8 citations · 22 across the 13 of their papers we have counts for
19 papers · 1 filter
AI translation of literary texts is "fine", but readers still prefer human translations
Yves Ferstler, Adam Podoxin, Ty Brassington +5
AI translation of literary works is increasingly common. While the content may be rendered adequately, we do not know enough about how readers experience it in terms of immersivene…
AI use in American newspapers is widespread, uneven, and rarely disclosed
Jenna Russell, Marzena Karpinska, Destiny Akinode +4
AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a large-scale dataset of 186K arti…
Preliminary Ranking of WMT25 General Machine Translation Systems
Tom Kocmi, Eleftherios Avramidis, Rachel Bawden +25
We present the preliminary rankings of machine translation (MT) systems submitted to the WMT25 General Machine Translation Shared Task, as determined by automatic evaluation metric…
An Interdisciplinary Approach to Human-Centered Machine Translation
Marine Carpuat, Omri Asscher, Kalika Bali +17
Machine Translation (MT) tools are widely used today, often in contexts where professional translators are not present. Despite progress in MT technology, a gap persists between sy…
OWL: Probing Cross-Lingual Recall of Memorized Texts via World Literature
Alisha Srivastava, Emir Korukluoglu, Minh Nhat Le +4
Large language models (LLMs) are known to memorize and recall English text from their pretraining data. However, the extent to which this ability generalizes to non-English languag…
Does quantization affect models' performance on long-context tasks?
Anmol Mekala, Anirudh Atmakuru, Yixiao Song +2
Large language models (LLMs) now support context windows exceeding 128K tokens, but this comes with significant memory requirements and high inference latency. Quantization can mit…