Cover Image

Fluency and Faithfulness in Human and Machine Literary Translation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Griebel, Sarah, Underwood, Ted
Format:	Preprint
Published:	2026
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Locating the Leading Edge of Cultural Change
by: Griebel, Sarah, et al.
Published: (2024)

How Good Are LLMs for Literary Translation, Really? Literary Translation Evaluation with Humans and LLMs
by: Zhang, Ran, et al.
Published: (2024)

Simpson's Paradox and the Accuracy-Fluency Tradeoff in Translation
by: Lim, Zheng Wei, et al.
Published: (2024)

Multiple References with Meaningful Variations Improve Literary Machine Translation
by: Wu, Si, et al.
Published: (2024)

Towards Tailored Recovery of Lexical Diversity in Literary Machine Translation
by: Ploeger, Esther, et al.
Published: (2024)

Creativity Bias: How Machine Evaluation Struggles with Creativity in Literary Translations
by: Gerrits, Kyo, et al.
Published: (2026)

(Perhaps) Beyond Human Translation: Harnessing Multi-Agent Collaboration for Translating Ultra-Long Literary Texts
by: Wu, Minghao, et al.
Published: (2024)

Can Language Models Represent the Past without Anachronism?
by: Underwood, Ted, et al.
Published: (2025)

"Once Upon a Time..." Literary Narrative Connectedness Progresses with Grade Level: Potential Impact on Reading Fluency and Literacy Skills
by: Ribeiro, Marina, et al.
Published: (2025)

Synthetic Fluency: Hallucinations, Confabulations, and the Creation of Irish Words in LLM-Generated Translations
by: Castilho, Sheila, et al.
Published: (2025)

Feeding Two Birds or Favoring One? Adequacy-Fluency Tradeoffs in Evaluation and Meta-Evaluation of Machine Translation
by: Shayegh, Behzad, et al.
Published: (2025)

Findings of the WMT 2024 Shared Task on Discourse-Level Literary Translation
by: Wang, Longyue, et al.
Published: (2024)

The Comparison of Translationese in Machine Translation and Human Transation in terms of Translation Relations
by: Zhou, Fan
Published: (2024)

Testing the Deliteralization Hypothesis in Human and Machine Translation
by: Marmonier, Malik, et al.
Published: (2026)

AI-Assisted Human Evaluation of Machine Translation
by: Zouhar, Vilém, et al.
Published: (2024)

From Babbling to Fluency: Evaluating the Evolution of Language Models in Terms of Human Language Acquisition
by: Yang, Qiyuan, et al.
Published: (2024)

To Diverge or Not to Diverge: A Morphosyntactic Perspective on Machine Translation vs Human Translation
by: Luo, Jiaming, et al.
Published: (2024)

Extending CREAMT: Leveraging Large Language Models for Literary Translation Post-Editing
by: Castaldo, Antonio, et al.
Published: (2025)

MAS-LitEval : Multi-Agent System for Literary Translation Quality Assessment
by: Kim, Junghwan, et al.
Published: (2025)

Can LLMs Simulate Human Behavioral Variability? A Case Study in the Phonemic Fluency Task
by: Qiu, Mengyang, et al.
Published: (2025)

Enhancing Human Evaluation in Machine Translation with Comparative Judgment
by: Song, Yixiao, et al.
Published: (2025)

A 2-step Framework for Automated Literary Translation Evaluation: Its Promises and Pitfalls
by: Shafayat, Sheikh, et al.
Published: (2024)

Context-Aware Monolingual Human Evaluation of Machine Translation
by: Picinini, Silvio, et al.
Published: (2025)

An Interdisciplinary Approach to Human-Centered Machine Translation
by: Carpuat, Marine, et al.
Published: (2025)

SAMAS: A Spectrum-Guided Multi-Agent System for Achieving Style Fidelity in Literary Translation
by: Wu, Jingzhuo, et al.
Published: (2026)

Exploring the Correlation between Human and Machine Evaluation of Simultaneous Speech Translation
by: Wang, Xiaoman, et al.
Published: (2024)

Aligning Neural Machine Translation Models: Human Feedback in Training and Inference
by: Ramos, Miguel Moura, et al.
Published: (2023)

Beyond Human-Only: Evaluating Human-Machine Collaboration for Collecting High-Quality Translation Data
by: Liu, Zhongtao, et al.
Published: (2024)

What Does LLM Refinement Actually Improve? A Systematic Study on Document-Level Literary Translation
by: Tan, Shaomu, et al.
Published: (2026)

FaithRL: Learning to Reason Faithfully through Step-Level Faithfulness Maximization
by: Gui, Runquan, et al.
Published: (2026)

On the Evaluation Practices in Multilingual NLP: Can Machine Translation Offer an Alternative to Human Translations?
by: Choenni, Rochelle, et al.
Published: (2024)

Steering LLMs toward Korean Local Speech: Iterative Refinement Framework for Faithful Dialect Translation
by: Park, Keunhyeung, et al.
Published: (2025)

Redefining Machine Simultaneous Interpretation: From Incremental Translation to Human-Like Strategies
by: Zhang, Qianen, et al.
Published: (2026)

Remedy: Learning Machine Translation Evaluation from Human Preferences with Reward Modeling
by: Tan, Shaomu, et al.
Published: (2025)

Error Span Annotation: A Balanced Approach for Human Evaluation of Machine Translation
by: Kocmi, Tom, et al.
Published: (2024)

Redefining Machine Simultaneous Interpretation: From Incremental Translation to Human-Like Strategies
by: Zhang, Qianen, et al.
Published: (2025)

Towards Chapter-to-Chapter Context-Aware Literary Translation via Large Language Models
by: Jin, Linghao, et al.
Published: (2024)

SimulPL: Aligning Human Preferences in Simultaneous Machine Translation
by: Yu, Donglei, et al.
Published: (2025)

Evaluating Human Alignment and Model Faithfulness of LLM Rationale
by: Fayyaz, Mohsen, et al.
Published: (2024)

Hindsight Quality Prediction Experiments in Multi-Candidate Human-Post-Edited Machine Translation
by: Marmonier, Malik, et al.
Published: (2026)