Papers by Vani Kanjirangat

2 papers
Early Guessing for Dialect Identification (2022.findings-emnlp)

Copied to clipboard

Challenge: Current research on dialect identification is model-centric, focusing on performance.
Approach: They propose a data-centric approach to find the shortest input needed to make a plausible guess.
Outcome: The proposed method generalizes across dialects and datasets with two shortening criteria.
Tokenization and Representation Biases in Multilingual Models on Dialectal NLP Tasks (2025.emnlp-main)

Copied to clipboard

Challenge: Large Language Models (LLMs) pre-trained on massive text data in many languages are preferred solution for various Natural Language processing tasks.
Approach: They compare tokenization parity and information parity as representational biases in pre-trained models . they find TP is better predictor of performance on tasks reliant on syntactic and morphological cues .
Outcome: The proposed model improves on dialect classification, topic classification, and extractive question answering tasks.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations