5 citations · 12 across the 10 of their papers we have counts for
9 papers
CaMMT: Benchmarking Culturally Aware Multimodal Machine Translation
Emilio Villa-Cueva, Sholpan Bolatzhanova, Diana Turmakhan +32
Translating cultural content poses challenges for machine translation systems due to the differences in conceptualizations between cultures, where language alone may fail to convey…
IteRABRe: Iterative Recovery-Aided Block Reduction
Haryo Akbarianto Wibowo, Haiyue Song, Hideki Tanaka +3
Large Language Models (LLMs) have grown increasingly expensive to deploy, driving the need for effective model compression techniques. While block pruning offers a straightforward…
Pralekha: Cross-Lingual Document Alignment for Indic Languages
Sanjay Suryanarayanan, Haiyue Song, Mohammed Safi Ur Rahman Khan +2
Mining parallel document pairs for document-level machine translation (MT) remains challenging due to the limitations of existing Cross-Lingual Document Alignment (CLDA) techniques…
When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?
Zhuoyuan Mao, Chenhui Chu, Raj Dabre +3
Word alignment has proven to benefit many-to-many neural machine translation (NMT). However, high-quality ground-truth bilingual dictionaries were used for pre-editing in previous…
A System for Worldwide COVID-19 Information Aggregation
Akiko Aizawa, Frederic Bergeron, Junjie Chen +26
The global pandemic of COVID-19 has made the public pay close attention to related news, covering various domains, such as sanitation, treatment, and effects on education. Meanwhil…
JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation
Zhuoyuan Mao, Fabien Cromieres, Raj Dabre +2
Neural machine translation (NMT) needs large parallel corpora for state-of-the-art translation quality. Low-resource NMT is typically addressed by transfer learning which leverages…