We invite proposals from practitioners across industry and academia who are interested in the areas of information retrieval, databases, and knowledge management. The best fit proposal should include a well-motivated goal with real world impact, a novel and challenging task, a fair setup with stable evaluation approach, and adequate amount of real-world data for the competition.

• A well-motivated goal: A goal of the proposed competition should be solving a challenging real-world problem at the same time impacting the research and other communities positively. A good competition is where the output of the competition should lead to a greater good of everyone, such proposals are encouraged.
• A challenging, achievable task: The task should require genuinely novel approaches rather than straightforward application of existing methods to a new dataset. Proposals that reframe standard information extraction/search/recommendation tasks without a meaningful new dimension (e.g., a new constraint, new interaction model, new evaluation axis, or new modality) are discouraged. The task should be manageable in approximately 2 months.
• A fair setup: The organizers should guarantee the availability of the data and the confidentiality of the test set. The evaluation metrics should be both meaningful for the application in-hand and statistically sound for the objective comparison. The baseline should be established to show that non-trivial results can be achieved.
• A real-world dataset: A proposal should clearly explain what data will be provided for competition and the source of the data. Also, explain how/why the provided data is sufficient for the competition.
• Accessibility to the broader research community: The task should be approachable for researchers who are familiar with AI/ML but not necessarily with the specific domain. Domain-specific data is welcome, but tasks requiring deep domain expertise to interpret errors (e.g., medical coding, complex legal reasoning) are discouraged; tasks where domain data is used but failure analysis remains tractable for generalists (e.g., summarization of medical records, extraction from contracts) are a better fit.

A proposal should be no more than 4 pages and should cover all the important details such as dates, submission and evaluation of results, etc. and describe the competition rules clearly.

Please provide following details with your proposal:

1. Title: The title of your challenge.
2. Problem Description: Describe the problem clearly in detail. Explain the importance of the problem and its impact. Discuss different scenarios for the problem with its challenges and limitations. Share the simple data samples and explain the data clearly. If the proposed competition includes more than one track, please describe each track clearly and show unique value for each track.
   1. If data is domain specific, explain what materials you will provide to onboard non-domain-experts. Include sample data with annotations explaining what a good vs. bad output looks like to a general audience.
3. Evaluation: Describe how you plan to evaluate the submission. Select the evaluation method which is fair and statistically robust.
4. Suggested Participants: Provide a list of suggested participants in the challenge.
5. Timeline. Dates for expected start of the competition, user registration, team formation, submission, evaluation, and notification.
6. Awards. Specify the type and form of the awards you want to share with the winners.
7. Host information: Names, affiliations, email addresses, and short biographies of the organizers. Please include previous experiences in organizing shared tasks.