3 citations · 4 across the 9 of their papers we have counts for
9 papers · 1 filter
Tracing Stereotypes from Representation to Output in Multilingual LLMs
Ariun-Erdene Tumurchuluun, Yusser Al Ghussin, Pinzhen Chen +2
Multilingual LLMs show stereotype-related behavior that varies across languages, but behavioral scores do not show where the relevant information is represented or how it affects t…
Last Translation Benchmark
Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…
Cultivar: A Contrastive and Locale-Oriented Translation Benchmark for Investigating Contamination and Localisation Robustness
Pinzhen Chen, Koel Dutta Chowdhury, Xiaoya Xu +20
Multilingual translation benchmarks are typically sourced in English and translated into other languages, treating language pairs as the unit of evaluation---a design that is prone…
When Flores Bloomz Wrong: Cross-Direction Contamination in Machine Translation Evaluation
David Tan, Pinzhen Chen, Josef van Genabith +1
Large language models (LLMs) can be benchmark-contaminated, resulting in inflated scores that mask memorization as generalization, and in multilingual settings, this memorization c…
PETra: A Multilingual Corpus of Pragmatic Explicitation in Translation
Doreen Osmelak, Koel Dutta Chowdhury, Uliana Sentsova +2
Translators often enrich texts with background details that make implicit cultural meanings explicit for new audiences. This phenomenon, known as pragmatic explicitation, has been…
Translating away Translationese without Parallel Data
Rricha Jalota, Koel Dutta Chowdhury, Cristina España-Bonet +1
Translated texts exhibit systematic linguistic differences compared to original texts in the same language, and these differences are referred to as translationese. Translationese…
Towards Debiasing Translation Artifacts
Koel Dutta Chowdhury, Rricha Jalota, Cristina España-Bonet +1
Cross-lingual natural language processing relies on translation, either by humans or machines, at different levels, from translating training data to translating test sets. However…
Comparing Feature-Engineering and Feature-Learning Approaches for Multilingual Translationese Classification
Daria Pylypenko, Kwabena Amponsah-Kaakyire, Koel Dutta Chowdhury +2
Traditional hand-crafted linguistically-informed features have often been used for distinguishing between translated and original non-translated texts. By contrast, to date, neural…
The RGNLP Machine Translation Systems for WAT 2018
Atul Kr. Ojha, Koel Dutta Chowdhury, Chao-Hong Liu +1
This paper presents the system description of Machine Translation (MT) system(s) for Indic Languages Multilingual Task for the 2018 edition of the WAT Shared Task. In our experimen…