---
title: "GT-Vision-Lab/VQA_LSTM_CNN: papers citing it"
description: "3 papers in the tracked journals link to the GitHub repository GT-Vision-Lab/VQA_LSTM_CNN in their Crossref records, the first in 2018; most of them (1) in 2023."
url: https://scholar4ai.com/code/github-gt-vision-lab-vqa-lstm-cnn
markdown_url: https://scholar4ai.com/code/github-gt-vision-lab-vqa-lstm-cnn.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "3 papers in the tracked journals link to the GitHub repository GT-Vision-Lab/VQA_LSTM_CNN in their Crossref records, the first in 2018; most of them (1) in 2023. (as of 2026-11-03)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-03T14:43:26+09:00
window: 2026-10-05 to 2026-11-03
source: OpenAlex (CC0)
---

# GT-Vision-Lab/VQA_LSTM_CNN: papers linking to it

Research papers in the 480 tracked journals that link to GT-Vision-Lab/VQA_LSTM_CNN (https://github.com/GT-Vision-Lab/VQA_LSTM_CNN), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

- GitHub
- 386 stars
- 131 forks
- Lua
- created 2015
- https://github.com/GT-Vision-Lab/VQA_LSTM_CNN

All repositories: https://scholar4ai.com/code.md

## Key findings

- 3 papers in the tracked journals link to the GitHub repository GT-Vision-Lab/VQA_LSTM_CNN in their Crossref records, the first in 2018; most of them (1) in 2023.
- By category: AI (3); the journals with the most are International Journal of Computer Vision (3).

## By year

*Papers linking to GT-Vision-Lab/VQA_LSTM_CNN by publication year*

| Year | Papers |
|---|---:|
| 2018 | 1 |
| 2019 | 1 |
| 2023 | 1 |

## Journals

*Journals whose papers link to GT-Vision-Lab/VQA_LSTM_CNN most*

| Journal | Papers |
|---|---:|
| [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | 3 |

## Papers

*Papers linking to GT-Vision-Lab/VQA_LSTM_CNN, most cited first*

| Published | Title | Journal | Authors | Citations | Link |
|---|---|---|---|---:|---|
| 2019-10-11 | [Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization](https://doi.org/10.1007/s11263-019-01228-7) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das et al. | 6,898 | cites it |
| 2018-09-11 | [Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering](https://doi.org/10.1007/s11263-018-1116-0) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Yash Goyal, Tejas Khot, Aishwarya Agrawal et al. | 486 | cites it |
| 2023-08-28 | [Correlation Information Bottleneck: Towards Adapting Pretrained Multimodal Models for Robust Visual Question Answering](https://doi.org/10.1007/s11263-023-01858-y) | [International Journal of Computer Vision](https://scholar4ai.com/journals/international-journal-of-computer-vision.md) | Jingjing Jiang, Ziyi Liu, Nanning Zheng | 22 | cites it |

## How this is measured

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

## Cite this page

Scholar4AI. (2026). GT-Vision-Lab/VQA_LSTM_CNN: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-gt-vision-lab-vqa-lstm-cnn

```bibtex
@misc{scholar4ai-code-github-gt-vision-lab-vqa-lstm-cnn,
  author = {{Scholar4AI}},
  title = {GT-Vision-Lab/VQA_LSTM_CNN: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-gt-vision-lab-vqa-lstm-cnn}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).