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Vivek Seshadri

3 accepted papers

2024

INMT-Lite: Accelerating Low-Resource Language Data Collection via Offline Interactive Neural Machine Translation

COLING 2024main

A steady increase in the performance of Massively Multilingual Models (MMLMs) has contributed to their rapidly increasing use in data collection pipelines. Interactive Neural Machine Translation (INMT) systems are one class of tools that can utilize MMLMs to promote such data collection in several u…

Cited by 0SourcePDFScholar
2024

PARIKSHA: A Large-Scale Investigation of Human-LLM Evaluator Agreement on Multilingual and Multi-Cultural Data

EMNLP 2024main

Evaluation of multilingual Large Language Models (LLMs) is challenging due to a variety of factors – the lack of benchmarks with sufficient linguistic diversity, contamination of popular benchmarks into LLM pre-training data and the lack of local, cultural nuances in translated benchmarks. In this w…

2023

X-RiSAWOZ: High-Quality End-to-End Multilingual Dialogue Datasets and Few-shot Agents

ACL 2023findings

Task-oriented dialogue research has mainly focused on a few popular languages like English and Chinese, due to the high dataset creation cost for a new language. To reduce the cost, we apply manual editing to automatically translated data. We create a new multilingual benchmark, X-RiSAWOZ, by transl…