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 [1].
Extending Analogical Generalization with Near-Misses
Authors: Matthew McLure, Scott Friedman, Kenneth Forbus
AAAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We show that ALIGN out-performs analogical generalization on two perceptual data sets: (1) hand-drawn sketches; and (2) geospatial concepts from strategy-game maps. |
| Researcher Affiliation | Collaboration | Matthew D. Mc Lure Qualitative Reasoning Group Northwestern University 2133 Sheridan Road Evanston, IL, 60208, USA EMAIL Scott E. Friedman Smart Information Flow Technologies (SIFT) Minneapolis, MN, USA EMAIL Kenneth D. Forbus Qualitative Reasoning Group Northwestern University 2133 Sheridan Road Evanston, IL, 60608, USA EMAIL |
| Pseudocode | Yes | Figure 5: ALIGN s top-level training and testing procedures. |
| Open Source Code | No | The paper does not provide any concrete access to source code (specific repository link, explicit code release statement, or code in supplementary materials) for the methodology described. |
| Open Datasets | No | The paper does not provide concrete access information (specific link, DOI, repository name, formal citation with authors/year, or reference to established benchmark datasets) for a publicly available or open dataset. It mentions using "hand-drawn sketches" and data from "Freeciv map" which appear to be collected for this work but no public access is provided. |
| Dataset Splits | Yes | Performance was evaluated via 4-fold cross-validation. Statistical significance was measured using a one-tailed, paired t-test. [...] 10-fold cross-validation was used. |
| Hardware Specification | No | The paper does not provide specific hardware details (exact GPU/CPU models, processor types with speeds, memory amounts, or detailed computer specifications) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers like Python 3.8, CPLEX 12.4) needed to replicate the experiment. |
| Experiment Setup | Yes | The similarity threshold for ALIGN was set to 0.8. This was also the assimilation threshold used for the Prototypes condition. |