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..
The Price of Selfishness: Conjunctive Query Entailment for ALCSelf Is 2EXPTIME-Hard
Authors: Bartosz Bednarczyk, Sebastian Rudolph5495-5502
AAAI 2022 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | As common for this type of problem, our proof establishes a reduction from alternating Turing machines running in exponential space, but several novel ideas and encoding tricks are required to make the approach work in that specific, restricted setting. |
| Researcher Affiliation | Academia | Bartosz Bednarczyk,1,2 Sebastian Rudolph1 1 Computational Logic Group, Technische Universität Dresden, Germany 2 Institute of Computer Science, University of Wrocław, Poland EMAIL |
| Pseudocode | No | The paper does not contain any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper is theoretical and does not describe a software methodology for which code would be provided. |
| Open Datasets | No | The paper is theoretical and does not use datasets for training. |
| Dataset Splits | No | The paper is theoretical and does not describe experiments that would involve validation splits. |
| Hardware Specification | No | The paper is theoretical and does not mention any specific hardware used for running experiments. |
| Software Dependencies | No | The paper is theoretical and does not mention any specific software dependencies with version numbers for reproducibility. |
| Experiment Setup | No | The paper is theoretical and does not describe an experimental setup with hyperparameters or training configurations. |