Translation
3193 papers with code • 2 benchmarks • 14 datasets
Benchmarks
These leaderboards are used to track progress in Translation
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Libraries
Use these libraries to find Translation models and implementationsDatasets
xP3
CVSS
Oxford Radar RobotCar Dataset
Duolingo STAPLE Shared Task
Demetr
SpeechMatrix
ACES
FRMT
MuLD
Latest papers with no code
SGHateCheck: Functional Tests for Detecting Hate Speech in Low-Resource Languages of Singapore
To address the limitations of current hate speech detection models, we introduce \textsf{SGHateCheck}, a novel framework designed for the linguistic and cultural context of Singapore and Southeast Asia.
A Hong Kong Sign Language Corpus Collected from Sign-interpreted TV News
The dataset is collected to enrich resources for HKSL and support research in large-vocabulary continuous sign language recognition (SLR) and translation (SLT).
Multivariate trace estimation using quantum state space linear algebra
In this paper, we present a quantum algorithm for approximating multivariate traces, i. e. the traces of matrix products.
Reinforcement Learning for Edit-Based Non-Autoregressive Neural Machine Translation
Non-autoregressive (NAR) language models are known for their low latency in neural machine translation (NMT).
The IgboAPI Dataset: Empowering Igbo Language Technologies through Multi-dialectal Enrichment
The Igbo language is facing a risk of becoming endangered, as indicated by a 2025 UNESCO study.
Suvach -- Generated Hindi QA benchmark
Current evaluation benchmarks for question answering (QA) in Indic languages often rely on machine translation of existing English datasets.
Which Nigerian-Pidgin does Generative AI speak?: Issues about Representativeness and Bias for Multilingual and Low Resource Languages
Although it has mainly been a spoken language until recently, there are currently two written genres (BBC and Wikipedia) in Naija.
Modeling Orthographic Variation Improves NLP Performance for Nigerian Pidgin
We test the effect of this data augmentation on two critical NLP tasks: machine translation and sentiment analysis.
Usefulness of Emotional Prosody in Neural Machine Translation
In this work, we propose to improve translation quality by adding another external source of information: the automatically recognized emotion in the voice.
Quality Estimation with $k$-nearest Neighbors and Automatic Evaluation for Model-specific Quality Estimation
Providing quality scores along with Machine Translation (MT) output, so-called reference-free Quality Estimation (QE), is crucial to inform users about the reliability of the translation.
