most citedSemantically Cohesive Word Grouping in Indian Languages

1 citations · 2 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Improving Video Question Answering through query-based frame selection

Himanshu Patil, Geo Jolly, Ramana Raja Buddala +2

Video Question Answering (VideoQA) models enhance understanding and interaction with audiovisual content, making it more accessible, searchable, and useful for a wide range of fiel…

cs.CL2025

AyurParam: A State-of-the-Art Bilingual Language Model for Ayurveda

Mohd Nauman, Sravan Gvm, Vijay Devane +7

Current large language models excel at broad, general-purpose tasks, but consistently underperform when exposed to highly specialized domains that require deep cultural, linguistic…

cs.CL2025

The Art of Breaking Words: Rethinking Multilingual Tokenizer Design

Aamod Thakur, Ajay Nagpal, Atharva Savarkar +7

While model architecture and training objectives are well-studied, tokenization, particularly in multilingual contexts, remains a relatively neglected aspect of Large Language Mode…

cs.CL20251 cited

Intent Aware Context Retrieval for Multi-Turn Agricultural Question Answering

Abhay Vijayvargia, Ajay Nagpal, Kundeshwar Pundalik +5

Indian farmers often lack timely, accessible, and language-friendly agricultural advice, especially in rural areas with low literacy. To address this gap in accessibility, this pap…

cs.CL2025

MorphTok: Morphologically Grounded Tokenization for Indian Languages

Maharaj Brahma, N J Karthika, Atul Singh +5

Tokenization is a crucial step in NLP, especially with the rise of large language models (LLMs), impacting downstream performance, computational cost, and efficiency. Existing LLMs…

cs.CL20251 cited

Semantically Cohesive Word Grouping in Indian Languages

N J Karthika, Adyasha Patra, Nagasai Saketh Naidu +3

Indian languages are inflectional and agglutinative and typically follow clause-free word order. The structure of sentences across most major Indian languages are similar when thei…