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..
Incentive-Compatible Selection for One or Two Influentials
Authors: Yuxin Zhao, Yao Zhang, Dengji Zhao
IJCAI 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we first design a mechanism to actually reach the bound. Then, we move this forward to choosing two agents and propose a mechanism to achieve an approximation ratio of (3 + ln 2)/(4(1 + ln 2)) ( 0.54). Then, we show the mechanism is IC when β 1/2. Theorem 1. A β-logarithmic mechanism is IC if β 1/2. Theorem 8. LALD is 3+ln 2 4(1+ln 2)-optimal. |
| Researcher Affiliation | Academia | Yuxin Zhao , Yao Zhang and Dengji Zhao Shanghai Tech University EMAIL |
| Pseudocode | Yes | β-logarithmic Mechanism (β-LM) 1. Given a network G = (N, E), find the 1-influential set Sinf. 1 (G) = {i1, . . . , im}, where it it+1 for all 1 t < m. 2. Assign the probability of each agent to be selected as follows: |
| Open Source Code | No | No mention of open-source code or links to repositories for the described methodology. |
| Open Datasets | No | This is a theoretical paper that does not use datasets for training or evaluation. |
| Dataset Splits | No | This is a theoretical paper that does not involve validation datasets. |
| Hardware Specification | No | This is a theoretical paper that does not discuss hardware specifications for experiments. |
| Software Dependencies | No | This is a theoretical paper that does not list software dependencies with version numbers. |
| Experiment Setup | No | This is a theoretical paper that does not describe an experimental setup or hyperparameters. |