Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance

20 February 2024

Papers citing "Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance"

39 / 39 papers shown

Title
On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic Choices Branislav Pecher Ivan Srba Maria Bielikova 103 5 0 20 Feb 2024
Task Contamination: Language Models May Not Be Few-Shot Anymore Changmao Li Jeffrey Flanigan 122 98 0 26 Dec 2023
Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learning Lucas Weber Elia Bruni Dieuwke Hupkes 54 28 0 20 Oct 2023
Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting Melanie Sclar Yejin Choi Yulia Tsvetkov Alane Suhr 60 322 0 17 Oct 2023
Llama 2: Open Foundation and Fine-Tuned Chat Models Hugo Touvron Louis Martin Kevin R. Stone Peter Albert Amjad Almahairi ... Sharan Narang Aurelien Rodriguez Robert Stojnic Sergey Edunov Thomas Scialom AI4MH ALM 186 11,484 0 18 Jul 2023
Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study Peiyu Liu Zikang Liu Ze-Feng Gao Dawei Gao Wayne Xin Zhao Yaliang Li Bolin Ding Ji-Rong Wen MQ LRM 40 34 0 16 Jul 2023
Pushing the Limits of ChatGPT on NLP Tasks Xiaofei Sun Linfeng Dong Xiaoya Li Zhen Wan Shuhe Wang ... Jiwei Li Fei Cheng Lingjuan Lyu Fei Wu Guoyin Wang AI4MH LRM 56 29 0 16 Jun 2023
Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation Marius Mosbach Tiago Pimentel Shauli Ravfogel Dietrich Klakow Yanai Elazar 61 127 0 26 May 2023
Instruction Tuned Models are Quick Learners Himanshu Gupta Saurabh Arjun Sawant Swaroop Mishra Mutsumi Nakamura Arindam Mitra Santosh Mashetty Chitta Baral 51 26 0 17 May 2023
Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples! Yubo Ma Yixin Cao YongChing Hong Aixin Sun RALM 110 150 0 15 Mar 2023
Finding Support Examples for In-Context Learning Xiaonan Li Xipeng Qiu 55 92 0 27 Feb 2023
Do We Still Need Clinical Language Models? Eric P. Lehman Evan Hernandez Diwakar Mahajan Jonas Wulff Micah J. Smith Zachary M. Ziegler Daniel Nadler Peter Szolovits Alistair E. W. Johnson Emily Alsentzer LM&MA AI4MH 38 137 0 16 Feb 2023
Is ChatGPT a General-Purpose Natural Language Processing Task Solver? Chengwei Qin Aston Zhang Zhuosheng Zhang Jiaao Chen Michihiro Yasunaga Diyi Yang LM&MA AI4MH LRM ELM 109 689 0 08 Feb 2023
Data Curation Alone Can Stabilize In-context Learning Ting-Yun Chang Robin Jia 32 52 0 20 Dec 2022
In-context Examples Selection for Machine Translation Sweta Agrawal Chunting Zhou M. Lewis Luke Zettlemoyer Marjan Ghazvininejad LRM 69 191 0 05 Dec 2022
MEAL: Stable and Active Learning for Few-Shot Prompting Abdullatif Köksal Timo Schick Hinrich Schütze 54 25 0 15 Nov 2022
Active Example Selection for In-Context Learning Yiming Zhang Shi Feng Chenhao Tan SILM LRM 49 191 0 08 Nov 2022
Selective Annotation Makes Language Models Better Few-Shot Learners Hongjin Su Jungo Kasai Chen Henry Wu Weijia Shi Tianlu Wang ... Rui Zhang Mari Ostendorf Luke Zettlemoyer Noah A. Smith Tao Yu 53 251 0 05 Sep 2022
Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning Haokun Liu Derek Tam Mohammed Muqeeth Jay Mohta Tenghao Huang Joey Tianyi Zhou Colin Raffel 61 881 0 11 May 2022
PERFECT: Prompt-free and Efficient Few-shot Learning with Language Models Rabeeh Karimi Mahabadi Luke Zettlemoyer James Henderson Marzieh Saeidi Lambert Mathias Ves Stoyanov Majid Yazdani VLM 42 71 0 03 Apr 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 605 12,525 0 04 Mar 2022
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models Robert L Logan IV Ivana Balavzević Eric Wallace Fabio Petroni Sameer Singh Sebastian Riedel VPVLM 66 209 0 24 Jun 2021
LoRA: Low-Rank Adaptation of Large Language Models J. E. Hu Yelong Shen Phillip Wallis Zeyuan Allen-Zhu Yuanzhi Li Shean Wang Lu Wang Weizhu Chen OffRL AI4TS AI4CE ALM AIMat 149 9,946 0 17 Jun 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 307 1,152 0 18 Apr 2021
How Many Data Points is a Prompt Worth? Teven Le Scao Alexander M. Rush VLM 115 301 0 15 Mar 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 307 1,950 0 31 Dec 2020
It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners Timo Schick Hinrich Schütze 74 966 0 15 Sep 2020
On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines Marius Mosbach Maksym Andriushchenko Dietrich Klakow 59 355 0 08 Jun 2020
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 338 41,106 0 28 May 2020
Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping Jesse Dodge Gabriel Ilharco Roy Schwartz Ali Farhadi Hannaneh Hajishirzi Noah A. Smith 57 590 0 15 Feb 2020
Quantifying the Carbon Emissions of Machine Learning Alexandre Lacoste A. Luccioni Victor Schmidt Thomas Dandres 54 688 0 21 Oct 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy M. Lewis Luke Zettlemoyer Veselin Stoyanov AIMat 327 24,160 0 26 Jul 2019
BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions Christopher Clark Kenton Lee Ming-Wei Chang Tom Kwiatkowski Michael Collins Kristina Toutanova 121 1,475 0 24 May 2019
SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems Alex Jinpeng Wang Yada Pruksachatkun Nikita Nangia Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 137 2,287 0 02 May 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 655 93,936 0 11 Oct 2018
Neural Network Acceptability Judgments Alex Warstadt Amanpreet Singh Samuel R. Bowman 126 1,390 0 31 May 2018
Snips Voice Platform: an embedded Spoken Language Understanding system for private-by-design voice interfaces A. Coucke Alaa Saade Adrien Ball Théodore Bluche A. Caulier ... Thibault Gisselbrecht F. Caltagirone Thibaut Lavril Maël Primet Joseph Dureau SyDa 87 818 0 25 May 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 457 7,080 0 20 Apr 2018
Character-level Convolutional Networks for Text Classification Xiang Zhang Jiaqi Zhao Yann LeCun 159 6,046 0 04 Sep 2015