📢 We are also co-hosting ImageEval 2026, a shared task at ArabicNLP 2026, co-located with EMNLP.

Tasks & Evaluation

Two tasks with a shared goal: open-ended answers to questions about images, appropriate to the language and culture of the asker.

Task definition

Given an image and a question about its content, a system produces a short, open-ended answer. Answers are free text rather than multiple choice, so they must be semantically correct, grounded in the visual content, and appropriate to the linguistic and cultural context of the question. Many questions draw on local knowledge about food, places, customs, and objects that is not spelled out in the image itself.

The two tasks

Every question in the dataset exists in two forms, audio and text. Both tasks use the same images and the same questions; they differ only in how the question is provided. You may enter either task or both.

Task Input Output
Task 1: Spoken Visual QA Image + spoken question (audio) Open-ended answer (text)
Task 2: Textual Visual QA Image + written question (text) Open-ended answer (text)

Task 1 tests end-to-end understanding when the question arrives as speech. Task 2 removes speech recognition from the equation and isolates multimodal, culturally grounded reasoning.

Language tracks

Each task is offered as a separate track per language, and systems are ranked per track. You can enter a single track, several, or all of them.

  • English
  • Modern Standard Arabic
  • Dialectal Arabic
  • Bangla
  • Hindi
  • Assamese
  • Urdu
  • More planned

Highlighted languages are confirmed for the first data release; the others are planned and will follow in the same format.

Evaluation

Because answers are open-ended, scoring rewards meaning rather than exact wording.

Official ranking

BERTScore F1

Measures semantic similarity to the reference, so answers that mean the same thing score well even when the wording differs.

Auxiliary

BLEU & ROUGE

Lexical-overlap metrics reported for context. Not used for the ranking.

Supplementary

LLM-based analysis

May be reported for submitted systems as additional analysis. Not used for the ranking.

The official evaluation script is released together with the data, so you can reproduce the ranking metric locally before submitting. Submissions run on CodaBench during the evaluation phase; see Participate for the full workflow.

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