/free/en/authors/yicheng-fu/year/2022/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yicheng-fu/year/2022/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Yicheng Fu](https://md.research.elamur.ai/free/en/authors/yicheng-fu/) / 2022

# Yicheng Fu — papers of 2022 — 1 paper, the most cited first

1 paper · [all years of Yicheng Fu](https://md.research.elamur.ai/free/en/authors/yicheng-fu/#years)

**[P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks](https://md.research.elamur.ai/free/en/papers/liu-2022-p-tuning-prompt-tuning-can/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiao Liu, Kaixuan Ji, Yicheng Fu, et al.*2022 · 1,017 citations*