7 citations · 8 across the 12 of their papers we have counts for
12 papers
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…
Omnilingual SONAR: Cross-Lingual and Cross-Modal Sentence Embeddings Bridging Massively Multilingual Text and Speech
Omnilingual SONAR Team, João Maria Janeiro, Pere-Lluís Huguet Cabot +17
Cross-lingual sentence encoders typically cover only a few hundred languages and often trade downstream quality for stronger alignment, limiting their adoption. We introduce OmniSO…
XL-Suite: Cross-Lingual Synthetic Training and Evaluation Data for Open-Ended Generation
Vivek Iyer, Pinzhen Chen, Ricardo Rei +1
Cross-lingual open-ended generation - responding in a language different from that of the query - is an important yet understudied problem. This work proposes XL-Instruct, a novel…
Cultural Adaptation of Menus: A Fine-Grained Approach
Zhonghe Zhang, Xiaoyu He, Vivek Iyer +1
Machine Translation of Culture-Specific Items (CSIs) poses significant challenges. Recent work on CSI translation has shown some success using Large Language Models (LLMs) to adapt…
Quality or Quantity? On Data Scale and Diversity in Adapting Large Language Models for Low-Resource Translation
Vivek Iyer, Bhavitvya Malik, Pavel Stepachev +3
Despite the recent popularity of Large Language Models (LLMs) in Machine Translation (MT), their performance in low-resource languages (LRLs) still lags significantly behind Neural…
Code-Switching with Word Senses for Pretraining in Neural Machine Translation
Vivek Iyer, Edoardo Barba, Alexandra Birch +2
Lexical ambiguity is a significant and pervasive challenge in Neural Machine Translation (NMT), with many state-of-the-art (SOTA) NMT systems struggling to handle polysemous words…
Towards Effective Disambiguation for Machine Translation with Large Language Models
Vivek Iyer, Pinzhen Chen, Alexandra Birch
Resolving semantic ambiguity has long been recognised as a central challenge in the field of Machine Translation. Recent work on benchmarking translation performance on ambiguous s…
The University of Edinburgh's Submission to the WMT22 Code-Mixing Shared Task (MixMT)
Faheem Kirefu, Vivek Iyer, Pinzhen Chen +1
The University of Edinburgh participated in the WMT22 shared task on code-mixed translation. This consists of two subtasks: i) generating code-mixed Hindi/English (Hinglish) text g…
A Deep Learning Approach for Ontology Enrichment from Unstructured Text
Lalit Mohan Sanagavarapu, Vivek Iyer, Raghu Reddy
Information Security in the cyber world is a major cause for concern, with a significant increase in the number of attack surfaces. Existing information on vulnerabilities, attacks…
A framework for syntactic and semantic quality evaluation of ontologies
Vivek Iyer, Lalit Mohan Sanagavarapu, Raghu Reddy
The increasing focus on Web 3.0 is leading to automated creation and enrichment of ontologies and other linked datasets. Alongside automation, quality evaluation of enriched ontolo…
VeeAlign: Multifaceted Context Representation using Dual Attention for Ontology Alignment
Vivek Iyer, Arvind Agarwal, Harshit Kumar
Ontology Alignment is an important research problem applied to various fields such as data integration, data transfer, data preparation, etc. State-of-the-art (SOTA) Ontology Align…
Multifaceted Context Representation using Dual Attention for Ontology Alignment
Vivek Iyer, Arvind Agarwal, Harshit Kumar
Ontology Alignment is an important research problem that finds application in various fields such as data integration, data transfer, data preparation etc. State-of-the-art (SOTA)…