1 citations · 1 across the 3 of their papers we have counts for
11 papers
Hearing to Translate: The Effectiveness of Speech Modality Integration into LLMs
Sara Papi, Javier Garcia Gilabert, Zachary Hopton +8
As Large Language Models (LLMs) expand beyond text, integrating speech as a native modality has given rise to SpeechLLMs, which directly process spoken language and enable speech-t…
Biased Tales: Cultural and Topic Bias in Generating Children's Stories
Donya Rooein, Vilém Zouhar, Debora Nozza +1
Stories play a pivotal role in human communication, shaping beliefs and morals, particularly in children. As parents increasingly rely on large language models (LLMs) to craft bedt…
How Important is `Perfect' English for Machine Translation Prompts?
Patrícia Schmidtová, Niyati Bafna, Seth Aycock +4
Large language models (LLMs) have achieved top results in recent machine translation evaluations, but they are also known to be sensitive to errors and perturbations in their promp…
Estimating Machine Translation Difficulty
Lorenzo Proietti, Stefano Perrella, Vilém Zouhar +2
Machine translation quality has steadily improved over the years, achieving near-perfect translations in recent benchmarks. These high-quality outputs make it difficult to distingu…
COMET-poly: Machine Translation Metric Grounded in Other Candidates
Maike Züfle, Vilém Zouhar, Tu Anh Dinh +3
Automated metrics for machine translation attempt to replicate human judgment. Unlike humans, who often assess a translation in the context of multiple alternatives, these metrics…
Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification
Chenfei Xiong, Jingwei Ni, Yu Fan +10
We introduce Co-DETECT (Collaborative Discovery of Edge cases in TExt ClassificaTion), a novel mixed-initiative annotation framework that integrates human expertise with automatic…