activity
20242026
collaborators

6 papers

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.IR2025

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…

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.IR2024

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…