5 papers
Domain-Specific Quality Estimation for Machine Translation in Low-Resource Scenarios
Namrata Patil Gurav, Akashdeep Ranu, Archchana Sindhujan +1
Quality Estimation (QE) is essential for assessing machine translation quality in reference-less settings, particularly for domain-specific and low-resource language scenarios. In…
Beyond Scalar Scores: Reinforcement Learning for Error-Aware Quality Estimation of Machine Translation
Archchana Sindhujan, Girish A. Koushik, Shenbin Qian +2
Quality Estimation (QE) aims to assess the quality of machine translation (MT) outputs without relying on reference translations, making it essential for real-world, large-scale MT…
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…
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…
What do Large Language Models Need for Machine Translation Evaluation?
Shenbin Qian, Archchana Sindhujan, Minnie Kabra +4
Leveraging large language models (LLMs) for various natural language processing tasks has led to superlative claims about their performance. For the evaluation of machine translati…