23 citations · 55 across the 10 of their papers we have counts for
10 papers
MemInsight: Autonomous Memory Augmentation for LLM Agents
Rana Salama, Jason Cai, Michelle Yuan +4
Large language model (LLM) agents have evolved to intelligently process information, make decisions, and interact with users or tools. A key capability is the integration of long-t…
Fine-Tuned Machine Translation Metrics Struggle in Unseen Domains
Vilém Zouhar, Shuoyang Ding, Anna Currey +3
We introduce a new, extensive multidimensional quality metrics (MQM) annotated dataset covering 11 language pairs in the biomedical domain. We use this dataset to investigate wheth…
RAMP: Retrieval and Attribute-Marking Enhanced Prompting for Attribute-Controlled Translation
Gabriele Sarti, Phu Mon Htut, Xing Niu +4
Attribute-controlled translation (ACT) is a subtask of machine translation that involves controlling stylistic or linguistic attributes (like formality and gender) of translation o…
MT-GenEval: A Counterfactual and Contextual Dataset for Evaluating Gender Accuracy in Machine Translation
Anna Currey, Maria Nădejde, Raghavendra Pappagari +5
As generic machine translation (MT) quality has improved, the need for targeted benchmarks that explore fine-grained aspects of quality has increased. In particular, gender accurac…
Sockeye 3: Fast Neural Machine Translation with PyTorch
Felix Hieber, Michael Denkowski, Tobias Domhan +11
Sockeye 3 is the latest version of the Sockeye toolkit for Neural Machine Translation (NMT). Now based on PyTorch, Sockeye 3 provides faster model implementations and more advanced…
CoCoA-MT: A Dataset and Benchmark for Contrastive Controlled MT with Application to Formality
Maria Nădejde, Anna Currey, Benjamin Hsu +3
The machine translation (MT) task is typically formulated as that of returning a single translation for an input segment. However, in many cases, multiple different translations ar…
Faithful Target Attribute Prediction in Neural Machine Translation
Xing Niu, Georgiana Dinu, Prashant Mathur +1
The training data used in NMT is rarely controlled with respect to specific attributes, such as word casing or gender, which can cause errors in translations. We argue that predict…
Improving Gender Translation Accuracy with Filtered Self-Training
Prafulla Kumar Choubey, Anna Currey, Prashant Mathur +1
Targeted evaluations have found that machine translation systems often output incorrect gender, even when the gender is clear from context. Furthermore, these incorrectly gendered…
Multi-Source Syntactic Neural Machine Translation
Anna Currey, Kenneth Heafield
We introduce a novel multi-source technique for incorporating source syntax into neural machine translation using linearized parses. This is achieved by employing separate encoders…
The University of Edinburgh's Neural MT Systems for WMT17
Rico Sennrich, Alexandra Birch, Anna Currey +5
This paper describes the University of Edinburgh's submissions to the WMT17 shared news translation and biomedical translation tasks. We participated in 12 translation directions f…