---
license: mit
tags:
- research-notes
- image-captioning
- research
---

# Image Captioning: reading plan

## Overview

This repository contains a working research note about **Image Captioning**. It organizes motivation, related work, a falsifiable hypothesis, and an evaluation plan. It is not presented as a completed paper or a release of trained models.

## Changelog

* 2026-10-07 — initial upload
* 2026-10-21 — config and docs sync

## Scope and limitations

Exploratory by design: no benchmark claims, no completed ablations, no released code, no trained checkpoint. The references are a starting point for verification, not evidence that the study has run.

## Roadmap

Next steps, in no particular order: a cleaner entry point, input-shape docs, and a small evaluation script if time permits.

## Related work

A reading list around Image Captioning is being assembled. Entries will be added as the note matures; suggestions via repository discussions are welcome.

## Open questions

* which baselines are actually comparable under matched capacity?
* what is the minimum data exposure for a meaningful signal?
* which confounders would invalidate a naive comparison?

## What is covered

* the scope of the research question and likely confounders
* a proposed comparison with matched baselines
* concrete evaluation context such as MS COCO Captions, NoCaps, and TextCaps
* reproducibility checks, failure modes, and open questions
* topic-relevant references

## Files

* `summary.md` — primary artifact
* `README.md` — this documentation
* `config.json` — architecture configuration
* `training_args.json` — default experiment settings
* `model.safetensors` — initialization checkpoint

## License

Released under **mit**. Review the source-data terms separately when this repository is used with external datasets.