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We are pleased to announce the release of the test topics for the TREC-AToMiC task. These topics have been carefully selected from the AToMiC text collection, and we invite participants to submit their runfiles based on these test topics.

Topic Selection (Task-1)

In order to ensure a diverse range of topics, we employed two primary criteria for topic selection:

  • Unillustrated sections in enwiki: We identified sections within the English Wikipedia (enwiki) that do not have accompanying images but potentially have matching images in other Wikipedia pages from foreign languages.

  • Vital articles at level 3: We referred to Wikipedia:Vital_articles and selected articles classified as level 3 vital articles. These articles serve as quality control monitors for Wikipedia.

Additionally, we considered the following sub-criteria:

  • Article Quality: We sampled 100 topics from C-class articles, 50 topics from B-class articles, and 50 topics from Featured or Good Articles.
  • AToMiC Text Collection Coverage: The coverage of the AToMiC text collection for the test topics is as follows: 180 topics belong to the other set with no sparse labels at all, 19 topics are from the training set, and 1 topic represents the test set. Note that choosing examples from the training set is deliberate as the sparse labels may not represent the entire possibility of images that would be associated with the topic

Topic Selection (Task-2)

For this year’s evaluation, we will be focusing solely on Task-2 (See guidelines for more detailed instructions): No additional annotations are required. The selection of image topics is carried out using our baseline runfiles, namely fusion-all, fusion-ViTs, and fusion-SPLADE-ViTg. From each text topic, we utilize these baseline runfiles to identify the top-20 images. To ensure diversity and avoid duplication, we perform further deduplication on the selected images, resulting in a final set of 200 images.

We believe that this selection process ensures a diverse and representative set of topics for the TREC-AToMiC task. We look forward to receiving your runfiles based on these test topics. Please don’t hesitate to reach out if you have any questions or need further clarification.

Thank you for your participation!

The dataset is available on HuggingFace 🤗: