The Natural Language of Actions
Authors: Guy Tennenholtz, Shie Mannor
ICML 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We visualize and test action embeddings in three domains including a drawing task, a high dimensional navigation task, and the large action space domain of Star Craft II. |
| Researcher Affiliation | Academia | 1Faculty of Electrical Engineering, Technion Institute of Technology, Israel. Correspondence to: Guy Tennenholtz <guytenn@gmail.com>, Shie Mannor <shie@technion.ac.il>. |
| Pseudocode | No | No pseudocode or algorithm blocks were found. |
| Open Source Code | No | The paper mentions 'A detailed overview of the training process can be found in the supplementary material' and 'Additional technical details can be found in the supplementary material', but does not explicitly state that source code is released or provide a link to it. |
| Open Datasets | Yes | We trained Act2Vec with action-only context over a corpus of 70,000 human-made drawings in the square category of the Quick, Draw! (Cheema et al., 2012) dataset. |
| Dataset Splits | No | The paper discusses experiments and results but does not explicitly state specific train/validation/test dataset splits (e.g., percentages or counts) or detailed splitting methodology. |
| Hardware Specification | No | The paper does not provide specific hardware details (e.g., exact GPU/CPU models, processor types, or memory amounts) used for running its experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details, such as library names with version numbers (e.g., Python 3.8, PyTorch 1.9), needed to replicate the experiment. |
| Experiment Setup | No | The paper states that 'A detailed overview of the training process can be found in the supplementary material' and 'Additional technical details can be found in the supplementary material', implying setup details are external to the main text. No specific hyperparameter values or training configurations are provided in the main body of the paper. |