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.