| Challenge: | LaTeXMT is a software solution for structure-preserving, source-to-source translation of LaTex documents. |
| Approach: | They propose a software solution for structure-preserving, source-to-source translation of LaTeX documents . authors propose transformer-based language models which can be trained on plain text . |
| Outcome: | The proposed software is available under the LGPL-3.0 open-source licence and a web version is publicly available. |
Similar Papers
Proceedings of the Fourth Workshop on Discourse in Machine Translation (DiscoMT 2019) (D19-65)
Copied to clipboard
| Challenge: | . - (EN) |
| Approach: | . - (EN) |
| Outcome: | . - (EN) |
TransIns: Document Translation with Markup Reinsertion (2021.emnlp-demo)
Copied to clipboard
| Challenge: | MT models cannot translate complex formatted documents, as markup can be nested, apply to spans contiguous in source but non-contiguous. |
| Approach: | They propose a system for non-plain text document translation that reinserts markup into translated sentences using token alignments between source and target sentences. |
| Outcome: | The proposed system outperforms translation services in terms of markup quality . it integrates token alignments between source and target sentences to reinsert markup . the proposed system is available under the MIT license . |
LMDX: Language Model-based Document Information Extraction and Localization (2024.findings-acl)
Copied to clipboard
Vincent Perot, Kai Kang, Florian Luisier, Guolong Su, Xiaoyu Sun, Ramya Sree Boppana, Zilong Wang, Zifeng Wang, Jiaqi Mu, Hao Zhang, Chen-Yu Lee, Nan Hua
| Challenge: | Large Language Models have revolutionized Natural Language Processing but their application in extracting information from visually rich documents has not been successful. |
| Approach: | They propose a language model-based document information extraction and localization methodology to reframe the document information extract task for a LLM. |
| Outcome: | The proposed method enables extraction of singular, repeated, and hierarchical entities with and without training data. |
INMT: Interactive Neural Machine Translation Prediction (D19-3)
Copied to clipboard
| Challenge: | Existing MT systems are only useful for information assimilation, and require substantial manual post processing. |
| Approach: | They propose an Interactive Machine Translation interface that assists human translators with on-the-fly hints and suggestions. |
| Outcome: | The proposed interface makes the end-to-end translation process faster, more efficient and creates high-quality translations. |
Exploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literature (2022.emnlp-main)
Copied to clipboard
Katherine Thai, Marzena Karpinska, Kalpesh Krishna, Bill Ray, Moira Inghilleri, John Wieting, Mohit Iyyer
| Challenge: | Literary translation is a culturally significant task, but it is bottlenecked by the small number of qualified literary translators . a dataset of non-English language novels is used to study literary MT . |
| Approach: | They use a dataset of non-English language novels aligned to human and automatic English translations to study literary MT. |
| Outcome: | The proposed model prefers human translations over machine translations at a rate of 84% . state-of-the-art MT metrics do not correlate with preferences, the study finds . |
DOCmT5: Document-Level Pretraining of Multilingual Language Models (2022.findings-naacl)
Copied to clipboard
| Challenge: | DOCmT5 is a multilingual sequence-to-sequence language model pretraining with large-scale parallel documents. |
| Approach: | They propose a multilingual sequence-to-sequence language model pretrained with large-scale parallel documents. |
| Outcome: | The proposed model improves on baselines on document-level generation tasks. |
Exploring Discourse Structure in Document-level Machine Translation (2023.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods for document-level machine translation (DocMT) are under-utilizing the context. |
| Approach: | They propose a paragraph-to-paragraph translation mode that utilizes discourse information . they propose 'speech-based' translation mode which utilizes contextual information based on the context . |
| Outcome: | The proposed method utilizes discourse information and performs better than previous methods. |
Context-Interactive Pre-Training for Document Machine Translation (2021.naacl-main)
Copied to clipboard
| Challenge: | Document machine translation typically suffers from a lack of document-level bilingual data. |
| Approach: | They propose a document machine translation model that incorporates contextual information into the training signals by capturing cross-sentence dependency within the target document and cross sentence translation to make better use of contextual information. |
| Outcome: | The proposed model outperforms baselines on three benchmark datasets and significantly outperformed previous approaches. |
Multimodal Neural Machine Translation Using Synthetic Images Transformed by Latent Diffusion Model (2023.acl-srw)
Copied to clipboard
| Challenge: | Existing methods to translate source language sentences using images are not optimal for machine translation. |
| Approach: | They propose a new multimodal neural machine translation model using synthetic images transformed by a latent diffusion model. |
| Outcome: | The proposed model improves translation performance on English-German translation tasks using the Multi30k dataset. |
On Context Span Needed for Machine Translation Evaluation (2020.lrec-1)
Copied to clipboard
| Challenge: | a number of common patterns can be observed for context-aware MT evaluation, authors say . document-level evaluations have largely been performed at the sentence level . the definition of what constitutes a "document level" evaluation is still unclear . |
| Approach: | They propose to use a series of surveys to identify the necessary context span . they find common patterns that can be used to draw general guidelines . |
| Outcome: | The proposed evaluations of machine translation systems show that some issues and spans depend on domain and target language. |