Is Fine-tuning Needed? Pre-trained Language Models Are Near Perfect for
Out-of-Domain Detection

Is Fine-tuning Needed? Pre-trained Language Models Are Near Perfect for Out-of-Domain Detection

22 May 2023

Papers citing "Is Fine-tuning Needed? Pre-trained Language Models Are Near Perfect for Out-of-Domain Detection"

10 / 10 papers shown

Title
Shh, don't say that! Domain Certification in LLMs Cornelius Emde Alasdair Paren Preetham Arvind Maxime Kayser Tom Rainforth Thomas Lukasiewicz Bernard Ghanem Philip H. S. Torr Adel Bibi 33 1 0 26 Feb 2025
Multi-Task Model Merging via Adaptive Weight Disentanglement Feng Xiong Runxi Cheng Wang Chen Zhanqiu Zhang Yiwen Guo Chun Yuan Ruifeng Xu MoMe 80 4 0 10 Jan 2025
Process Reward Model with Q-Value Rankings W. Li Yixuan Li LRM 35 13 0 15 Oct 2024
Your Finetuned Large Language Model is Already a Powerful Out-of-distribution Detector Andi Zhang Tim Z. Xiao Weiyang Liu Robert Bamler Damon J. Wischik OODD 27 4 0 07 Apr 2024
How Useful is Continued Pre-Training for Generative Unsupervised Domain Adaptation? Rheeya Uppaal Yixuan Li Junjie Hu 16 4 0 31 Jan 2024
Mitigating Neural Network Overconfidence with Logit Normalization Hongxin Wei Renchunzi Xie Hao-Ran Cheng Lei Feng Bo An Yixuan Li OODD 158 258 0 19 May 2022
Types of Out-of-Distribution Texts and How to Detect Them Udit Arora William Huang He He OODD 198 97 0 14 Sep 2021
Revisiting Mahalanobis Distance for Transformer-Based Out-of-Domain Detection Alexander Podolskiy Dmitry Lipin A. Bout Ekaterina Artemova Irina Piontkovskaya OODD 78 70 0 11 Jan 2021
Calibration of Pre-trained Transformers Shrey Desai Greg Durrett UQLM 229 288 0 17 Mar 2020
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 294 6,003 0 20 Apr 2018