Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation
Authors: Sang-Woo Lee, Tong Gao, Sohee Yang, Jaejun Yoo, Jung-Woo Ha
ICLR 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate our method on Guess Which, a challenging task-oriented visual dialog problem, where the number of candidate classes is near 10K. Our experimental results and ablation studies show that AQM+ outperforms the state-of-the-art models by a remarkable margin with a reasonable approximation. |
| Researcher Affiliation | Industry | Sang-Woo Lee, Tong Gao, Sohee Yang, Jaejun Yoo, & Jung-Woo Ha Clova AI Research, NAVER Corp. {sang.woo.lee,tong.gao,sh.yang,jaejun.yoo,jungwoo.ha}@navercorp.com |
| Pseudocode | Yes | Algorithm 1 Question Generating Process of AQM+ in Our Guess Which Experiments |
| Open Source Code | Yes | Our code is modified from the code of Modhe et al. (2018), and we make our code publically available2. https://github.com/naver/aqm-plus |
| Open Datasets | Yes | Guess Which uses Visual Dialog dataset (Das et al., 2017a) which includes human dialogs on MSCOCO images (Lin et al., 2014) as well as the captions that are generated. |
| Dataset Splits | No | The paper mentions 'training data' and 'test images' but does not explicitly provide details about training/validation/test splits, such as percentages or sample counts for a distinct validation set. |
| Hardware Specification | Yes | We used Tesla P40 for our experiments. |
| Software Dependencies | No | The paper mentions the use of 'NAVER Smart Machine Learening (NSML) platform' and that 'Our code is modified from the code of Modhe et al. (2018)', which implies PyTorch use. However, it does not specify exact version numbers for any software dependencies like Python or PyTorch. |
| Experiment Setup | Yes | We set |Ct,topk| = |Qt,gen| = |At,topk(qt)| = 20. The epoch for SL-Q is 60. The epoch for RL-Q and RL-QA is 20 for non-delta, and 15 for delta, respectively. |