{"total":30,"rows":[{"id":"2312.13585","title":"Speech Translation with Large Language Models: An Industrial Practice","created":"2023-12-21","cited_by_count":28,"area":null},{"id":"2306.03856","title":"Iterative Translation Refinement with Large Language Models","created":"2023-06-06","cited_by_count":27,"area":null},{"id":"2402.12025","title":"Speech Translation with Speech Foundation Models and Large Language Models: What is There and What is Missing?","created":"2024-02-19","cited_by_count":23,"area":null},{"id":"2405.20089","title":"The Fine-Tuning Paradox: Boosting Translation Quality Without Sacrificing LLM Abilities","created":"2024-05-30","cited_by_count":22,"area":null},{"id":"2503.04369","title":"Lost in Literalism: How Supervised Training Shapes Translationese in LLMs","created":"2025-03-06","cited_by_count":11,"area":null},{"id":"2311.02851","title":"Improving Machine Translation with Large Language Models: A Preliminary Study with Cooperative Decoding","created":"2023-11-06","cited_by_count":10,"area":null},{"id":"2401.01419","title":"To Diverge or Not to Diverge: A Morphosyntactic Perspective on Machine Translation vs Human Translation","created":"2024-01-02","cited_by_count":10,"area":null},{"id":"2410.00988","title":"Creative and Context-Aware Translation of East Asian Idioms with GPT-4","created":"2024-10-01","cited_by_count":10,"area":null},{"id":"2309.11668","title":"Towards Effective Disambiguation for Machine Translation with Large Language Models","created":"2023-09-20","cited_by_count":8,"area":null},{"id":"2309.17061","title":"SCALE: Synergized Collaboration of Asymmetric Language Translation Engines","created":"2023-09-29","cited_by_count":3,"area":null},{"id":"2310.14610","title":"That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context?","created":"2023-10-23","cited_by_count":3,"area":null},{"id":"2401.05072","title":"Aligning Translation-Specific Understanding to General Understanding in Large Language Models","created":"2024-01-10","cited_by_count":3,"area":null},{"id":"2504.03045","title":"Extending CREAMT: Leveraging Large Language Models for Literary Translation Post-Editing","created":"2025-04-03","cited_by_count":3,"area":null},{"id":"2602.03484","title":"Preferences for Idiomatic Language are Acquired Slowly -- and Forgotten Quickly: A Case Study on Swedish","created":"2026-02-03","cited_by_count":3,"area":null},{"id":"2310.15987","title":"Dissecting In-Context Learning of Translations in GPTs","created":"2023-10-24","cited_by_count":2,"area":null},{"id":"2506.00507","title":"Exploring In-context Example Generation for Machine Translation","created":"2025-05-31","cited_by_count":2,"area":null},{"id":"2410.03394","title":"Killing Two Flies with One Stone: An Attempt to Break LLMs Using English->Icelandic Idioms and Proper Names","created":"2024-10-04","cited_by_count":1,"area":null},{"id":"2505.21937","title":"Graph-Assisted Culturally Adaptable Idiomatic Translation for Indic Languages","created":"2025-05-28","cited_by_count":1,"area":null},{"id":"2312.10750","title":"Distinguishing Translations by Human, NMT, and ChatGPT: A Linguistic and Statistical Approach","created":"2023-12-17","cited_by_count":0,"area":null},{"id":"2403.14454","title":"Prediction of Translation Techniques for the Translation Process","created":"2024-03-21","cited_by_count":0,"area":null},{"id":"2406.07970","title":"Guiding In-Context Learning of LLMs through Quality Estimation for Machine Translation","created":"2024-06-12","cited_by_count":0,"area":null},{"id":"2412.09993","title":"Large Language Models for Persian $ \\leftrightarrow $ English Idiom Translation","created":"2024-12-13","cited_by_count":0,"area":null},{"id":"2506.13013","title":"Missing the human touch? A computational stylometry analysis of GPT-4 translations of online Chinese literature","created":"2025-06-16","cited_by_count":0,"area":null},{"id":"2509.22768","title":"ML2B: Benchmarking LLMs on Cross-Lingual ML Pipeline Generation","created":"2025-09-26","cited_by_count":0,"area":null},{"id":"2510.06866","title":"Unlocking Latent Discourse Translation in LLMs Through Quality-Aware Decoding","created":"2025-10-08","cited_by_count":0,"area":null},{"id":"2511.21761","title":"LLMs for Low-Resource Dialect Translation Using Context-Aware Prompting: A Case Study on Sylheti","created":"2025-11-24","cited_by_count":0,"area":null},{"id":"2603.08450","title":"A Dataset for Probing Translationese Preferences in English-to-Swedish Translation","created":"2026-03-09","cited_by_count":0,"area":null},{"id":"2604.10557","title":"LLMs Should Incorporate Explicit Mechanisms for Human Empathy","created":"2026-04-12","cited_by_count":0,"area":null},{"id":"2605.25686","title":"Testing the Deliteralization Hypothesis in Human and Machine Translation","created":"2026-05-25","cited_by_count":0,"area":null},{"id":"2606.10113","title":"Emotion Profiling in LLM-Based Literary Translation: Systematic Shifts Across MT and Post-Editing","created":"2026-06-08","cited_by_count":0,"area":null}],"next_cursor":null}