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20142026
most citedAn Autoencoder Approach to Learning Bilingual Word Representations

326 citations · 717 across the 90 of their papers we have counts for

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Showing 2019Show all

7 papers · 1 filter

cs.AI2019★ 9 cited

Scene Graph based Image Retrieval -- A case study on the CLEVR Dataset

Sahana Ramnath, Amrita Saha, Soumen Chakrabarti +1

With the prolification of multimodal interaction in various domains, recently there has been much interest in text based image retrieval in the computer vision community. However m…

cs.CV2019

PlotQA: Reasoning over Scientific Plots

Nitesh Methani, Pritha Ganguly, Mitesh M. Khapra +1

Existing synthetic datasets (FigureQA, DVQA) for reasoning over plots do not contain variability in data labels, real-valued data, or complex reasoning questions. Consequently, pro…

cs.CL2019★ 2 cited

Let's Ask Again: Refine Network for Automatic Question Generation

Preksha Nema, Akash Kumar Mohankumar, Mitesh M. Khapra +2

In this work, we focus on the task of Automatic Question Generation (AQG) where given a passage and an answer the task is to generate the corresponding question. It is desired that…

cs.CL2019

Frustratingly Poor Performance of Reading Comprehension Models on Non-adversarial Examples

Soham Parikh, Ananya B. Sai, Preksha Nema +1

When humans learn to perform a difficult task (say, reading comprehension (RC) over longer passages), it is typically the case that their performance improves significantly on an e…

cs.CL2019★ 1 cited

ElimiNet: A Model for Eliminating Options for Reading Comprehension with Multiple Choice Questions

Soham Parikh, Ananya B. Sai, Preksha Nema +1

The task of Reading Comprehension with Multiple Choice Questions, requires a human (or machine) to read a given passage, question pair and select one of the n given options. The cu…

cs.CV2019★ 4 cited

Efficient Video Classification Using Fewer Frames

Shweta Bhardwaj, Mukundhan Srinivasan, Mitesh M. Khapra

Recently,there has been a lot of interest in building compact models for video classification which have a small memory footprint (<1 GB). While these models are compact, they typi…

cs.CL2019★ 8 cited

Re-evaluating ADEM: A Deeper Look at Scoring Dialogue Responses

Ananya B. Sai, Mithun Das Gupta, Mitesh M. Khapra +1

Automatically evaluating the quality of dialogue responses for unstructured domains is a challenging problem. ADEM(Lowe et al. 2017) formulated the automatic evaluation of dialogue…