134 citations · 275 across the 23 of their papers we have counts for
5 papers · 1 filter
Fine-Grained Emotion Prediction by Modeling Emotion Definitions
Gargi Singh, Dhanajit Brahma, Piyush Rai +1
In this paper, we propose a new framework for fine-grained emotion prediction in the text through emotion definition modeling. Our approach involves a multi-task learning framework…
P-SIF: Document Embeddings Using Partition Averaging
Vivek Gupta, Ankit Saw, Pegah Nokhiz +3
Simple weighted averaging of word vectors often yields effective representations for sentences which outperform sophisticated seq2seq neural models in many tasks. While it is desir…
Deep Attentive Ranking Networks for Learning to Order Sentences
Pawan Kumar, Dhanajit Brahma, Harish Karnick +1
We present an attention-based ranking framework for learning to order sentences given a paragraph. Our framework is built on a bidirectional sentence encoder and a self-attention b…
Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks
Shikhar Vashishth, Manik Bhandari, Prateek Yadav +3
Word embeddings have been widely adopted across several NLP applications. Most existing word embedding methods utilize sequential context of a word to learn its embedding. While th…
A Deep Generative Framework for Paraphrase Generation
Ankush Gupta, Arvind Agarwal, Prawaan Singh +1
Paraphrase generation is an important problem in NLP, especially in question answering, information retrieval, information extraction, conversation systems, to name a few. In this…