ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2207.11680
  4. Cited By
No More Fine-Tuning? An Experimental Evaluation of Prompt Tuning in Code
  Intelligence

No More Fine-Tuning? An Experimental Evaluation of Prompt Tuning in Code Intelligence

24 July 2022
Chaozheng Wang
Yuanhang Yang
Cuiyun Gao
Yun Peng
Hongyu Zhang
Michael R. Lyu
    AAML
ArXivPDFHTML

Papers citing "No More Fine-Tuning? An Experimental Evaluation of Prompt Tuning in Code Intelligence"

10 / 10 papers shown
Title
Enhancing Code Generation via Bidirectional Comment-Level Mutual Grounding
Enhancing Code Generation via Bidirectional Comment-Level Mutual Grounding
Yifeng Di
Tianyi Zhang
26
0
0
12 May 2025
PLHF: Prompt Optimization with Few-Shot Human Feedback
PLHF: Prompt Optimization with Few-Shot Human Feedback
Chun-Pai Yang
Kan Zheng
Shou-De Lin
21
0
0
11 May 2025
Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit
Deep Learning for Code Intelligence: Survey, Benchmark and Toolkit
Yao Wan
Yang He
Zhangqian Bi
Jianguo Zhang
Hongyu Zhang
Yulei Sui
Guandong Xu
Hai Jin
Philip S. Yu
27
20
0
30 Dec 2023
A Comprehensive Evaluation of Parameter-Efficient Fine-Tuning on
  Software Engineering Tasks
A Comprehensive Evaluation of Parameter-Efficient Fine-Tuning on Software Engineering Tasks
Wentao Zou
Qi Li
Jidong Ge
Chuanyi Li
Xiaoyu Shen
LiGuo Huang
Bin Luo
24
5
0
25 Dec 2023
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally
  Across Scales and Tasks
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks
Xiao Liu
Kaixuan Ji
Yicheng Fu
Weng Lam Tam
Zhengxiao Du
Zhilin Yang
Jie Tang
VLM
238
805
0
14 Oct 2021
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for
  Code Understanding and Generation
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation
Yue Wang
Weishi Wang
Shafiq R. Joty
S. Hoi
235
1,489
0
02 Sep 2021
The Power of Scale for Parameter-Efficient Prompt Tuning
The Power of Scale for Parameter-Efficient Prompt Tuning
Brian Lester
Rami Al-Rfou
Noah Constant
VPVLM
280
3,844
0
18 Apr 2021
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding
  and Generation
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
Shuai Lu
Daya Guo
Shuo Ren
Junjie Huang
Alexey Svyatkovskiy
...
Nan Duan
Neel Sundaresan
Shao Kun Deng
Shengyu Fu
Shujie Liu
ELM
198
1,105
0
09 Feb 2021
Exploiting Cloze Questions for Few Shot Text Classification and Natural
  Language Inference
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference
Timo Schick
Hinrich Schütze
258
1,587
0
21 Jan 2020
Language Models as Knowledge Bases?
Language Models as Knowledge Bases?
Fabio Petroni
Tim Rocktaschel
Patrick Lewis
A. Bakhtin
Yuxiang Wu
Alexander H. Miller
Sebastian Riedel
KELM
AI4MH
415
2,584
0
03 Sep 2019
1