Inverse Problems for Gradual Semantics
Authors: Nir Oren, Bruno Yun, Srdjan Vesic, Murilo Baptista
IJCAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Our empirical evaluation is detailed in Section 5. We evaluated each of the strategies discussed in Section 3.3 over directed scale-free, small world (Erdos-Renyi), and complete graphs of different sizes. |
| Researcher Affiliation | Academia | 1University of Aberdeen 2CNRS, Univ. Artois, CRIL, France |
| Pseudocode | Yes | Algorithm 1 The bisection method. Algorithm 2 Computing arguments minimal upper bounds |
| Open Source Code | Yes | Source code for our algorithm and evaluation can be found on Git Hub at https://github.com/jhudsy/numerical inverse. |
| Open Datasets | No | The paper evaluates on 'directed scale-free, small world (Erdos-Renyi), and complete graphs of different sizes' which appear to be generated for the experiments, rather than being a named, publicly accessible dataset with explicit access information (link, DOI, or formal citation). |
| Dataset Splits | No | The paper describes creating a 'simple target preference ordering' and evaluating strategies, but does not mention specific training, validation, or test dataset splits, percentages, or cross-validation schemes. |
| Hardware Specification | No | The paper does not provide specific hardware details such as exact GPU/CPU models, memory amounts, or cloud instance types used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies, such as library names with version numbers (e.g., Python 3.8, PyTorch 1.9), used for the experiments. |
| Experiment Setup | Yes | As part of our evaluation, we ran 10, 100 and 2000 iterations of the bisection method for each argument... Table 2 describes the remaining parameters used in our evaluation. Parameters used in our evaluation: ζ: 1, Graph Size: 10, 20, ..., 150, Runs per graph size: 15, Erdos-Renyi probability: 0.1, 0.3, 0.5, 0.7, Maximum relative error: 0.001, Bisection method iterations: 10, 100, 2000, Bisection method ϵ: 0.001, Maximum bisection method calls: 1000. |