Measuring the Robustness of NLP Models to Domain Shifts

Measuring the Robustness of NLP Models to Domain Shifts

31 May 2023

Alexander Chapanin

Vitaly Shalumov

Papers citing "Measuring the Robustness of NLP Models to Domain Shifts"

11 / 11 papers shown

Title
Adapting Large Language Models for Multi-Domain Retrieval-Augmented-Generation Alexandre Misrahi Nadezhda Chirkova Maxime Louis Vassilina Nikoulina RALM 85 0 0 03 Apr 2025
Are LLMs Better than Reported? Detecting Label Errors and Mitigating Their Effect on Model Performance Omer Nahum Nitay Calderon Orgad Keller Idan Szpektor Roi Reichart 25 2 0 24 Oct 2024
On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMs Nitay Calderon Roi Reichart 40 10 0 27 Jul 2024
A Systematic Study of Knowledge Distillation for Natural Language Generation with Pseudo-Target Training Nitay Calderon Subhabrata Mukherjee Roi Reichart Amir Kantor 31 17 0 03 May 2023
The future is different: Large pre-trained language models fail in prediction tasks K. Cvejoski Ramses J. Sanchez C. Ojeda 22 3 0 01 Nov 2022
State-of-the-art generalisation research in NLP: A taxonomy and review Dieuwke Hupkes Mario Giulianelli Verna Dankers Mikel Artetxe Yanai Elazar ... Leila Khalatbari Maria Ryskina Rita Frieske Ryan Cotterell Zhijing Jin 114 93 0 06 Oct 2022
Measure and Improve Robustness in NLP Models: A Survey Xuezhi Wang Haohan Wang Diyi Yang 139 130 0 15 Dec 2021
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics Sebastian Gehrmann Tosin P. Adewumi Karmanya Aggarwal Pawan Sasanka Ammanamanchi Aremu Anuoluwapo ... Nishant Subramani Wei-ping Xu Diyi Yang Akhila Yerukola Jiawei Zhou VLM 254 285 0 02 Feb 2021
Robustness Gym: Unifying the NLP Evaluation Landscape Karan Goel Nazneen Rajani Jesse Vig Samson Tan Jason M. Wu Stephan Zheng Caiming Xiong Joey Tianyi Zhou Christopher Ré AAML OffRL OOD 154 136 0 13 Jan 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 241 1,919 0 31 Dec 2020
Domain Divergences: a Survey and Empirical Analysis Abhinav Ramesh Kashyap Devamanyu Hazarika Min-Yen Kan Roger Zimmermann 170 37 0 23 Oct 2020