mlsanityData to 7 Oct 2026

compare-mt: A Tool for Holistic Comparison of Language Generation Systems

arXiv 1903.07926 ↗First posted 19 Mar 2019cs.CLcited by 43

Not on the map. Why?

Abstract (arXiv)

In this paper, we describe compare-mt, a tool for holistic analysis and comparison of the results of systems for language generation tasks such as machine translation. The main goal of the tool is to give the user a high-level and coherent view of the salient differences between systems that can then be used to guide further analysis or system improvement. It implements a number of tools to do so, such as analysis of accuracy of generation of particular types of words, bucketed histograms of sentence accuracies or counts based on salient characteristics, and extraction of characteristic n-grams for each system. It also has a number of advanced features such as use of linguistic labels, source side data, or comparison of log likelihoods for probabilistic models, and also aims to be easily extensible by users to new types of analysis. The code is available at https://github.com/neulab/compare-mt

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Mar 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 14; 2022: 11; 2023: 9; 2024: 4; 2025: 3; 2026: 2.

43 papers.

Sort:

By area:

  1. 2021Word Alignment by Fine-tuning Embeddings on Parallel Corporacited by 186
  2. 2021ExplainaBoard: An Explainable Leaderboard for NLPcited by 50
  3. 2023DINOISER: Diffused Conditional Sequence Learning by Manipulating Noisescited by 50
  4. 2021When Does Translation Require Context? A Data-driven, Multilingual Explorationcited by 36
  5. 2021Meta-Curriculum Learning for Domain Adaptation in Neural Machine Translationcited by 28
  6. 2021Towards More Fine-grained and Reliable NLP Performance Predictioncited by 26
  7. 2022CTC Alignments Improve Autoregressive Translationcited by 25
  8. 2022FOAM: A Follower-aware Speaker Model For Vision-and-Language Navigationcited by 22
  9. 2021The statistical advantage of automatic NLG metrics at the system levelcited by 18
  10. 2021TranSmart: A Practical Interactive Machine Translation Systemcited by 17
  11. 2021Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine Translationcited by 17
  12. 2021Meta Back-translationcited by 16
31 more
  1. 2021On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translationcited by 14
  2. 2021On the Language Coverage Bias for Neural Machine Translationcited by 12
  3. 2023Simple and Scalable Nearest Neighbor Machine Translationcited by 12
  4. 2022MMTAfrica: Multilingual Machine Translation for African Languagescited by 11
  5. 2023Angler: Helping Machine Translation Practitioners Prioritize Model Improvementscited by 11
  6. 2022Integrating Vectorized Lexical Constraints for Neural Machine Translationcited by 9
  7. 2022CipherDAug: Ciphertext based Data Augmentation for Neural Machine Translationcited by 9
  8. 2021What Do You Get When You Cross Beam Search with Nucleus Sampling?cited by 7
  9. 2022Improving Retrieval Augmented Neural Machine Translation by Controlling Source and Fuzzy-Match Interactionscited by 7
  10. 2023TabGenie: A Toolkit for Table-to-Text Generationcited by 7
  11. 2021An Exploration of Data Augmentation Techniques for Improving English to Tigrinya Translationcited by 6
  12. 2022Multi-Granularity Optimization for Non-Autoregressive Translationcited by 6
  13. 2022Non-Autoregressive Neural Machine Translation: A Call for Claritycited by 5
  14. 2022Local Byte Fusion for Neural Machine Translationcited by 5
  15. 2021Macro-Average: Rare Types Are Important Toocited by 4
  16. 2023Human-in-the-loop Machine Translation with Large Language Modelcited by 4
  17. 2023Towards Accurate Translation via Semantically Appropriate Application of Lexical Constraintscited by 3
  18. 2024Gloss2Text: Sign Language Gloss translation using LLMs and Semantically Aware Label Smoothingcited by 3
  19. 2024BinaryAlign: Word Alignment as Binary Sequence Labelingcited by 3
  20. 2022Improving Robustness of Retrieval Augmented Translation via Shuffling of Suggestionscited by 2
  21. 2023Revisiting Non-Autoregressive Translation at Scalecited by 2
  22. 2023The Unreasonable Effectiveness of Random Target Embeddings for Continuous-Output Neural Machine Translationcited by 2
  23. 2025Exploring In-context Example Generation for Machine Translationcited by 2
  24. 2025Relation Extraction or Pattern Matching? Unravelling the Generalisation Limits of Language Models for Biographical REcited by 1
  25. 2025Angular Dispersion Accelerates k-Nearest Neighbors Machine Translationcited by 1
  26. 2022Third-Party Aligner for Neural Word Alignmentscited by 0
  27. 2023Towards Reliable Neural Machine Translation with Consistency-Aware Meta-Learningcited by 0
  28. 2024Deterministic Reversible Data Augmentation for Neural Machine Translationcited by 0
  29. 2024MT-LENS: An all-in-one Toolkit for Better Machine Translation Evaluationcited by 0
  30. 2026Representation Collapse in Machine Translation Through the Lens of Angular Dispersioncited by 0
  31. 2026string2string Studio: An Interactive, In-Browser Platform for String-to-String Algorithmscited by 0