81 citations · 121 across the 10 of their papers we have counts for
14 papers
Structsum Generation for Faster Text Comprehension
Parag Jain, Andreea Marzoca, Francesco Piccinno
We consider the task of generating structured representations of text using large language models (LLMs). We focus on tables and mind maps as representative modalities. Tables are…
Conversational Semantic Parsing using Dynamic Context Graphs
Parag Jain, Mirella Lapata
In this paper we consider the task of conversational semantic parsing over general purpose knowledge graphs (KGs) with millions of entities, and thousands of relation-types. We foc…
Semantic Parsing for Conversational Question Answering over Knowledge Graphs
Laura Perez-Beltrachini, Parag Jain, Emilio Monti +1
In this paper, we are interested in developing semantic parsers which understand natural language questions embedded in a conversation with a user and ground them to formal queries…
Multi-Document Summarization with Centroid-Based Pretraining
Ratish Puduppully, Parag Jain, Nancy F. Chen +1
In Multi-Document Summarization (MDS), the input can be modeled as a set of documents, and the output is its summary. In this paper, we focus on pretraining objectives for MDS. Spe…
Memory-Based Semantic Parsing
Parag Jain, Mirella Lapata
We present a memory-based model for context-dependent semantic parsing. Previous approaches focus on enabling the decoder to copy or modify the parse from the previous utterance, a…
Unified Semantic Parsing with Weak Supervision
Priyanka Agrawal, Parag Jain, Ayushi Dalmia +3
Semantic parsing over multiple knowledge bases enables a parser to exploit structural similarities of programs across the multiple domains. However, the fundamental challenge lies…
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…
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…
Story Generation from Sequence of Independent Short Descriptions
Parag Jain, Priyanka Agrawal, Abhijit Mishra +3
Existing Natural Language Generation (NLG) systems are weak AI systems and exhibit limited capabilities when language generation tasks demand higher levels of creativity, originali…
Topic Modeling Using Distributed Word Embeddings
Ramandeep S Randhawa, Parag Jain, Gagan Madan
We propose a new algorithm for topic modeling, Vec2Topic, that identifies the main topics in a corpus using semantic information captured via high-dimensional distributed word embe…
Bifurcation Phenomena in Two-Dimensional Piecewise Smooth Discontinuous Maps
Biswambhar Rakshit, Manjul Apratim, Parag Jain +1
In recent years the theory of border collision bifurcations has been developed for piecewise smooth maps that are continuous across the border, and has been successfully applied to…