41 citations · 244 across the 40 of their papers we have counts for
45 papers
Word Similarity Datasets for Indian Languages: Annotation and Baseline Systems
Syed S. Akhtar, Arihant Gupta, Avijit Vajpayee +2
With the advent of word representations, word similarity tasks are becoming increasing popular as an evaluation metric for the quality of the representations. In this paper, we pre…
MARCUS: An Event-Centric NLP Pipeline that generates Character Arcs from Narratives
Sriharsh Bhyravajjula, Ujwal Narayan, Manish Shrivastava
Character arcs are important theoretical devices employed in literary studies to understand character journeys, identify tropes across literary genres, and establish similarities b…
X-RiSAWOZ: High-Quality End-to-End Multilingual Dialogue Datasets and Few-shot Agents
Mehrad Moradshahi, Tianhao Shen, Kalika Bali +16
Task-oriented dialogue research has mainly focused on a few popular languages like English and Chinese, due to the high dataset creation cost for a new language. To reduce the cost…
PMIndiaSum: Multilingual and Cross-lingual Headline Summarization for Languages in India
Ashok Urlana, Pinzhen Chen, Zheng Zhao +3
This paper introduces PMIndiaSum, a multilingual and massively parallel summarization corpus focused on languages in India. Our corpus provides a training and testing ground for fo…
Attention at SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS)
Debashish Roy, Manish Shrivastava
In this paper, we have worked on interpretability, trust, and understanding of the decisions made by models in the form of classification tasks. The task is divided into 3 subtasks…
Indian Language Summarization using Pretrained Sequence-to-Sequence Models
Ashok Urlana, Sahil Manoj Bhatt, Nirmal Surange +1
The ILSUM shared task focuses on text summarization for two major Indian languages- Hindi and Gujarati, along with English. In this task, we experiment with various pretrained sequ…
Generalised Spherical Text Embedding
Souvik Banerjee, Bamdev Mishra, Pratik Jawanpuria +1
This paper aims to provide an unsupervised modelling approach that allows for a more flexible representation of text embeddings. It jointly encodes the words and the paragraphs as…
Diverse Multi-Answer Retrieval with Determinantal Point Processes
Poojitha Nandigam, Nikhil Rayaprolu, Manish Shrivastava
Often questions provided to open-domain question answering systems are ambiguous. Traditional QA systems that provide a single answer are incapable of answering ambiguous questions…
Leveraging Data Recasting to Enhance Tabular Reasoning
Aashna Jena, Vivek Gupta, Manish Shrivastava +1
Creating challenging tabular inference data is essential for learning complex reasoning. Prior work has mostly relied on two data generation strategies. The first is human annotati…
PreCogIIITH at HinglishEval : Leveraging Code-Mixing Metrics & Language Model Embeddings To Estimate Code-Mix Quality
Prashant Kodali, Tanmay Sachan, Akshay Goindani +4
Code-Mixing is a phenomenon of mixing two or more languages in a speech event and is prevalent in multilingual societies. Given the low-resource nature of Code-Mixing, machine gene…
HashSet -- A Dataset For Hashtag Segmentation
Prashant Kodali, Akshala Bhatnagar, Naman Ahuja +2
Hashtag segmentation is the task of breaking a hashtag into its constituent tokens. Hashtags often encode the essence of user-generated posts, along with information like topic and…
Battling Hateful Content in Indic Languages HASOC '21
Aditya Kadam, Anmol Goel, Jivitesh Jain +7
The extensive rise in consumption of online social media (OSMs) by a large number of people poses a critical problem of curbing the spread of hateful content on these platforms. Wi…
A Dynamic Head Importance Computation Mechanism for Neural Machine Translation
Akshay Goindani, Manish Shrivastava
Multiple parallel attention mechanisms that use multiple attention heads facilitate greater performance of the Transformer model for various applications e.g., Neural Machine Trans…
Is My Model Using The Right Evidence? Systematic Probes for Examining Evidence-Based Tabular Reasoning
Vivek Gupta, Riyaz A. Bhat, Atreya Ghosal +3
Neural models command state-of-the-art performance across NLP tasks, including ones involving "reasoning". Models claiming to reason about the evidence presented to them should att…
Volta at SemEval-2021 Task 9: Statement Verification and Evidence Finding with Tables using TAPAS and Transfer Learning
Devansh Gautam, Kshitij Gupta, Manish Shrivastava
Tables are widely used in various kinds of documents to present information concisely. Understanding tables is a challenging problem that requires an understanding of language and…
"Subverting the Jewtocracy": Online Antisemitism Detection Using Multimodal Deep Learning
Mohit Chandra, Dheeraj Pailla, Himanshu Bhatia +4
The exponential rise of online social media has enabled the creation, distribution, and consumption of information at an unprecedented rate. However, it has also led to the burgeon…
AbuseAnalyzer: Abuse Detection, Severity and Target Prediction for Gab Posts
Mohit Chandra, Ashwin Pathak, Eesha Dutta +4
While extensive popularity of online social media platforms has made information dissemination faster, it has also resulted in widespread online abuse of different types like hate…
Tag2Risk: Harnessing Social Music Tags for Characterizing Depression Risk
Aayush Surana, Yash Goyal, Manish Shrivastava +2
Musical preferences have been considered a mirror of the self. In this age of Big Data, online music streaming services allow us to capture ecologically valid music listening behav…
ConfNet2Seq: Full Length Answer Generation from Spoken Questions
Vaishali Pal, Manish Shrivastava, Laurent Besacier
Conversational and task-oriented dialogue systems aim to interact with the user using natural responses through multi-modal interfaces, such as text or speech. These desired respon…
Modeling ASR Ambiguity for Dialogue State Tracking Using Word Confusion Networks
Vaishali Pal, Fabien Guillot, Manish Shrivastava +2
Spoken dialogue systems typically use a list of top-N ASR hypotheses for inferring the semantic meaning and tracking the state of the dialogue. However ASR graphs, such as confusio…
Transition-Based Deep Input Linearization
Ratish Puduppully, Yue Zhang, Manish Shrivastava
Traditional methods for deep NLG adopt pipeline approaches comprising stages such as constructing syntactic input, predicting function words, linearizing the syntactic input and ge…
Curriculum Learning Strategies for Hindi-English Codemixed Sentiment Analysis
Anirudh Dahiya, Neeraj Battan, Manish Shrivastava +1
Sentiment Analysis and other semantic tasks are commonly used for social media textual analysis to gauge public opinion and make sense from the noise on social media. The language…
Predicting Algorithm Classes for Programming Word Problems
Vinayak Athavale, Aayush Naik, Rajas Vanjape +1
We introduce the task of algorithm class prediction for programming word problems. A programming word problem is a problem written in natural language, which can be solved using an…
SWDE : A Sub-Word And Document Embedding Based Engine for Clickbait Detection
Vaibhav Kumar, Mrinal Dhar, Dhruv Khattar +4
In order to expand their reach and increase website ad revenue, media outlets have started using clickbait techniques to lure readers to click on articles on their digital platform…