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Akhil Arora

EPFL

16 papers hereh-index 11728 citations29 works total

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

author position
  • first author4
  • middle author7
  • last author5

Across the 16 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CL7
  • cs.SI4
  • cs.CY2
  • cs.DB2
  • cs.IR1
affiliations
  • EPFL
HomepageORCID 0000-0002-8650-8213
same name
  • Akhil Arora — 9 papers, h 2
  • Akhil Arora — 1 paper, h 1

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
20162025
most citedHolistic Influence Maximization: Combining Scalability and Efficiency with Opinion-Aware Models

110 citations · 245 across the 14 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.IR2022★ 5 cited

Quote Erat Demonstrandum: A Web Interface for Exploring the Quotebank Corpus

Vuk Vuković, Akhil Arora, Huan-Cheng Chang +2

The use of attributed quotes is the most direct and least filtered pathway of information propagation in news. Consequently, quotes play a central role in the conception, reception…

cs.CL2022

Strong Heuristics for Named Entity Linking

Marko Čuljak, Andreas Spitz, Robert West +1

Named entity linking (NEL) in news is a challenging endeavour due to the frequency of unseen and emerging entities, which necessitates the use of unsupervised or zero-shot methods.…

cs.CL2022

Efficient Entity Candidate Generation for Low-Resource Languages

Alberto García-Durán, Akhil Arora, Robert West

Candidate generation is a crucial module in entity linking. It also plays a key role in multiple NLP tasks that have been proven to beneficially leverage knowledge bases. Neverthel…

cs.CY2022★ 9 cited

Wikipedia Reader Navigation: When Synthetic Data Is Enough

Akhil Arora, Martin Gerlach, Tiziano Piccardi +2

Every day millions of people read Wikipedia. When navigating the vast space of available topics using hyperlinks, readers describe trajectories on the article network. Understandin…

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