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Celestine Mendler-Dünner

Max Planck Institute for Intelligent Systems

31 papers hereh-index 171.4k citations45 works total

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

author position
  • first author9
  • middle author14
  • last author8

Across the 31 of 31 papers where every author was matched, so the position is known.

fields
  • cs.LG21
  • cs.IR3
  • stat.ML2
  • cs.CY1
  • cs.DC1
  • cs.GT1
affiliations
  • Max Planck Institute for Intelligent Systems
Homepage
same name
  • Celestine Mendler-Dünner — 1 paper, h 0

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
20162026
most citedStochastic Optimization for Performative Prediction

25 citations · 125 across the 27 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.GT2024★ 1 cited

Decline Now: A Combinatorial Model for Algorithmic Collective Action

Dorothee Sigg, Moritz Hardt, Celestine Mendler-Dünner

Drivers on food delivery platforms often run a loss on low-paying orders. In response, workers on DoorDash started a campaign, #DeclineNow, to purposefully decline orders below a c…

cs.LG2024

Evaluating language models as risk scores

André F. Cruz, Moritz Hardt, Celestine Mendler-Dünner

Current question-answering benchmarks predominantly focus on accuracy in realizable prediction tasks. Conditioned on a question and answer-key, does the most likely token match the…

cs.CY2024

An engine not a camera: Measuring performative power of online search

Celestine Mendler-Dünner, Gabriele Carovano, Moritz Hardt

The power of digital platforms is at the center of major ongoing policy and regulatory efforts. To advance existing debates, we designed and executed an experiment to measure the p…

cs.IR2024★ 1 cited

Algorithmic Collective Action in Recommender Systems: Promoting Songs by Reordering Playlists

Joachim Baumann, Celestine Mendler-Dünner

We investigate algorithmic collective action in transformer-based recommender systems. Our use case is a music streaming platform where a collective of fans aims to promote the vis…

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