• Task: Given a controversial topic, the task is to retrieve images (from web pages) for each stance (pro/con) that show support for that stance.
  • Input: [topics] [data]
  • Submission: [submit]
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This task uses a focused crawl of about 56K images (and associated web pages) as document collection. The crawl is created from several image search queries for each of the 50 topics. The relevance judgments of last year are available for training supervised approaches. The output of last year's approaches can be inspected on Registered teams were invited in 2022 to submit search queries that were then used to extend the crawl. [data]


Like last year, systems are evaluated on 50 topics by the ratio of images among the 20 retrieved images for each topic (10 images for each stance) that are relevant for the respective topic and stance. [topics]


This task uses TIRA for submissions, which allows for both run file upload and Docker image submission. For each topic and stance, include 10 retrieved images. Each team can submit up to 5 different runs.

The submission format adapts the standard TREC format. Each line corresponds to an image retrieved for some topic and stance at a certain rank, making a run file 1000 lines long (50 topics, 2 stances, 10 ranks). Each line contains the following fields, separated by single whitespaces:

  • The topic number (51 to 100).
  • The stance ("PRO" or "CON").
  • The image's ID (corresponds to the name of the image's directory in the collection; always 17 characters long and starts with "I").
  • The rank (1 to 10 in increasing order per topic and stance). Not used in this year's evaluation.
  • A score (integer or floating point; non-increasing per topic and stance). Not used in this year's evaluation.
  • A tag that identifies your group and the method you used to produce the run.
For example:
1 PRO I000330ba4ea0ad13 1 17.89 myGroupMyMethod
1 PRO I0005e6fe00ea17fd 2 16.43 myGroupMyMethod
1 CON I0009d5f038fe6f2e 1 15.89 myGroupMyMethod
1 CON I000f34bd3f8cb030 2 14.43 myGroupMyMethod

TIRA Tutorial and TIRA Baselines

We provide a TIRA tutorial that provides baselines that can be executed in TIRA at

In case of problems or questions concerning TIRA, please use the TIRA forum.


On topicArgumentativeOn stance
Neville Longbottomclip_chatgpt_args.raw0.7850.3380.222
Neville Longbottomclip_chatgpt_args.debater0.6840.3410.216
Hikaru SuluKeywords0.6640.3500.185
Hikaru SuluTopic-title0.7700.3350.179
Neville Longbottombm25_chatgpt_args.raw0.5720.2740.166
Jean-Luc PicardNo stance detection (0)0.5230.2920.162
Neville Longbottombm25_chatgpt_args.diff0.4420.2400.150
Jean-Luc PicardText and image text stance detection (3)0.5020.2720.144
Jean-Luc PicardBM25 Baseline (-1)0.5360.2680.141
Jean-Luc PicardText stance detection (1)0.4980.2620.136
Neville Longbottombm25_chatgpt_args.debater0.4160.2010.128
Jean-Luc PicardImage text stance detection (2)0.3690.1960.098

Related Work

Task Committee