MEAL: Stable and Active Learning for Few-Shot Prompting

15 November 2022

Abdullatif Köksal

Hinrich Schütze

Papers citing "MEAL: Stable and Active Learning for Few-Shot Prompting"

21 / 21 papers shown

Title
Active Few-Shot Learning for Vertex Classification Starting from an Unlabeled Dataset Felix Burr Marcel Hoffmann A. Scherp SSL 174 0 0 25 Apr 2025
The Power of Adaptation: Boosting In-Context Learning through Adaptive Prompting Shuzhang Cai Twumasi Mensah-Boateng Xander Kuksov Jing Yuan Shaojie Tang 31 0 0 23 Dec 2024
DragEntity: Trajectory Guided Video Generation using Entity and Positional Relationships Zhang Wan Sheng Tang Jiawei Wei Ruize Zhang Juan Cao VGen 19 2 0 14 Oct 2024
LLMs vs Established Text Augmentation Techniques for Classification: When do the Benefits Outweight the Costs? Ján Cegin Jakub Simko Peter Brusilovsky 26 1 0 29 Aug 2024
Fighting Randomness with Randomness: Mitigating Optimisation Instability of Fine-Tuning using Delayed Ensemble and Noisy Interpolation Branislav Pecher Ján Cegin Róbert Belanec Jakub Simko Ivan Srba M. Bieliková 44 1 0 18 Jun 2024
Flexible and Adaptable Summarization via Expertise Separation Xiuying Chen Mingzhe Li Shen Gao Xin Cheng Qingqing Zhu Rui Yan Xin Gao Xiangliang Zhang MoE 41 3 0 08 Jun 2024
StablePT: Towards Stable Prompting for Few-shot Learning via Input Separation Xiaoming Liu Chen Liu Zhaohan Zhang Chengzhengxu Li Longtian Wang Y. Lan Chao Shen VLM 49 4 0 30 Apr 2024
On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic Choices Branislav Pecher Ivan Srba M. Bieliková 69 3 0 20 Feb 2024
Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance Branislav Pecher Ivan Srba M. Bieliková ALM 39 7 0 20 Feb 2024
Automatic Combination of Sample Selection Strategies for Few-Shot Learning Branislav Pecher Ivan Srba M. Bieliková Joaquin Vanschoren 34 1 0 05 Feb 2024
Effects of diversity incentives on sample diversity and downstream model performance in LLM-based text augmentation Ján Cegin Branislav Pecher Jakub Simko Ivan Srba M. Bieliková Peter Brusilovsky 33 10 0 12 Jan 2024
The language of prompting: What linguistic properties make a prompt successful? Alina Leidinger R. Rooij Ekaterina Shutova 38 43 0 03 Nov 2023
MorphPiece : A Linguistic Tokenizer for Large Language Models Jeffrey Hsu 24 3 0 14 Jul 2023
Do prompt positions really matter? Junyu Mao Stuart E. Middleton Mahesan Niranjan VLM 29 3 0 23 May 2023
Active Learning Principles for In-Context Learning with Large Language Models Katerina Margatina Timo Schick Nikolaos Aletras Jane Dwivedi-Yu 30 39 0 23 May 2023
Sociocultural knowledge is needed for selection of shots in hate speech detection tasks Antonis Maronikolakis Abdullatif Köksal Hinrich Schütze 43 0 0 04 Apr 2023
Active Prompting with Chain-of-Thought for Large Language Models Shizhe Diao Pengcheng Wang Yong Lin Tong Zhang ReLM KELM LLMAG LRM 31 120 0 23 Feb 2023
FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding Yanan Zheng Jing Zhou Yujie Qian Ming Ding Chonghua Liao Jian Li Ruslan Salakhutdinov Jie Tang Sebastian Ruder Zhilin Yang ELM 212 29 0 27 Sep 2021
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity Yao Lu Max Bartolo Alastair Moore Sebastian Riedel Pontus Stenetorp AILaw LRM 279 1,124 0 18 Apr 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 241 1,919 0 31 Dec 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 258 1,589 0 21 Jan 2020