2 citations · 3 across the 11 of their papers we have counts for
13 papers
Function-Space Temporal Self-Distillation for Policy Optimization
Aryan Das, Arnab Bhattacharya, Vinay Kumar Verma
Reinforcement Learning with Verifiable Rewards (RLVR) improves reasoning in language models, but scalar outcomes provide coarse supervision over response trajectories. Self-distill…
SALD: Self-Referenced Advantage Learning for Diffusion Models
Aryan Das, Surjo Dey, Koushik Biswas +4
Recent work on language-model adaptation has shown that single models can obtain informative training signals by evaluating their behavior in demonstrationor feedback-augmented con…
BhashaSetu: Cross-Lingual Knowledge Transfer from High-Resource to Extreme Low-Resource Languages
Subhadip Maji, Arnab Bhattacharya
Despite remarkable advances in natural language processing, developing effective systems for low-resource languages remains a formidable challenge, with performances typically lagg…
INDIC DIALECT: A Multi Task Benchmark to Evaluate and Translate in Indian Language Dialects
Tarun Sharma, Manikandan Ravikiran, Sourava Kumar Behera +3
Recent NLP advances focus primarily on standardized languages, leaving most low-resource dialects under-served especially in Indian scenarios. In India, the issue is particularly i…
Lexical and Statistical Analysis of Bangla Newspaper and Literature: A Corpus-Driven Study on Diversity, Readability, and NLP Adaptation
Pramit Bhattacharyya, Arnab Bhattacharya
In this paper, we present a comprehensive corpus-driven analysis of Bangla literary and newspaper texts to investigate their lexical diversity, structural complexity and readabilit…
A Rapid Thermal Chemical Vapor Deposition System for Fast Synthesis of Epitaxial Graphene Under Ambient Pressure
Shikhar Kumar Gupta, Meet Ghelani, Pragna Datta +10
Graphene has emerged as a promising material for next-generation electronic and thermal devices owing to its exceptional charge transport and thermal conductivity. However, high-qu…
A Case Study of Cross-Lingual Zero-Shot Generalization for Classical Languages in LLMs
V. S. D. S. Mahesh Akavarapu, Hrishikesh Terdalkar, Pramit Bhattacharyya +5
Large Language Models (LLMs) have demonstrated remarkable generalization capabilities across diverse tasks and languages. In this study, we focus on natural language understanding…
BanglaByT5: Byte-Level Modelling for Bangla
Pramit Bhattacharyya, Arnab Bhattacharya
Large language models (LLMs) have achieved remarkable success across various natural language processing tasks. However, most LLM models use traditional tokenizers like BPE and Sen…
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…
A Likelihood Ratio Test of Genetic Relationship among Languages
V. S. D. S. Mahesh Akavarapu, Arnab Bhattacharya
Lexical resemblances among a group of languages indicate that the languages could be genetically related, i.e., they could have descended from a common ancestral language. However,…
Automated Cognate Detection as a Supervised Link Prediction Task with Cognate Transformer
V. S. D. S. Mahesh Akavarapu, Arnab Bhattacharya
Identification of cognates across related languages is one of the primary problems in historical linguistics. Automated cognate identification is helpful for several downstream tas…
Cognate Transformer for Automated Phonological Reconstruction and Cognate Reflex Prediction
V. S. D. S. Mahesh Akavarapu, Arnab Bhattacharya
Phonological reconstruction is one of the central problems in historical linguistics where a proto-word of an ancestral language is determined from the observed cognate words of da…
Antarlekhaka: A Comprehensive Tool for Multi-task Natural Language Annotation
Hrishikesh Terdalkar, Arnab Bhattacharya
One of the primary obstacles in the advancement of Natural Language Processing (NLP) technologies for low-resource languages is the lack of annotated datasets for training and test…