105 citations · 349 across the 67 of their papers we have counts for
13 papers · 1 filter
Toward Machine Translation Literacy: How Lay Users Perceive and Rely on Imperfect Translations
Yimin Xiao, Yongle Zhang, Dayeon Ki +5
As Machine Translation (MT) becomes increasingly commonplace, understanding how the general public perceives and relies on imperfect MT is crucial for contextualizing MT research i…
Linguistic Nepotism: Trading-off Quality for Language Preference in Multilingual RAG
Dayeon Ki, Marine Carpuat, Paul McNamee +4
Multilingual Retrieval-Augmented Generation (mRAG) systems enable language models to answer knowledge-intensive queries with citation-supported responses across languages. Despite…
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…
Steering Large Language Models with Register Analysis for Arbitrary Style Transfer
Xinchen Yang, Marine Carpuat
Large Language Models (LLMs) have demonstrated strong capabilities in rewriting text across various styles. However, effectively leveraging this ability for example-based arbitrary…
Should I Share this Translation? Evaluating Quality Feedback for User Reliance on Machine Translation
Dayeon Ki, Kevin Duh, Marine Carpuat
As people increasingly use AI systems in work and daily life, feedback mechanisms that help them use AI responsibly are urgently needed, particularly in settings where users are no…
Multiple LLM Agents Debate for Equitable Cultural Alignment
Dayeon Ki, Rachel Rudinger, Tianyi Zhou +1
Large Language Models (LLMs) need to adapt their predictions to diverse cultural contexts to benefit diverse communities across the world. While previous efforts have focused on si…
VietMix: A Naturally-Occurring Parallel Corpus and Augmentation Framework for Vietnamese-English Code-Mixed Machine Translation
Hieu Tran, Phuong-Anh Nguyen-Le, Huy Nghiem +3
Machine translation (MT) systems universally degrade when faced with code-mixed text. This problem is more acute for low-resource languages that lack dedicated parallel corpora. Th…
GraphicBench: A Planning Benchmark for Graphic Design with Language Agents
Dayeon Ki, Tianyi Zhou, Marine Carpuat +3
Large Language Model (LLM)-powered agents have unlocked new possibilities for automating human tasks. While prior work has focused on well-defined tasks with specified goals, the c…
AskQE: Question Answering as Automatic Evaluation for Machine Translation
Dayeon Ki, Kevin Duh, Marine Carpuat
How can a monolingual English speaker determine whether an automatic translation in French is good enough to be shared? Existing MT error detection and quality estimation (QE) tech…
Can you map it to English? The Role of Cross-Lingual Alignment in Multilingual Performance of LLMs
Kartik Ravisankar, Hyojung Han, Sarah Wiegreffe +1
Large language models (LLMs) can answer prompts in many languages, despite being trained predominantly on English; yet, the mechanisms driving this generalization remain poorly und…
Words as Bridges: Exploring Computational Support for Cross-Disciplinary Translation Work
Calvin Bao, Yow-Ting Shiue, Marine Carpuat +1
Scholars often explore literature outside of their home community of study. This exploration process is frequently hampered by field-specific jargon. Past computational work often…
Sustaining Human Agency, Attending to Its Cost: An Investigation into Generative AI Design for Non-Native Speakers' Language Use
Yimin Xiao, Cartor Hancock, Sweta Agrawal +4
AI systems and tools today can generate human-like expressions on behalf of people. It raises the crucial question about how to sustain human agency in AI-mediated communication. W…
Automatic Input Rewriting Improves Translation with Large Language Models
Dayeon Ki, Marine Carpuat
Can we improve machine translation (MT) with LLMs by rewriting their inputs automatically? Users commonly rely on the intuition that well-written text is easier to translate when u…