3 citations · 13 across the 15 of their papers we have counts for
9 papers · 1 filter
Multilingual Bias Detection and Mitigation for Indian Languages
Ankita Maity, Anubhav Sharma, Rudra Dhar +3
Lack of diverse perspectives causes neutrality bias in Wikipedia content leading to millions of worldwide readers getting exposed by potentially inaccurate information. Hence, neut…
Neural models for Factual Inconsistency Classification with Explanations
Tathagata Raha, Mukund Choudhary, Abhinav Menon +4
Factual consistency is one of the most important requirements when editing high quality documents. It is extremely important for automatic text generation systems like summarizatio…
LLM-RM at SemEval-2023 Task 2: Multilingual Complex NER using XLM-RoBERTa
Rahul Mehta, Vasudeva Varma
Named Entity Recognition(NER) is a task of recognizing entities at a token level in a sentence. This paper focuses on solving NER tasks in a multilingual setting for complex named…
GrapeQA: GRaph Augmentation and Pruning to Enhance Question-Answering
Dhaval Taunk, Lakshya Khanna, Pavan Kandru +3
Commonsense question-answering (QA) methods combine the power of pre-trained Language Models (LM) with the reasoning provided by Knowledge Graphs (KG). A typical approach collects…
XWikiGen: Cross-lingual Summarization for Encyclopedic Text Generation in Low Resource Languages
Dhaval Taunk, Shivprasad Sagare, Anupam Patil +3
Lack of encyclopedic text contributors, especially on Wikipedia, makes automated text generation for low resource (LR) languages a critical problem. Existing work on Wikipedia text…
Summarizing Indian Languages using Multilingual Transformers based Models
Dhaval Taunk, Vasudeva Varma
With the advent of multilingual models like mBART, mT5, IndicBART etc., summarization in low resource Indian languages is getting a lot of attention now a days. But still the numbe…
Massively Multilingual Language Models for Cross Lingual Fact Extraction from Low Resource Indian Languages
Bhavyajeet Singh, Pavan Kandru, Anubhav Sharma +1
Massive knowledge graphs like Wikidata attempt to capture world knowledge about multiple entities. Recent approaches concentrate on automatically enriching these KGs from text. How…
Investigating Strategies for Clause Recommendation
Sagar Joshi, Sumanth Balaji, Jerrin Thomas +2
Clause recommendation is the problem of recommending a clause to a legal contract, given the context of the contract in question and the clause type to which the clause should belo…
Graph-based Keyword Planning for Legal Clause Generation from Topics
Sagar Joshi, Sumanth Balaji, Aparna Garimella +1
Generating domain-specific content such as legal clauses based on minimal user-provided information can be of significant benefit in automating legal contract generation. In this p…