34 citations · 68 across the 20 of their papers we have counts for
24 papers
Beyond Relevance: Structured Semantic Supervision for Product Search with LLM-Augmented Annotations
Girish A. Koushik, Swapnil Bhosale, Samarth Agrawal +4
E-commerce search requires distinguishing products that are merely related to a query from those that directly satisfy the user's shopping intent. We augment query-product pairs wi…
ALOPE: Adaptive Layer Optimization for Translation Quality Estimation using Large Language Models
Archchana Sindhujan, Shenbin Qian, Chan Chi Chun Matthew +2
Large Language Models (LLMs) have shown remarkable performance across a wide range of natural language processing tasks. Quality Estimation (QE) for Machine Translation (MT), which…
NEAR: A Nested Embedding Approach to Efficient Product Retrieval and Ranking
Shenbin Qian, Diptesh Kanojia, Samarth Agrawal +4
E-commerce information retrieval (IR) systems struggle to simultaneously achieve high accuracy in interpreting complex user queries and maintain efficient processing of vast produc…
When LLMs Struggle: Reference-less Translation Evaluation for Low-resource Languages
Archchana Sindhujan, Diptesh Kanojia, Constantin Orasan +1
This paper investigates the reference-less evaluation of machine translation for low-resource language pairs, known as quality estimation (QE). Segment-level QE is a challenging cr…
Benchmarking terminology building capabilities of ChatGPT on an English-Russian Fashion Corpus
Anastasiia Bezobrazova, Miriam Seghiri, Constantin Orasan
This paper compares the accuracy of the terms extracted using SketchEngine, TBXTools and ChatGPT. In addition, it evaluates the quality of the definitions produced by ChatGPT for t…
Centrality-aware Product Retrieval and Ranking
Hadeel Saadany, Swapnil Bhosale, Samarth Agrawal +3
This paper addresses the challenge of improving user experience on e-commerce platforms by enhancing product ranking relevant to users' search queries. Ambiguity and complexity of…
Cyber Risks of Machine Translation Critical Errors : Arabic Mental Health Tweets as a Case Study
Hadeel Saadany, Ashraf Tantawy, Constantin Orasan
With the advent of Neural Machine Translation (NMT) systems, the MT output has reached unprecedented accuracy levels which resulted in the ubiquity of MT tools on almost all online…
Google Translate Error Analysis for Mental Healthcare Information: Evaluating Accuracy, Comprehensibility, and Implications for Multilingual Healthcare Communication
Jaleh Delfani, Constantin Orasan, Hadeel Saadany +5
This study explores the use of Google Translate (GT) for translating mental healthcare (MHealth) information and evaluates its accuracy, comprehensibility, and implications for mul…
SurreyAI 2023 Submission for the Quality Estimation Shared Task
Archchana Sindhujan, Diptesh Kanojia, Constantin Orasan +1
Quality Estimation (QE) systems are important in situations where it is necessary to assess the quality of translations, but there is no reference available. This paper describes t…
Evaluation of Chinese-English Machine Translation of Emotion-Loaded Microblog Texts: A Human Annotated Dataset for the Quality Assessment of Emotion Translation
Shenbin Qian, Constantin Orasan, Felix do Carmo +2
In this paper, we focus on how current Machine Translation (MT) tools perform on the translation of emotion-loaded texts by evaluating outputs from Google Translate according to a…
Better Transcription of UK Supreme Court Hearings
Hadeel Saadany, Catherine Breslin, Constantin Orăsan +1
Transcription of legal proceedings is very important to enable access to justice. However, speech transcription is an expensive and slow process. In this paper we describe part of…
A Semi-supervised Approach for a Better Translation of Sentiment in Dialectical Arabic UGT
Hadeel Saadany, Constantin Orasan, Emad Mohamed +1
In the online world, Machine Translation (MT) systems are extensively used to translate User-Generated Text (UGT) such as reviews, tweets, and social media posts, where the main me…
Biographical: A Semi-Supervised Relation Extraction Dataset
Alistair Plum, Tharindu Ranasinghe, Spencer Jones +2
Extracting biographical information from online documents is a popular research topic among the information extraction (IE) community. Various natural language processing (NLP) tec…
PLOD: An Abbreviation Detection Dataset for Scientific Documents
Leonardo Zilio, Hadeel Saadany, Prashant Sharma +2
The detection and extraction of abbreviations from unstructured texts can help to improve the performance of Natural Language Processing tasks, such as machine translation and info…
Sentiment-Aware Measure (SAM) for Evaluating Sentiment Transfer by Machine Translation Systems
Hadeel Saadany, Constantin Orasan, Emad Mohamed +1
In translating text where sentiment is the main message, human translators give particular attention to sentiment-carrying words. The reason is that an incorrect translation of suc…
BLEU, METEOR, BERTScore: Evaluation of Metrics Performance in Assessing Critical Translation Errors in Sentiment-oriented Text
Hadeel Saadany, Constantin Orasan
Social media companies as well as authorities make extensive use of artificial intelligence (AI) tools to monitor postings of hate speech, celebrations of violence or profanity. Si…
Challenges in Translation of Emotions in Multilingual User-Generated Content: Twitter as a Case Study
Hadeel Saadany, Constantin Orasan, Rocio Caro Quintana +2
Although emotions are universal concepts, transferring the different shades of emotion from one language to another may not always be straightforward for human translators, let alo…
An Exploratory Analysis of Multilingual Word-Level Quality Estimation with Cross-Lingual Transformers
Tharindu Ranasinghe, Constantin Orasan, Ruslan Mitkov
Most studies on word-level Quality Estimation (QE) of machine translation focus on language-specific models. The obvious disadvantages of these approaches are the need for labelled…
TransQuest: Translation Quality Estimation with Cross-lingual Transformers
Tharindu Ranasinghe, Constantin Orasan, Ruslan Mitkov
Recent years have seen big advances in the field of sentence-level quality estimation (QE), largely as a result of using neural-based architectures. However, the majority of these…
Fake or Real? A Study of Arabic Satirical Fake News
Hadeel Saadany, Emad Mohamed, Constantin Orasan
One very common type of fake news is satire which comes in a form of a news website or an online platform that parodies reputable real news agencies to create a sarcastic version o…
Is it Great or Terrible? Preserving Sentiment in Neural Machine Translation of Arabic Reviews
Hadeel Saadany, Constantin Orasan
Since the advent of Neural Machine Translation (NMT) approaches there has been a tremendous improvement in the quality of automatic translation. However, NMT output still lacks acc…
RGCL at SemEval-2020 Task 6: Neural Approaches to Definition Extraction
Tharindu Ranasinghe, Alistair Plum, Constantin Orasan +1
This paper presents the RGCL team submission to SemEval 2020 Task 6: DeftEval, subtasks 1 and 2. The system classifies definitions at the sentence and token levels. It utilises sta…
TransQuest at WMT2020: Sentence-Level Direct Assessment
Tharindu Ranasinghe, Constantin Orasan, Ruslan Mitkov
This paper presents the team TransQuest's participation in Sentence-Level Direct Assessment shared task in WMT 2020. We introduce a simple QE framework based on cross-lingual trans…
Intelligent Translation Memory Matching and Retrieval with Sentence Encoders
Tharindu Ranasinghe, Constantin Orasan, Ruslan Mitkov
Matching and retrieving previously translated segments from a Translation Memory is the key functionality in Translation Memories systems. However this matching and retrieving proc…