no code implementations • 7 Jan 2025 • N J Karthika, Adyasha Patra, Nagasai Saketh Naidu, Arnab Bhattacharya, Ganesh Ramakrishnan, Chaitali Dangarikar
Indian languages are inflectional and agglutinative and typically follow clause-free word order.
no code implementations • 11 Dec 2024 • Shubham Kumar Nigam, Balaramamahanthi Deepak Patnaik, Shivam Mishra, Noel Shallum, Kripabandhu Ghosh, Arnab Bhattacharya
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.
1 code implementation • 14 Oct 2024 • Shubham Kumar Nigam, Aniket Deroy, Subhankar Maity, Arnab Bhattacharya
To evaluate the quality of these predictions and explanations, we introduce two human evaluation metrics: Clarity and Linking.
no code implementations • 20 Jun 2024 • Pramit Bhattacharyya, Arnab Bhattacharya
In this work, we propose a pragmatic approach to generate grammatically wrong sentences in Bangla.
1 code implementation • 6 Jun 2024 • Shubham Kumar Nigam, Anurag Sharma, Danush Khanna, Noel Shallum, Kripabandhu Ghosh, Arnab Bhattacharya
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.
no code implementations • 22 Apr 2024 • Mitodru Niyogi, Arnab Bhattacharya
In the end, we want to point out that we have only trained Paramanu-Ganita only on a part of our entire mathematical corpus and yet to explore the full potential of our model.
1 code implementation • 30 Mar 2024 • V. S. D. S. Mahesh Akavarapu, Arnab Bhattacharya
To this end, inspired by molecular phylogenetics, we propose a likelihood ratio test to determine if given languages are related based on the proportion of invariant character sites in the aligned wordlists applied during tree inference.
no code implementations • 20 Mar 2024 • Mitodru Niyogi, Arnab Bhattacharya
We also instruction-tuned our model on 10, 763 diverse legal tasks, including legal clause generation, legal drafting, case summarization, etc.
1 code implementation • 5 Feb 2024 • V. S. D. S. Mahesh Akavarapu, Arnab Bhattacharya
Identification of cognates across related languages is one of the primary problems in historical linguistics.
no code implementations • 31 Jan 2024 • Mitodru Niyogi, Arnab Bhattacharya
The models are pretrained on a single GPU with context size of 1024 and vary in size from 13. 29 million (M) to 367. 5 M parameters.
1 code implementation • 17 Oct 2023 • Shubham Kumar Nigam, Aniket Deroy, Noel Shallum, Ayush Kumar Mishra, Anup Roy, Shubham Kumar Mishra, Arnab Bhattacharya, Saptarshi Ghosh, Kripabandhu Ghosh
This paper describes our submission to the SemEval-2023 for Task 6 on LegalEval: Understanding Legal Texts.
1 code implementation • 11 Oct 2023 • 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 daughter languages.
no code implementations • WS 2019 • Hrishikesh Terdalkar, Arnab Bhattacharya
We build a natural language question-answering system in sa\d{m}sk\d{r}ta that uses the knowledge graph to answer factoid questions.
1 code implementation • 11 Oct 2023 • Hrishikesh Terdalkar, Arnab Bhattacharya
In this paper, we present Antarlekhaka, a tool for manual annotation of a comprehensive set of tasks relevant to NLP.
no code implementations • 26 Sep 2023 • Shubham Kumar Nigam, Shubham Kumar Mishra, Ayush Kumar Mishra, Noel Shallum, Arnab Bhattacharya
Legal QA platforms bear the promise to metamorphose the manner in which legal experts engage with jurisprudential documents.
no code implementations • 11 Jul 2023 • Pramit Bhattacharyya, Joydeep Mondal, Subhadip Maji, Arnab Bhattacharya
We also demonstrate the efficacy of Vacaspati as a corpus by showing that similar models built from other corpora are not as effective.
no code implementations • 3 Feb 2023 • Ashutosh Dutta, Samrat Chatterjee, Arnab Bhattacharya, Mahantesh Halappanavar
Development of autonomous cyber system defense strategies and action recommendations in the real-world is challenging, and includes characterizing system state uncertainties and attack-defense dynamics.
no code implementations • 20 Dec 2022 • Aowabin Rahman, Arnab Bhattacharya, Thiagarajan Ramachandran, Sayak Mukherjee, Himanshu Sharma, Ted Fujimoto, Samrat Chatterjee
Search and Rescue (SAR) missions in remote environments often employ autonomous multi-robot systems that learn, plan, and execute a combination of local single-robot control actions, group primitives, and global mission-oriented coordination and collaboration.
1 code implementation • 29 Sep 2022 • Hrishikesh Terdalkar, Arnab Bhattacharya
We present Chandoj\~n\=anam, a web-based Sanskrit meter (Chanda) identification and utilization system.
