Small Language Models are Good Too: An Empirical Study of Zero-Shot Classification

17 April 2024

Papers citing "Small Language Models are Good Too: An Empirical Study of Zero-Shot Classification"

8 / 8 papers shown

Title
Integrating Language Models for Enhanced Network State Monitoring in DRL-Based SFC Provisioning Parisa Fard Moshiri Murat Arda Onsu Poonam Lohan Burak Kantarci Emil Janulewicz 34 0 0 16 Feb 2025
Small Language Models: Survey, Measurements, and Insights Zhenyan Lu Xiang Li Dongqi Cai Rongjie Yi Fangming Liu Xiwen Zhang Nicholas D. Lane Mengwei Xu ObjD LRM 47 31 0 24 Sep 2024
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes Lokesh Nagalapatti Chun-Liang Li Chih-Kuan Yeh Hootan Nakhost Yasuhisa Fujii Alexander Ratner Ranjay Krishna Chen-Yu Lee Tomas Pfister ALM 201 283 0 03 May 2023
LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions Minghao Wu Abdul Waheed Chiyu Zhang Muhammad Abdul-Mageed Alham Fikri Aji ALM 121 115 0 27 Apr 2023
Beyond Prompting: Making Pre-trained Language Models Better Zero-shot Learners by Clustering Representations Yu Fei Ping Nie Zhao Meng Roger Wattenhofer Mrinmaya Sachan VLM 35 20 0 29 Oct 2022
What Makes Pre-trained Language Models Better Zero-shot Learners? Jinghui Lu Dongsheng Zhu Weidong Han Rui Zhao Brian Mac Namee Fei Tan 34 21 0 30 Sep 2022
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 220 3,054 0 23 Jan 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 251 1,584 0 21 Jan 2020