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20192026
most citedindicnlp@kgp at DravidianLangTech-EACL2021: Offensive Language Identification in Dravidian Languages

9 citations · 18 across the 20 of their papers we have counts for

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16 papers · 1 filter

cs.CL2026

CaRGo-T: Causal Reasoning Graph-of-Thought improves Multimodal Humor Comprehension

Abhilash Nandy, Rahul Seetharaman, Aman Bansal +5

Large-scale vision-language models (VLMs) have demonstrated remarkable versatility across a wide range of multimodal tasks. However, understanding humor remains challenging because…

cs.CL2026

Known Intents, New Combinations: Clause-Factorized Decoding for Compositional Multi-Intent Detection

Abhilash Nandy

Multi-intent detection papers usually ask whether a model can recover multiple intents from one utterance. We ask a harder and, for deployment, more useful question: can it recover…

cs.CL2025

Leveraging Large Language Models for Predictive Analysis of Human Misery

Bishanka Seal, Rahul Seetharaman, Aman Bansal +1

This study investigates the use of Large Language Models (LLMs) for predicting human-perceived misery scores from natural language descriptions of real-world scenarios. The task is…

cs.CL2025

Leveraging Self-Attention for Input-Dependent Soft Prompting in LLMs

Ananth Muppidi, Abhilash Nandy, Sambaran Bandyopadhyay

The performance of large language models in domain-specific tasks necessitates fine-tuning, which is computationally expensive and technically challenging. This paper focuses on pa…

cs.CL2025

REFINE-AF: A Task-Agnostic Framework to Align Language Models via Self-Generated Instructions using Reinforcement Learning from Automated Feedback

Aniruddha Roy, Pretam Ray, Abhilash Nandy +2

Instruction-based Large Language Models (LLMs) have proven effective in numerous few-shot or zero-shot Natural Language Processing (NLP) tasks. However, creating human-annotated in…

cs.CL2024

A Pointer Network-based Approach for Joint Extraction and Detection of Multi-Label Multi-Class Intents

Ankan Mullick, Sombit Bose, Abhilash Nandy +2

In task-oriented dialogue systems, intent detection is crucial for interpreting user queries and providing appropriate responses. Existing research primarily addresses simple queri…

cs.CL2024

Order-Based Pre-training Strategies for Procedural Text Understanding

Abhilash Nandy, Yash Kulkarni, Pawan Goyal +1

In this paper, we propose sequence-based pretraining methods to enhance procedural understanding in natural language processing. Procedural text, containing sequential instructions…

cs.CL2024★ 2 cited

SERPENT-VLM : Self-Refining Radiology Report Generation Using Vision Language Models

Manav Nitin Kapadnis, Sohan Patnaik, Abhilash Nandy +3

Radiology Report Generation (R2Gen) demonstrates how Multi-modal Large Language Models (MLLMs) can automate the creation of accurate and coherent radiological reports. Existing met…

cs.CL2023

CLMSM: A Multi-Task Learning Framework for Pre-training on Procedural Text

Abhilash Nandy, Manav Nitin Kapadnis, Pawan Goyal +1

In this paper, we propose CLMSM, a domain-specific, continual pre-training framework, that learns from a large set of procedural recipes. CLMSM uses a Multi-Task Learning Framework…

cs.CL2023

: Domain-Specific Fast Continual Pre-training Technique using Document-Level Metadata and Taxonomy

Abhilash Nandy, Manav Nitin Kapadnis, Sohan Patnaik +3

In this paper, we propose (Fast Continual Pre-training Technique using Document Level Metadata and Taxonomy), a novel, compute-efficient framework that utilizes Document…

cs.CL2022

An Evaluation Framework for Legal Document Summarization

Ankan Mullick, Abhilash Nandy, Manav Nitin Kapadnis +3

A law practitioner has to go through numerous lengthy legal case proceedings for their practices of various categories, such as land dispute, corruption, etc. Hence, it is importan…

cs.CL2022★ 5 cited

Fine-grained Intent Classification in the Legal Domain

Ankan Mullick, Abhilash Nandy, Manav Nitin Kapadnis +2

A law practitioner has to go through a lot of long legal case proceedings. To understand the motivation behind the actions of different parties/individuals in a legal case, it is e…

cs.CL2021

Team Enigma at ArgMining-EMNLP 2021: Leveraging Pre-trained Language Models for Key Point Matching

Manav Nitin Kapadnis, Sohan Patnaik, Siba Smarak Panigrahi +2

We present the system description for our submission towards the Key Point Analysis Shared Task at ArgMining 2021. Track 1 of the shared task requires participants to develop metho…

cs.CL2021

Question Answering over Electronic Devices: A New Benchmark Dataset and a Multi-Task Learning based QA Framework

Abhilash Nandy, Soumya Sharma, Shubham Maddhashiya +3

Answering questions asked from instructional corpora such as E-manuals, recipe books, etc., has been far less studied than open-domain factoid context-based question answering. Thi…

cs.CL2021

cs60075_team2 at SemEval-2021 Task 1 : Lexical Complexity Prediction using Transformer-based Language Models pre-trained on various text corpora

Abhilash Nandy, Sayantan Adak, Tanurima Halder +1

This paper describes the performance of the team cs60075_team2 at SemEval 2021 Task 1 - Lexical Complexity Prediction. The main contribution of this paper is to fine-tune transform…

cs.CL2021★ 9 cited

indicnlp@kgp at DravidianLangTech-EACL2021: Offensive Language Identification in Dravidian Languages

Kushal Kedia, Abhilash Nandy

The paper presents the submission of the team indicnlp@kgp to the EACL 2021 shared task "Offensive Language Identification in Dravidian Languages." The task aimed to classify diffe…