Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Paging with Succinct Predictions
Authors: Antonios Antoniadis, Joan Boyar, Marek Elias, Lene Monrad Favrholdt, Ruben Hoeksma, Kim S. Larsen, Adam Polak, Bertrand Simon
ICML 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | We develop algorithms satisfy all three desirable properties of learning-augmented algorithms that is, they are consistent, robust and smooth despite being limited to a one-bit prediction per request. We also present lower bounds establishing that our algorithms are essentially best possible. |
| Researcher Affiliation | Academia | 1University of Twente, Enschede, Netherlands 2University of Southern Denmark, Odense, Denmark 3Bocconi University, Milan, Italy 4Max Planck Institute for Informatics, Saarbr ucken, Germany 5IN2P3 Computing Center and CNRS, Villeurbanne, France. |
| Pseudocode | Yes | Algorithm 1 MARK0 Eviction Strategy; Algorithm 2 MARK&PREDICT Eviction Strategy |
| Open Source Code | No | This paper is theoretical and does not mention releasing source code. |
| Open Datasets | No | This paper is theoretical and does not use datasets for training. |
| Dataset Splits | No | This paper is theoretical and does not report on experiments requiring dataset splits. |
| Hardware Specification | No | This paper is theoretical and does not describe hardware used for experiments. |
| Software Dependencies | No | This paper is theoretical and does not mention specific software dependencies with version numbers for implementation. |
| Experiment Setup | No | This paper is theoretical and does not include details on experimental setup or hyperparameters. |