65 citations · 582 across the 89 of their papers we have counts for
13 papers · 2 filters
ECTSum: A New Benchmark Dataset For Bullet Point Summarization of Long Earnings Call Transcripts
Rajdeep Mukherjee, Abhinav Bohra, Akash Banerjee +8
Despite tremendous progress in automatic summarization, state-of-the-art methods are predominantly trained to excel in summarizing short newswire articles, or documents with strong…
TransLIST: A Transformer-Based Linguistically Informed Sanskrit Tokenizer
Jivnesh Sandhan, Rathin Singha, Narein Rao +3
Sanskrit Word Segmentation (SWS) is essential in making digitized texts available and in deploying downstream tasks. It is, however, non-trivial because of the sandhi phenomenon th…
Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluation
Abhay Shukla, Paheli Bhattacharya, Soham Poddar +4
Summarization of legal case judgement documents is a challenging problem in Legal NLP. However, not much analyses exist on how different families of summarization models (e.g., ext…
A Novel Multi-Task Learning Approach for Context-Sensitive Compound Type Identification in Sanskrit
Jivnesh Sandhan, Ashish Gupta, Hrishikesh Terdalkar +4
The phenomenon of compounding is ubiquitous in Sanskrit. It serves for achieving brevity in expressing thoughts, while simultaneously enriching the lexical and structural formation…
Pre-trained Language Models for the Legal Domain: A Case Study on Indian Law
Shounak Paul, Arpan Mandal, Pawan Goyal +1
NLP in the legal domain has seen increasing success with the emergence of Transformer-based Pre-trained Language Models (PLMs) pre-trained on legal text. PLMs trained over European…
Exploring Generative Models for Joint Attribute Value Extraction from Product Titles
Kalyani Roy, Tapas Nayak, Pawan Goyal
Attribute values of the products are an essential component in any e-commerce platform. Attribute Value Extraction (AVE) deals with extracting the attributes of a product and their…
A Framework to Generate High-Quality Datapoints for Multiple Novel Intent Detection
Ankan Mullick, Sukannya Purkayastha, Pawan Goyal +1
Systems like Voice-command based conversational agents are characterized by a pre-defined set of skills or intents to perform user specified tasks. In the course of time, newer int…
CORAL: Contextual Response Retrievability Loss Function for Training Dialog Generation Models
Bishal Santra, Ravi Ghadia, Manish Gupta +1
In the field of Natural Language Processing, there are many tasks that can be tackled effectively using the cross-entropy (CE) loss function. However, the task of dialog generation…
A Study on Prompt-based Few-Shot Learning Methods for Belief State Tracking in Task-oriented Dialog Systems
Debjoy Saha, Bishal Santra, Pawan Goyal
We tackle the Dialogue Belief State Tracking(DST) problem of task-oriented conversational systems. Recent approaches to this problem leveraging Transformer-based models have yielde…
A Generative Approach for Financial Causality Extraction
Tapas Nayak, Soumya Sharma, Yash Butala +3
Causality represents the foremost relation between events in financial documents such as financial news articles, financial reports. Each financial causality contains a cause span…
Sequence-Based Extractive Summarisation for Scientific Articles
Daniel Kershaw, Rob Koeling
This paper presents the results of research on supervised extractive text summarisation for scientific articles. We show that a simple sequential tagging model based only on the te…
Prabhupadavani: A Code-mixed Speech Translation Data for 25 Languages
Jivnesh Sandhan, Ayush Daksh, Om Adideva Paranjay +2
Nowadays, the interest in code-mixing has become ubiquitous in Natural Language Processing (NLP); however, not much attention has been given to address this phenomenon for Speech T…
Systematic Investigation of Strategies Tailored for Low-Resource Settings for Low-Resource Dependency Parsing
Jivnesh Sandhan, Laxmidhar Behera, Pawan Goyal
In this work, we focus on low-resource dependency parsing for multiple languages. Several strategies are tailored to enhance performance in low-resource scenarios. While these are…