Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems

Neeraj Varshney, Chitta Baral

Type: Preprint

Publication Date: 2022-01-01

Citations: 1

DOI: https://doi.org/10.48550/arxiv.2210.05528

View Publication

Locations

arXiv (Cornell University) - View - PDF
DataCite API - View

Similar Works

Action	Title	Year	Authors
+ PDF Chat	Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems	2022	Neeraj Varshney Chitta Baral
+	Efficient NLP Model Finetuning via Multistage Data Filtering	2022	Xu Ouyang Shahina Mohd Azam Ansari Felix Xiaozhu Lin Yangfeng Ji
+ PDF Chat	Leveraging Large Language Models for Enhanced NLP Task Performance through Knowledge Distillation and Optimized Training Strategies	2024	Yining Huang
+	Finding the SWEET Spot: Analysis and Improvement of Adaptive Inference in Low Resource Settings	2023	Daniel Rotem Michael Hassid Jonathan Mamou Roy Schwartz
+	Finding the SWEET Spot: Analysis and Improvement of Adaptive Inference in Low Resource Settings	2023	Daniel Rotem Michael Hassid Jonathan Mamou Roy Schwartz
+ PDF Chat	On Importance of Layer Pruning for Smaller BERT Models and Low Resource Languages	2025	Mayur Shirke Amey Shembade Madhushri Wagh Pavan Thorat Raviraj Joshi
+	Towards Improving Selective Prediction Ability of NLP Systems	2020	Neeraj Varshney Swaroop Mishra Chitta Baral
+	Towards Improving Selective Prediction Ability of NLP Systems	2022	Neeraj Varshney Swaroop Mishra Chitta Baral
+	Achieving Peak Performance for Large Language Models: A Systematic Review	2024	Zhyar Rzgar K. Rostam Sándor Szénási Gábor Kertész
+	Efficient NLP Model Finetuning via Multistage Data Filtering	2023	Xu Ouyang Shahina Mohd Azam Ansari Felix Xiaozhu Lin Yangfeng Ji
+	AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks	2023	Alexander Tornede Difan Deng Theresa Eimer Joseph Giovanelli Aditya Mohan Tim Ruhkopf Sarah Segel Daphne Theodorakopoulos Tanja Tornede Henning Wachsmuth
+	The Right Tool for the Job: Matching Model and Instance Complexities	2020	Roy Schwartz Gabriel Stanovsky Swabha Swayamdipta Jesse Dodge Noah A. Smith
+	The Right Tool for the Job: Matching Model and Instance Complexities	2020	Roy Schwartz Gabriel Stanovsky Swabha Swayamdipta Jesse Dodge Noah A. Smith
+	The Right Tool for the Job: Matching Model and Instance Complexities	2020	Roy Schwartz Gabriel Stanovsky Swabha Swayamdipta Jesse Dodge Noah A. Smith
+	CrossCheck: Rapid, Reproducible, and Interpretable Model Evaluation	2021	Dustin Arendt ZhuanYi Shaw Prasha Shrestha Ellyn Ayton Maria Glenski Svitlana Volkova
+	Dynabench: Rethinking Benchmarking in NLP	2021	Douwe Kiela Max Bartolo Yixin Nie Divyansh Kaushik Atticus Geiger Zhengxuan Wu Bertie Vidgen Grusha Prasad Amanpreet Singh Pratik Ringshia
+	Dynabench: Rethinking Benchmarking in NLP	2021	Douwe Kiela Max Bartolo Yixin Nie Divyansh Kaushik Atticus Geiger Zhengxuan Wu Bertie Vidgen Grusha Prasad Amanpreet Singh Pratik Ringshia
+	A Survey of Knowledge-Intensive NLP with Pre-Trained Language Models	2022	Da Yin Dong Li Hao Cheng Xiaodong Liu Kai-Wei Chang Furu Wei Jianfeng Gao
+	EasyNLP: A Comprehensive and Easy-to-use Toolkit for Natural Language Processing	2022	Chengyu Wang Minghui Qiu Taolin Zhang Tingting Liu Lei Li Jianing Wang Ming Wang Jun Huang Wei Lin
+ PDF Chat	SMART: Automatically Scaling Down Language Models with Accuracy Guarantees for Reduced Processing Fees	2024	Saehan Jo Immanuel Trummer

Works That Cite This (1)

Action	Title	Year	Authors
+ PDF Chat	Making Pre-trained Language Models both Task-solvers and Self-calibrators	2023	Yangyi Chen Xingyao Wang Heng Ji

Works Cited by This (0)

Action	Title	Year	Authors