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20242026
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cs.CL2026

IndicQE-APE: A Benchmark for Quality Estimation and Automatic Post-Editing for Indic Languages

Diptesh Kanojia, Archchana Sindhujan, Sourabh Deoghare +15

Indic quality estimation (QE) and automatic post-editing (APE) data is spread across separate releases, so no single resource supports training and evaluation across tasks and lang…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2024

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…

cs.CL2024

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…