Fine-tuning Is a Surprisingly Effective Domain Adaptation Baseline in Handwriting Recognition

13 February 2023

Papers citing "Fine-tuning Is a Surprisingly Effective Domain Adaptation Baseline in Handwriting Recognition"

7 / 7 papers shown

Title
Practical Fine-Tuning of Autoregressive Models on Limited Handwritten Texts Jan Kohút Michal Hradiš 70 0 0 25 Mar 2025
Handwritten Text Recognition: A Survey Carlos Garrido-Munoz Antonio Ríos-Vila Jorge Calvo-Zaragoza 95 0 0 12 Feb 2025
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report Justin Zhao Timothy Wang Wael Abid Geoffrey Angus Arnav Garg Jeffery Kinnison Alex Sherstinsky Piero Molino Travis Addair Devvret Rishi ALM 39 28 0 29 Apr 2024
Towards Writing Style Adaptation in Handwriting Recognition Jan Kohút Michal Hradiš M. Kišš AI4TS 69 4 0 13 Feb 2023
SoftCTC -- Semi-Supervised Learning for Text Recognition using Soft Pseudo-Labels M. Kišš Michal Hradiš Karel Beneš Petr Buchal Michal Kula 44 4 0 05 Dec 2022
TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models Minghao Li Tengchao Lv Jingye Chen Lei Cui Yijuan Lu D. Florêncio Cha Zhang Zhoujun Li Furu Wei ViT 87 214 0 21 Sep 2021
AT-ST: Self-Training Adaptation Strategy for OCR in Domains with Limited Transcriptions M. Kišš Karel Beneš Michal Hradiš 52 13 0 27 Apr 2021