39 citations · 66 across the 7 of their papers we have counts for
6 papers · 1 filter
Discourse Context Predictability Effects in Hindi Word Order
Sidharth Ranjan, Marten van Schijndel, Sumeet Agarwal +1
We test the hypothesis that discourse predictability influences Hindi syntactic choice. While prior work has shown that a number of factors (e.g., information status, dependency le…
Dual Mechanism Priming Effects in Hindi Word Order
Sidharth Ranjan, Marten van Schijndel, Sumeet Agarwal +1
Word order choices during sentence production can be primed by preceding sentences. In this work, we test the DUAL MECHANISM hypothesis that priming is driven by multiple different…
DECAF: Deep Extreme Classification with Label Features
Anshul Mittal, Kunal Dahiya, Sheshansh Agrawal +4
Extreme multi-label classification (XML) involves tagging a data point with its most relevant subset of labels from an extremely large label set, with several applications such as…
ECLARE: Extreme Classification with Label Graph Correlations
Anshul Mittal, Noveen Sachdeva, Sheshansh Agrawal +3
Deep extreme classification (XC) seeks to train deep architectures that can tag a data point with its most relevant subset of labels from an extremely large label set. The core uti…
Can RNNs trained on harder subject-verb agreement instances still perform well on easier ones?
Hritik Bansal, Gantavya Bhatt, Sumeet Agarwal
Previous work suggests that RNNs trained on natural language corpora can capture number agreement well for simple sentences but perform less well when sentences contain agreement a…
How much complexity does an RNN architecture need to learn syntax-sensitive dependencies?
Gantavya Bhatt, Hritik Bansal, Rishubh Singh +1
Long short-term memory (LSTM) networks and their variants are capable of encapsulating long-range dependencies, which is evident from their performance on a variety of linguistic t…