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..
Distributional Rank Aggregation, and an Axiomatic Analysis
Authors: Adarsh Prasad, Harsh Pareek, Pradeep Ravikumar
ICML 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We present experiments to demonstrate this fact... Figure 1 shows the probability of success against the weight value w for both experiments. |
| Researcher Affiliation | Academia | Department of Computer Science, The University of Texas, Austin, TX 78712, USA |
| Pseudocode | No | The paper describes algorithms and procedures in text, but it does not include structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not contain any statements about making its source code publicly available or provide a link to a code repository. |
| Open Datasets | No | The paper generates data using "a mixture of two Mallows models" for its experiments, rather than using a pre-existing publicly available dataset with a specific access link or citation. |
| Dataset Splits | No | The paper describes the generation of data for experiments but does not specify training, validation, or test splits. It focuses on simulating distributions and aggregating them. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used to run the experiments (e.g., CPU/GPU models, memory). |
| Software Dependencies | No | The paper does not specify any software dependencies or their version numbers, such as programming languages, libraries, or frameworks used for implementation or experimentation. |
| Experiment Setup | Yes | In Experiment 1, we fix centers Z1 = {D, E, A, B, C} and Z2 = {B, C, D, E, A}, while in Experiment 2 we fix centers Z1 = {A, B, C, D, E} and Z2 = {B, C, D, E, A}. Then, for φ = 0.8, we vary w from 0.51 to 1.0. |