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Pedro Szekely

3 papers here

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

author position
  • last author2

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • cs.AI2
  • cs.CR1
ORCID 0000-0002-4621-2266

identity via Semantic Scholar / OpenAlex

most citedEvaluating the Feasibility of a Provably Secure Privacy-Preserving Entity Resolution Adaptation of PPJoin using Homomorphic Encryption

1 citations · 1 across the 3 of their papers we have counts for

collaborators

3 papers

cs.AI2024

Speechworthy Instruction-tuned Language Models

Hyundong Cho, Nicolaas Jedema, Leonardo F. R. Ribeiro +5

Current instruction-tuned language models are exclusively trained with textual preference data and thus are often not aligned with the unique requirements of other modalities, such…

cs.CR2022★ 1 cited

Evaluating the Feasibility of a Provably Secure Privacy-Preserving Entity Resolution Adaptation of PPJoin using Homomorphic Encryption

Tanmay Ghai, Yixiang Yao, Srivatsan Ravi +1

Entity resolution is the task of disambiguating records that refer to the same entity in the real world. In this work, we explore adapting one of the most efficient and accurate Ja…

cs.AI2022

Enriching Wikidata with Linked Open Data

Bohui Zhang, Filip Ilievski, Pedro Szekely

Large public knowledge graphs, like Wikidata, contain billions of statements about tens of millions of entities, thus inspiring various use cases to exploit such knowledge graphs.…

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