21 citations · 121 across the 26 of their papers we have counts for
26 papers
MIDR: Enrichment-Augmented Indexing for Multimodal Document Retrieval
Debanjan Mahata, Atharva Tendle, Daniel Preotiuc-Pietro +2
Retrieval over visually rich documents has a representation problem: important content often lives in tables, charts, figures, and layout relations that plain OCR linearizes, corru…
M3DocRAG: Multi-modal Retrieval is What You Need for Multi-page Multi-document Understanding
Jaemin Cho, Debanjan Mahata, Ozan Irsoy +2
Document visual question answering (DocVQA) pipelines that answer questions from documents have broad applications. Existing methods focus on handling single-page documents with mu…
Enhancing Keyphrase Extraction from Long Scientific Documents using Graph Embeddings
Roberto Martínez-Cruz, Debanjan Mahata, Alvaro J. López-López +1
In this study, we investigate using graph neural network (GNN) representations to enhance contextualized representations of pre-trained language models (PLMs) for keyphrase extract…
LDKP: A Dataset for Identifying Keyphrases from Long Scientific Documents
Debanjan Mahata, Navneet Agarwal, Dibya Gautam +5
Identifying keyphrases (KPs) from text documents is a fundamental task in natural language processing and information retrieval. Vast majority of the benchmark datasets for this ta…
On the Evaluation of Answer-Agnostic Paragraph-level Multi-Question Generation
Jishnu Ray Chowdhury, Debanjan Mahata, Cornelia Caragea
We study the task of predicting a set of salient questions from a given paragraph without any prior knowledge of the precise answer. We make two main contributions. First, we propo…
Learning Rich Representation of Keyphrases from Text
Mayank Kulkarni, Debanjan Mahata, Ravneet Arora +1
In this work, we explore how to train task-specific language models aimed towards learning rich representation of keyphrases from text documents. We experiment with different maski…
On the Use of Context for Predicting Citation Worthiness of Sentences in Scholarly Articles
Rakesh Gosangi, Ravneet Arora, Mohsen Gheisarieha +2
In this paper, we study the importance of context in predicting the citation worthiness of sentences in scholarly articles. We formulate this problem as a sequence labeling task so…
GupShup: An Annotated Corpus for Abstractive Summarization of Open-Domain Code-Switched Conversations
Laiba Mehnaz, Debanjan Mahata, Rakesh Gosangi +7
Code-switching is the communication phenomenon where speakers switch between different languages during a conversation. With the widespread adoption of conversational agents and ch…
Get It Scored Using AutoSAS -- An Automated System for Scoring Short Answers
Yaman Kumar, Swati Aggarwal, Debanjan Mahata +3
In the era of MOOCs, online exams are taken by millions of candidates, where scoring short answers is an integral part. It becomes intractable to evaluate them by human graders. Th…
MIDAS at SemEval-2020 Task 10: Emphasis Selection using Label Distribution Learning and Contextual Embeddings
Sarthak Anand, Pradyumna Gupta, Hemant Yadav +4
This paper presents our submission to the SemEval 2020 - Task 10 on emphasis selection in written text. We approach this emphasis selection problem as a sequence labeling task wher…
Trawling for Trolling: A Dataset
Hitkul, Karmanya Aggarwal, Pakhi Bamdev +3
The ability to accurately detect and filter offensive content automatically is important to ensure a rich and diverse digital discourse. Trolling is a type of hurtful or offensive…
An Iterative Approach for Identifying Complaint Based Tweets in Social Media Platforms
Gyanesh Anand, Akash Gautam, Puneet Mathur +3
Twitter is a social media platform where users express opinions over a variety of issues. Posts offering grievances or complaints can be utilized by private/ public organizations t…
#MeTooMA: Multi-Aspect Annotations of Tweets Related to the MeToo Movement
Akash Gautam, Puneet Mathur, Rakesh Gosangi +3
In this paper, we present a dataset containing 9,973 tweets related to the MeToo movement that were manually annotated for five different linguistic aspects: relevance, stance, hat…
Keyphrase Extraction from Scholarly Articles as Sequence Labeling using Contextualized Embeddings
Dhruva Sahrawat, Debanjan Mahata, Mayank Kulkarni +7
In this paper, we formulate keyphrase extraction from scholarly articles as a sequence labeling task solved using a BiLSTM-CRF, where the words in the input text are represented us…
BHAAV- A Text Corpus for Emotion Analysis from Hindi Stories
Yaman Kumar, Debanjan Mahata, Sagar Aggarwal +3
In this paper, we introduce the first and largest Hindi text corpus, named BHAAV, which means emotions in Hindi, for analyzing emotions that a writer expresses through his characte…
Keyphrase Generation for Scientific Articles using GANs
Avinash Swaminathan, Raj Kuwar Gupta, Haimin Zhang +3
In this paper, we present a keyphrase generation approach using conditional Generative Adversarial Networks (GAN). In our GAN model, the generator outputs a sequence of keyphrases…
MobiVSR: A Visual Speech Recognition Solution for Mobile Devices
Nilay Shrivastava, Astitwa Saxena, Yaman Kumar +3
Visual speech recognition (VSR) is the task of recognizing spoken language from video input only, without any audio. VSR has many applications as an assistive technology, especiall…
Suggestion Mining from Online Reviews using ULMFiT
Sarthak Anand, Debanjan Mahata, Kartik Aggarwal +6
In this paper we present our approach and the system description for Sub Task A of SemEval 2019 Task 9: Suggestion Mining from Online Reviews and Forums. Given a sentence, the task…
Identifying Offensive Posts and Targeted Offense from Twitter
Haimin Zhang, Debanjan Mahata, Simra Shahid +5
In this paper we present our approach and the system description for Sub-task A and Sub Task B of SemEval 2019 Task 6: Identifying and Categorizing Offensive Language in Social Med…
Harnessing GANs for Zero-shot Learning of New Classes in Visual Speech Recognition
Yaman Kumar, Dhruva Sahrawat, Shubham Maheshwari +5
Visual Speech Recognition (VSR) is the process of recognizing or interpreting speech by watching the lip movements of the speaker. Recent machine learning based approaches model VS…
Kiki Kills: Identifying Dangerous Challenge Videos from Social Media
Nupur Baghel, Yaman Kumar, Paavini Nanda +3
There has been upsurge in the number of people participating in challenges made popular through social media channels. One of the examples of such a challenge is the Kiki Challenge…
Did you take the pill? - Detecting Personal Intake of Medicine from Twitter
Debanjan Mahata, Jasper Friedrichs, Rajiv Ratn Shah +1
Mining social media messages such as tweets, articles, and Facebook posts for health and drug related information has received significant interest in pharmacovigilance research. S…
Theme-weighted Ranking of Keywords from Text Documents using Phrase Embeddings
Debanjan Mahata, John Kuriakose, Rajiv Ratn Shah +2
Keyword extraction is a fundamental task in natural language processing that facilitates mapping of documents to a concise set of representative single and multi-word phrases. Keyw…
A Multimodal Approach to Predict Social Media Popularity
Mayank Meghawat, Satyendra Yadav, Debanjan Mahata +3
Multiple modalities represent different aspects by which information is conveyed by a data source. Modern day social media platforms are one of the primary sources of multimodal da…