81 citations · 226 across the 16 of their papers we have counts for
9 papers · 1 filter
On Controllable Sparse Alternatives to Softmax
Anirban Laha, Saneem A. Chemmengath, Priyanka Agrawal +3
Converting an n-dimensional vector to a probability distribution over n objects is a commonly used component in many machine learning tasks like multiclass classification, multilab…
Unsupervised Neural Text Simplification
Sai Surya, Abhijit Mishra, Anirban Laha +2
The paper presents a first attempt towards unsupervised neural text simplification that relies only on unlabeled text corpora. The core framework is composed of a shared encoder an…
Scalable Micro-planned Generation of Discourse from Structured Data
Anirban Laha, Parag Jain, Abhijit Mishra +1
We present a framework for generating natural language description from structured data such as tables; the problem comes under the category of data-to-text natural language genera…
Modeling Topical Coherence in Discourse without Supervision
Disha Shrivastava, Abhijit Mishra, Karthik Sankaranarayanan
Coherence of text is an important attribute to be measured for both manually and automatically generated discourse; but well-defined quantitative metrics for it are still elusive.…
Unsupervised Controllable Text Formalization
Parag Jain, Abhijit Mishra, Amar Prakash Azad +1
We propose a novel framework for controllable natural language transformation. Realizing that the requirement of parallel corpus is practically unsustainable for controllable gener…
A Mixed Hierarchical Attention based Encoder-Decoder Approach for Standard Table Summarization
Parag Jain, Anirban Laha, Karthik Sankaranarayanan +3
Structured data summarization involves generation of natural language summaries from structured input data. In this work, we consider summarizing structured data occurring in the f…
Generating Descriptions from Structured Data Using a Bifocal Attention Mechanism and Gated Orthogonalization
Preksha Nema, Shreyas Shetty, Parag Jain +3
In this work, we focus on the task of generating natural language descriptions from a structured table of facts containing fields (such as nationality, occupation, etc) and values…
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…
Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph
Amrita Saha, Vardaan Pahuja, Mitesh M. Khapra +2
While conversing with chatbots, humans typically tend to ask many questions, a significant portion of which can be answered by referring to large-scale knowledge graphs (KG). While…