Can Pre-Trained Text-to-Image Models Generate Visual Goals for Reinforcement Learning?
Authors: Jialu Gao, Kaizhe Hu, Guowei Xu, Huazhe Xu
NeurIPS 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate Lf Void across three simulated tasks and validate its feasibility in the corresponding realworld scenarios. |
| Researcher Affiliation | Academia | Jialu Gao1 , Kaizhe Hu1,2,3 , Guowei Xu1, Huazhe Xu1,2,3 1 Tsinghua University 2 Shanghai Qi Zhi Institute 3 Shanghai AI Lab |
| Pseudocode | Yes | we provide a detailed description of the full algorithm in Appendix A.2. |
| Open Source Code | No | Our project page: Lf Void.github.io. This is a project page, not an explicit statement that the code is available or a direct link to a code repository. |
| Open Datasets | Yes | The simulated tasks are developed based on the Robosuite benchmark, while we provide corresponding real-world tasks for each environment. A full description of the environments is provided in Appendix B.1. |
| Dataset Splits | No | The paper mentions creating a 'dataset of 1024 target images for each task' and training a discriminator using positive and negative samples, but it does not specify explicit train/validation/test splits with percentages or counts for the overall models or experiments. |
| Hardware Specification | No | The paper mentions 'simulated tasks' and 'real-robot environments' but does not provide specific hardware details such as GPU models, CPU specifications, or memory used for running the experiments. |
| Software Dependencies | No | The paper mentions using 'Dr Q-v2 [45] for visual RL training' and that simulated tasks are based on the 'Robosuite benchmark [51]', but it does not provide specific version numbers for these or other software components. |
| Experiment Setup | No | The paper states, 'The training details can be found in Appendix B.3.', indicating that detailed experimental setup information, such as hyperparameters, is not in the main text. |