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..
Quantum Lower Bounds for Finding Stationary Points of Nonconvex Functions
Authors: Chenyi Zhang, Tongyang Li
ICML 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we conduct a systematic study of quantum lower bounds on finding ϵapproximate stationary points of nonconvex functions |
| Researcher Affiliation | Academia | 1Computer Science Department, Stanford University 2Institute for Interdisciplinary Information Sciences, Tsinghua University 3Center on Frontiers of Computing Studies, Peking University 4School of Computer Science, Peking University. |
| Pseudocode | No | The paper describes theoretical concepts and proofs, but does not include any pseudocode or algorithm blocks. |
| Open Source Code | No | The paper focuses on theoretical lower bounds and does not mention releasing any source code for the described work. |
| Open Datasets | No | This is a theoretical paper focusing on lower bounds and proofs. It does not involve experimental training with datasets. |
| Dataset Splits | No | This is a theoretical paper focusing on lower bounds and proofs. It does not involve experimental validation with datasets. |
| Hardware Specification | No | As a theoretical paper, no experiments requiring specific hardware were conducted, and thus, no hardware specifications are mentioned. |
| Software Dependencies | No | As a theoretical paper, no experiments requiring specific software dependencies with version numbers were conducted. |
| Experiment Setup | No | As a theoretical paper, no experiments were set up, and therefore, no details such as hyperparameters or training settings are provided. |