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Arnab Bhattacharya

12 accepted papers

2025

A Case Study of Cross-Lingual Zero-Shot Generalization for Classical Languages in LLMs

V.S.D.S.Mahesh Akavarapu, Hrishikesh Terdalkar, Pramit Bhattacharyya, Shubhangi Agarwal, Dr. Vishakha Deulgaonkar, Chaitali Dangarikar +2
ACL 2025finding

Large Language Models (LLMs) have demonstrated remarkable generalization capabilities across diverse tasks and languages. In this study, we focus on natural language understanding in three classical languages—Sanskrit, Ancient Greek and Latin—to investigate the factors affecting cross-lingual zero-s…

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2025

LegalSeg: Unlocking the Structure of Indian Legal Judgments Through Rhetorical Role Classification

Shubham Kumar Nigam, Tanmay Dubey, Govind Sharma, Noel Shallum, Kripabandhu Ghosh, Arnab Bhattacharya
NAACL 2025findings

In this paper, we address the task of semantic segmentation of legal documents through rhetorical role classification, with a focus on Indian legal judgments. We introduce **LegalSeg**, the largest annotated dataset for this task, comprising over 7,000 documents and 1.4 million sentences, labeled wi…

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2025

Leveraging LLMs for Bangla Grammar Error Correction: Error Categorization, Synthetic Data, and Model Evaluation

Pramit Bhattacharyya, Arnab Bhattacharya
ACL 2025finding

Large Language Models (LLMs) perform exceedingly well in Natural Language Understanding (NLU) tasks for many languages including English. However, despite being the fifth most-spoken language globally, Grammatical Error Correction (GEC) in Bangla remains underdeveloped. In this work, we investigate…

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2025

NYAYAANUMANA and INLEGALLLAMA: The Largest Indian Legal Judgment Prediction Dataset and Specialized Language Model for Enhanced Decision Analysis

Shubham Kumar Nigam, Deepak Patnaik Balaramamahanthi, Shivam Mishra, Noel Shallum, Kripabandhu Ghosh, Arnab Bhattacharya
COLING 2025main

The integration of artificial intelligence (AI) in legal judgment prediction (LJP) has the potential to transform the legal landscape, particularly in jurisdictions like India, where a significant backlog of cases burdens the legal system. This paper introduces NyayaAnumana, the largest and most div…

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2024

A Likelihood Ratio Test of Genetic Relationship among Languages

V.S.D.S.Mahesh Akavarapu, Arnab Bhattacharya
NAACL 2024long

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, such resemblances can arise by chance and, hence, need not always imply an underlying genetic relationship. Many tests…

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2024

Legal Judgment Reimagined: PredEx and the Rise of Intelligent AI Interpretation in Indian Courts

Shubham Kumar Nigam, Anurag Sharma, Danush Khanna, Noel Shallum, Kripabandhu Ghosh, Arnab Bhattacharya
ACL 2024findings

In the era of Large Language Models (LLMs), predicting judicial outcomes poses significant challenges due to the complexity of legal proceedings and the scarcity of expert-annotated datasets. Addressing this, we introduce Prediction with Explanation (PredEx), the largest expert-annotated dataset for…

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2023

Cognate Transformer for Automated Phonological Reconstruction and Cognate Reflex Prediction

V.S.D.S.Mahesh Akavarapu, Arnab Bhattacharya
EMNLP 2023long main

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 daughter languages. Computational approaches to historical linguistics attempt to automate the task by learning models on…

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2023

Task and Model Agnostic Adversarial Attack on Graph Neural Networks

Kartik Sharma, Samidha Verma, Sourav Medya, Arnab Bhattacharya, Sayan Ranu
AAAI 2023technical

Adversarial attacks on Graph Neural Networks (GNNs) reveal their security vulnerabilities, limiting their adoption in safety-critical applications. However, existing attack strategies rely on the knowledge of either the GNN model being used or the predictive task being attacked. Is this knowledge ne…

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2022

HLDC: Hindi Legal Documents Corpus

Arnav Kapoor, Mudit Dhawan, Anmol Goel, Arjun T H, Akshala Bhatnagar, Vibhu Agrawal +4
ACL 2022findings

Many populous countries including India are burdened with a considerable backlog of legal cases. Development of automated systems that could process legal documents and augment legal practitioners can mitigate this. However, there is a dearth of high-quality corpora that is needed to develop such da…

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2021

GraphReach: Position-Aware Graph Neural Network using Reachability Estimations

Sunil Nishad, Shubhangi Agarwal, Arnab Bhattacharya, Sayan Ranu
IJCAI 2021poster

Majority of the existing graph neural networks(GNN) learn node embeddings that encode their local neighborhoods but not their positions. Consequently, two nodes that are vastly distant but located in similar local neighborhoods map to similar embeddings in those networks. This limitation prevents ac…

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2021

ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation

Vijit Malik, Rishabh Sanjay, Shubham Kumar Nigam, Kripabandhu Ghosh, Shouvik Kumar Guha, Arnab Bhattacharya +1
ACL 2021long

An automated system that could assist a judge in predicting the outcome of a case would help expedite the judicial process. For such a system to be practically useful, predictions by the system should be explainable. To promote research in developing such a system, we introduce ILDC (Indian Legal Do…

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