
## HyDiscGAN: A Hybrid Distributed cGAN for Audio-Visual Privacy Preservation in Multimodal Sentiment Analysis
Zhuojia Wu, Qi Zhang, Duoqian Miao, Kun Yi, Wei Fan, Liang Hu
Keywords: Natural Language Processing: NLP: Sentiment analysis, stylistic analysis, and argument mining, Machine Learning: ML: Multi-modal learning, Multidisciplinary Topics and Applications: MTA: Security and privacy
IJCAI/2024/Proceedings/0724 - HyDiscGAN: A Hybrid Distributed cGAN for Audio-Visual Privacy Preservation in Multimodal Sentiment Analysis.pdf

### Implementation
_Given the documentation given by the authors on the method, how much time investment would it be to re-implement the method from scratch?_

[10]

The authors do not share their implementation. Pseudo code is given in the paper and a process schematic is given in figure 2. 

### Data
_Given the data description in the documentation, how much effort take to either: Find the same dataset the authors used, or similar datasets and defend the comparability, or acquire one from scratch?_

[2]

(2/2)

The authors state they use two popular benchmark data sets, cite them, and provide statistics on them in table 1. No direct links provided.

### Configuration 
_Given the (hyper)parameters, including semantic parameters, of the method: How much effort would it take to acquire the algorithm configurations used for their results, and compare against their budgetary constraints?_

[10]

No details on hyperparameters specified.

### Experimental Procedure
_Given the experimental set-up of the work, how difficult is it to set up a new experiment, similar to those presented in the original work, with the same procedure?_

[7]

The authors state in 4.1 that they avreage five random seed runs and the metrics per task, most of which are very standard. No details given regarding training procedures or training testing splits.

### Expertise
_How much effort would it take to acquire the expertise required to reproduce the work independently relying on the available documentation?_

[7]

Requires expertise in GenAI and NLP, significantly more because of the lacking implementation.