Optical Character Recognition
Optical Character Recognition (OCR)
1 code implementation • Findings (ACL) 2022 • Arnav Kapoor, Mudit Dhawan, Anmol Goel, T. H. Arjun, Akshala Bhatnagar, Vibhu Agrawal, Amul Agrawal, Arnab Bhattacharya, Ponnurangam Kumaraguru, Ashutosh Modi
Further, as a use-case for the corpus, we introduce the task of bail prediction.
no code implementations • 30 Mar 2022 • Debopriyo Banerjee, Lucky Dhakad, Harsh Maheshwari, Muthusamy Chelliah, Niloy Ganguly, Arnab Bhattacharya
Recommendation in the fashion domain has seen a recent surge in research in various areas, for example, shop-the-look, context-aware outfit creation, personalizing outfit creation, etc.
1 code implementation • 16 Mar 2022 • Ethan King, Jan Drgona, Aaron Tuor, Shrirang Abhyankar, Craig Bakker, Arnab Bhattacharya, Draguna Vrabie
The dynamics-aware economic dispatch (DED) problem embeds low-level generator dynamics and operational constraints to enable near real-time scheduling of generation units in a power network.
no code implementations • 1 Feb 2022 • Hrishikesh Terdalkar, Arnab Bhattacharya, Madhulika Dubey, Ramamurthy S, Bhavna Naneria Singh
Knowledge bases (KB) are an important resource in a number of natural language processing (NLP) and information retrieval (IR) tasks, such as semantic search, automated question-answering etc.
no code implementations • 10 Jan 2022 • Shashwat Bhattacharya, Mahendra K Verma, Arnab Bhattacharya
We observe that although the predictions of all the models are quite close to each other, the machine learning models developed in this work provide the best match with the experimental and numerical results.
1 code implementation • 25 Dec 2021 • Kartik Sharma, Samidha Verma, Sourav Medya, Arnab Bhattacharya, Sayan Ranu
In this work, we study this problem and show that GNNs remain vulnerable even when the downstream task and model are unknown.
1 code implementation • 3 Dec 2021 • Vijit Malik, Rishabh Sanjay, Shouvik Kumar Guha, Angshuman Hazarika, Shubham Nigam, Arnab Bhattacharya, Ashutosh Modi
For automatically segmenting the legal documents, we experiment with the task of rhetorical role prediction: given a document, predict the text segments corresponding to various roles.
1 code implementation • 6 Jul 2021 • Hrishikesh Terdalkar, Arnab Bhattacharya
The application is language and corpus agnostic, but can be tuned for special needs of a specific language or a corpus.
1 code implementation • ACL 2021 • Vijit Malik, Rishabh Sanjay, Shubham Kumar Nigam, Kripa Ghosh, Shouvik Kumar Guha, Arnab Bhattacharya, Ashutosh Modi
The task requires an automated system to predict an explainable outcome of a case.
no code implementations • 21 Mar 2021 • Milan Jain, Soumya Kundu, Arnab Bhattacharya, Sen Huang, Vikas Chandan, Nikitha Radhakrishnan, Veronica Adetola, Draguna Vrabie
For effective integration of building operations into the evolving demand response programs of the power grid, real-time decisions concerning the use of building appliances for grid services must excel on multiple criteria, ranging from the added value to occupants' comfort to the quality of the grid services.
no code implementations • 9 Nov 2020 • Arnab Bhattacharya, Thiagarajan Ramachandran, Sandeep Banik, Chase P. Dowling, Shaunak D. Bopardikar
Adversary emulation is an offensive exercise that provides a comprehensive assessment of a system's resilience against cyber attacks.
1 code implementation • 19 Aug 2020 • Sunil Nishad, Shubhangi Agarwal, Arnab Bhattacharya, Sayan Ranu
In this paper, we develop GraphReach, a position-aware inductive GNN that captures the global positions of nodes through reachability estimations with respect to a set of anchor nodes.
no code implementations • 17 May 2020 • Arnab Kumar Mondal, Arnab Bhattacharya, Sudipto Mukherjee, Prathosh AP, Sreeram Kannan, Himanshu Asnani
Estimation of information theoretic quantities such as mutual information and its conditional variant has drawn interest in recent times owing to their multifaceted applications.
no code implementations • 12 Apr 2018 • Mitodru Niyogi, Kripabandhu Ghosh, Arnab Bhattacharya
The proposed method is superior to the state-of-the-art method not only for IR evaluation measures but also in terms of time requirements.
no code implementations • 6 Oct 2013 • Paheli Bhattacharya, Arnab Bhattacharya
Active languages such as Bangla (or Bengali) evolve over time due to a variety of social, cultural, economic, and political issues.
no code implementations • 18 Apr 2013 • Shubhadip Mitra, Partha Dutta, Arnab Bhattacharya
In this paper, we introduce generalized staircase (GS) constraints which is an important generalization of one such tractable class found in the literature, namely, staircase constraints.