Revision by Comparison for Ranking Functions

Authors: Meliha Sezgin, Gabriele Kern-Isberner

IJCAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Theoretical The proofs in this paper are straightforward, but technical, and therefore omitted due to lack of space.
Researcher Affiliation Academia Meliha Sezgin and Gabriele Kern-Isberner TU Dortmund University, Germany {meliha.sezgin, gabriele.kern-isberner}@tu-dortmund.de
Pseudocode No The paper contains formal definitions, theorems, and mathematical expressions but does not include any pseudocode or clearly labeled algorithm blocks.
Open Source Code No The paper does not provide any statement about releasing source code or a link to a code repository.
Open Datasets No The paper is theoretical and does not use or reference any publicly available datasets for training or evaluation.
Dataset Splits No The paper is theoretical and does not discuss dataset splits (training, validation, test) for experimental reproduction.
Hardware Specification No The paper is theoretical and does not describe any specific hardware used for running experiments.
Software Dependencies No The paper is theoretical and does not list specific software dependencies with version numbers.
Experiment Setup No The paper is theoretical and does not describe an experimental setup with hyperparameters or training configurations.