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Raghav Gupta

Chan Zuckerberg Biohub

10 papers hereh-index 111.6k citations17 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author8
  • last author1

Across the 10 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CL8
  • cs.AI1
  • cs.LO1
affiliations
  • Chan Zuckerberg Biohub
Homepage
same name
  • Raghav Gupta — 6 papers, h 6
  • Raghav Gupta — 4 papers, h 3
  • Raghav Gupta — 2 papers, h 2
  • Raghav Gupta — 1 paper
  • Raghav Gupta — 1 paper
  • Raghav Gupta — 1 paper, h 9

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20142020
most citedThe Eighth Dialog System Technology Challenge

53 citations · 127 across the 7 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CL2019★ 53 cited

The Eighth Dialog System Technology Challenge

Seokhwan Kim, Michel Galley, Chulaka Gunasekara +18

This paper introduces the Eighth Dialog System Technology Challenge. In line with recent challenges, the eighth edition focuses on applying end-to-end dialog technologies in a prag…

cs.CL2019

Extremely Small BERT Models from Mixed-Vocabulary Training

Sanqiang Zhao, Raghav Gupta, Yang Song +1

Pretrained language models like BERT have achieved good results on NLP tasks, but are impractical on resource-limited devices due to memory footprint. A large fraction of this foot…

cs.CL2019★ 3 cited

Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset

Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara +2

Virtual assistants such as Google Assistant, Alexa and Siri provide a conversational interface to a large number of services and APIs spanning multiple domains. Such systems need t…

cs.CL2019

Robust Zero-Shot Cross-Domain Slot Filling with Example Values

Darsh J Shah, Raghav Gupta, Amir A Fayazi +1

Task-oriented dialog systems increasingly rely on deep learning-based slot filling models, usually needing extensive labeled training data for target domains. Often, however, littl…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.