Diagram Understanding in Geometry Questions
Authors: Min Joon Seo, Hannaneh Hajishirzi, Ali Farhadi, Oren Etzioni
AAAI 2014 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | To empirically evaluate our method, we compile a new dataset of geometry questions (textual descriptions and diagrams) and compare with baselines that utilize standard vision techniques. Our experimental evaluation shows an F1 boost of more than 17% in identifying visual elements and 25% in aligning visual elements with their textual descriptions. |
| Researcher Affiliation | Collaboration | 1University of Washington, 2Allen Institute for AI |
| Pseudocode | Yes | Figure 2: G-ALIGNER: Method for coupling primitive identiļ¬cation and alignment. |
| Open Source Code | No | The paper states 'Our dataset and a demo of G-ALIGNER are publicly available at:http://cs.washington.edu/research/ai/geometry'. This links to a project page and a demo, but does not explicitly provide direct access to the source code for the described methodology. |
| Open Datasets | Yes | The dataset is publicly available in our project web page. 1Our dataset and a demo of G-ALIGNER are publicly available at:http://cs.washington.edu/research/ai/geometry |
| Dataset Splits | No | The paper mentions evaluating against a 'ground truth dataset' but does not specify explicit training, validation, or test splits (e.g., percentages or sample counts for each partition). |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., GPU models, CPU types) used for running the experiments. |
| Software Dependencies | No | The paper mentions using tools like 'Hough transform' and an 'OCR package of Tesseract', but it does not specify any version numbers for these or other software dependencies. |
| Experiment Setup | No | The paper discusses 'parameters' for Hough transform but states their method is 'not sensitive to the choice of parameters' and does not provide specific hyperparameter values or detailed system-level training configurations for reproduction. |