25 citations · 101 across the 15 of their papers we have counts for
21 papers
Vārta: A Large-Scale Headline-Generation Dataset for Indic Languages
Rahul Aralikatte, Ziling Cheng, Sumanth Doddapaneni +1
We present Vārta, a large-scale multilingual dataset for headline generation in Indic languages. This dataset includes 41.8 million news articles in 14 different Indic languages (a…
Towards Leaving No Indic Language Behind: Building Monolingual Corpora, Benchmark and Models for Indic Languages
Sumanth Doddapaneni, Rahul Aralikatte, Gowtham Ramesh +4
Building Natural Language Understanding (NLU) capabilities for Indic languages, which have a collective speaker base of more than one billion speakers is absolutely crucial. In thi…
Compositional Generalization in Multilingual Semantic Parsing over Wikidata
Ruixiang Cui, Rahul Aralikatte, Heather Lent +1
Semantic parsing (SP) allows humans to leverage vast knowledge resources through natural interaction. However, parsers are mostly designed for and evaluated on English resources, s…
Minimax and Neyman-Pearson Meta-Learning for Outlier Languages
Edoardo Maria Ponti, Rahul Aralikatte, Disha Shrivastava +2
Model-agnostic meta-learning (MAML) has been recently put forth as a strategy to learn resource-poor languages in a sample-efficient fashion. Nevertheless, the properties of these…
Itihasa: A large-scale corpus for Sanskrit to English translation
Rahul Aralikatte, Miryam de Lhoneux, Anoop Kunchukuttan +1
This work introduces Itihasa, a large-scale translation dataset containing 93,000 pairs of Sanskrit shlokas and their English translations. The shlokas are extracted from two India…
Focus Attention: Promoting Faithfulness and Diversity in Summarization
Rahul Aralikatte, Shashi Narayan, Joshua Maynez +2
Professional summaries are written with document-level information, such as the theme of the document, in mind. This is in contrast with most seq2seq decoders which simultaneously…
Joint Semantic Analysis with Document-Level Cross-Task Coherence Rewards
Rahul Aralikatte, Mostafa Abdou, Heather Lent +2
Coreference resolution and semantic role labeling are NLP tasks that capture different aspects of semantics, indicating respectively, which expressions refer to the same entity, an…
Compositional Generalization in Image Captioning
Mitja Nikolaus, Mostafa Abdou, Matthew Lamm +2
Image captioning models are usually evaluated on their ability to describe a held-out set of images, not on their ability to generalize to unseen concepts. We study the problem of…
Rewarding Coreference Resolvers for Being Consistent with World Knowledge
Rahul Aralikatte, Heather Lent, Ana Valeria Gonzalez +5
Unresolved coreference is a bottleneck for relation extraction, and high-quality coreference resolvers may produce an output that makes it a lot easier to extract knowledge triples…
X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension
Mostafa Abdou, Cezar Sas, Rahul Aralikatte +2
Although the vast majority of knowledge bases KBs are heavily biased towards English, Wikipedias do cover very different topics in different languages. Exploiting this, we introduc…
Ellipsis Resolution as Question Answering: An Evaluation
Rahul Aralikatte, Matthew Lamm, Daniel Hardt +1
Most, if not all forms of ellipsis (e.g., so does Mary) are similar to reading comprehension questions (what does Mary do), in that in order to resolve them, we need to identify an…
Model-based annotation of coreference
Rahul Aralikatte, Anders Søgaard
Humans do not make inferences over texts, but over models of what texts are about. When annotators are asked to annotate coreferent spans of text, it is therefore a somewhat unnatu…
A Visual Programming Paradigm for Abstract Deep Learning Model Development
Srikanth Tamilselvam, Naveen Panwar, Shreya Khare +3
Deep learning is one of the fastest growing technologies in computer science with a plethora of applications. But this unprecedented growth has so far been limited to the consumpti…
Adversarial Black-Box Attacks on Automatic Speech Recognition Systems using Multi-Objective Evolutionary Optimization
Shreya Khare, Rahul Aralikatte, Senthil Mani
Fooling deep neural networks with adversarial input have exposed a significant vulnerability in the current state-of-the-art systems in multiple domains. Both black-box and white-b…
DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension
Amrita Saha, Rahul Aralikatte, Mitesh M. Khapra +1
We propose DuoRC, a novel dataset for Reading Comprehension (RC) that motivates several new challenges for neural approaches in language understanding beyond those offered by exist…
DeepTriage: Exploring the Effectiveness of Deep Learning for Bug Triaging
Senthil Mani, Anush Sankaran, Rahul Aralikatte
For a given software bug report, identifying an appropriate developer who could potentially fix the bug is the primary task of a bug triaging process. A bug title (summary) and a d…
Sanskrit Sandhi Splitting using seq2(seq)^2
Rahul Aralikatte, Neelamadhav Gantayat, Naveen Panwar +2
In Sanskrit, small words (morphemes) are combined to form compound words through a process known as Sandhi. Sandhi splitting is the process of splitting a given compound word into…
Hi, how can I help you?: Automating enterprise IT support help desks
Senthil Mani, Neelamadhav Gantayat, Rahul Aralikatte +7
Question answering is one of the primary challenges of natural language understanding. In realizing such a system, providing complex long answers to questions is a challenging task…
mAnI: Movie Amalgamation using Neural Imitation
Naveen Panwar, Shreya Khare, Neelamadhav Gantayat +3
Cross-modal data retrieval has been the basis of various creative tasks performed by Artificial Intelligence (AI). One such highly challenging task for AI is to convert a book into…
DARVIZ: Deep Abstract Representation, Visualization, and Verification of Deep Learning Models
Anush Sankaran, Rahul Aralikatte, Senthil Mani +3
Traditional software engineering programming paradigms are mostly object or procedure oriented, driven by deterministic algorithms. With the advent of deep learning and cognitive s…
Fault in your stars: An Analysis of Android App Reviews
Rahul Aralikatte, Giriprasad Sridhara, Neelamadhav Gantayat +1
Mobile app distribution platforms such as Google Play Store allow users to share their feedback about downloaded apps in the form of a review comment and a corresponding star ratin…