most citedScaling Multi-Domain Dialogue State Tracking via Query Reformulation

9 citations · 16 across the 4 of their papers we have counts for

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cs.CL20191 cited

Representation Learning for Words and Entities

Pushpendre Rastogi

This thesis presents new methods for unsupervised learning of distributed representations of words and entities from text and knowledge bases. The first algorithm presented in the…

cs.CL20192 cited

Improving Long Distance Slot Carryover in Spoken Dialogue Systems

Tongfei Chen, Chetan Naik, Hua He +2

Tracking the state of the conversation is a central component in task-oriented spoken dialogue systems. One such approach for tracking the dialogue state is slot carryover, where a…

cs.CL20194 cited

A dataset for resolving referring expressions in spoken dialogue via contextual query rewrites (CQR)

Michael Regan, Pushpendre Rastogi, Arpit Gupta +1

We present Contextual Query Rewrite (CQR) a dataset for multi-domain task-oriented spoken dialogue systems that is an extension of the Stanford dialog corpus (Eric et al., 2017a).…

cs.CL20199 cited

Scaling Multi-Domain Dialogue State Tracking via Query Reformulation

Pushpendre Rastogi, Arpit Gupta, Tongfei Chen +1

We present a novel approach to dialogue state tracking and referring expression resolution tasks. Successful contextual understanding of multi-turn spoken dialogues requires resolv…

cs.CL2016

Problems With Evaluation of Word Embeddings Using Word Similarity Tasks

Manaal Faruqui, Yulia Tsvetkov, Pushpendre Rastogi +1

Lacking standardized extrinsic evaluation methods for vector representations of words, the NLP community has relied heavily on word similarity tasks as a proxy for intrinsic evalua…