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Pascal Vincent

4 papers hereh-index 468 citations4 works total

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

author position
  • middle author3
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • cs.CL1
same name
  • Pascal Vincent — 19 papers, h 21
  • Pascal Vincent — 7 papers
  • Pascal Vincent — 5 papers, h 7
  • Pascal Vincent — 4 papers, h 3
  • Pascal Vincent — 4 papers, h 6
  • Pascal Vincent — 2 papers

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

most citedClustering is Efficient for Approximate Maximum Inner Product Search

24 citations · 25 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2023★ 1 cited

WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models

Youssef Benchekroun, Megi Dervishi, Mark Ibrahim +7

We propose WorldSense, a benchmark designed to assess the extent to which LLMs are consistently able to sustain tacit world models, by testing how they draw simple inferences from…

cs.LG2023

Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations

Cian Eastwood, Julius von Kügelgen, Linus Ericsson +4

Self-supervised representation learning often uses data augmentations to induce some invariance to "style" attributes of the data. However, with downstream tasks generally unknown…

cs.LG2023

Discovering environments with XRM

Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim +3

Environment annotations are essential for the success of many out-of-distribution (OOD) generalization methods. Unfortunately, these are costly to obtain and often limited by human…

cs.LG2015★ 24 cited

Clustering is Efficient for Approximate Maximum Inner Product Search

Alex Auvolat, Sarath Chandar, Pascal Vincent +2

Efficient Maximum Inner Product Search (MIPS) is an important task that has a wide applicability in recommendation systems and classification with a large number of classes. Soluti…

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