##ENTRY IN THIS COMPETITION CONSTITUTES YOUR ACCEPTANCE OF THESE OFFICIAL COMPETITION RULES.

**[See Section 3.18 for defined terms](rules#18.-terms)**

*The Competition named below is a skills-based competition to promote and further the field of data science. You must register via the Competition Website to enter. To enter the Competition, you must agree to these Official Competition Rules, which incorporate by reference the provisions and content of the Competition Website and any Specific Competition Rules herein (collectively, the "Rules"). Please read these Rules carefully before entry to ensure you understand and agree. You further agree that Submission in the Competition constitutes agreement to these Rules. You may not submit to the Competition and are not eligible to receive the prizes associated with this Competition unless you agree to these Rules. These Rules form a binding legal agreement between you and the Competition Sponsor with respect to the Competition. Your competition Submissions  must conform to the requirements stated on the Competition Website. Your Submissions will be scored based on the evaluation metric described on the Competition Website. Subject to compliance with the Competition Rules, Prizes, if any, will be awarded to Participants with the best scores, based on the merits of the data science models submitted. See below for the complete Competition Rules.*

**You cannot sign up to Kaggle from multiple accounts and therefore you cannot enter or submit from multiple accounts.**
1. COMPETITION-SPECIFIC TERMS
1. COMPETITION TITLE
Classification of Math Problems By KASUT Academy
2. COMPETITION SPONSOR
KASUT Academy
3. COMPETITION SPONSOR ADDRESS
4700 King Abdullah University of Science and Technology Thuwal 23955-6900. Kingdom of Saudi Arabia.
4. COMPETITION WEBSITE
https://www.kaggle.com/competitions/classification-of-math-problems-by-kasut-academy
5. TOTAL PRIZES AVAILABLE: 10,000 SAR
6. WINNER LICENSE TYPE
Open Source


###2. COMPETITION-SPECIFIC RULES 
In addition to the provisions of the General Competition Rules below, you understand and agree to these Competition-Specific Rules required by the Competition Sponsor:

1. **Open-Source Models Only**  
   You are only allowed to use **open-weight models** in your solution. The use of proprietary, paid, or closed-source models is strictly prohibited. Violation of this rule will result in **disqualification**.

2. **Code Sharing Requirement (Top 5)**  
   To promote transparency and learning, participants who finish in the **Top 5** on the private leaderboard are required to publicly share their **full training and inference code** that can reproduce their final score.  
   - You’ll have **2 days after the competition ends** to submit your reproducible code.  
   - If code is not submitted or the result cannot be reasonably reproduced, we may need to **remove the entry from the final rankings**.
   - Preferably the teams should write a small article or blog explaining the logic behind their model choice and how they got there.

3. **No Duplicate Accounts**  
   The use of **duplicate or multiple accounts** is strictly prohibited. It can be easily discovered by the host. This will be actively monitored and violations will result in **immediate disqualification**.

4. **Prize Eligibility**  
   Prizes will be awarded **only to participants residing in Saudi Arabia**. If you are not a resident of Saudi Arabia, you are welcome to participate for learning and leaderboard placement, but you will not be eligible for monetary prizes.

5. **Manual Annotation of Test Set Is Prohibited**  
   Manually labeling or annotating the test set (e.g., by reading and assigning topics by hand) is strictly **not allowed**. Any indication of manual labeling will result in **disqualification** This also includes closed sourced automatic LLM labeling.

####1. TEAM LIMITS
a. The maximum Team size is five (5).
b. Team mergers are allowed and can be performed by the Team leader. In order to merge, the combined Team must have a total Submission count less than or equal to the maximum allowed as of the Team Merger Deadline. The maximum allowed is the number of Submissions per day multiplied by the number of days the competition has been running.
####2. SUBMISSION LIMITS
a. You may submit a maximum of five (5) Submissions per day.
b. You may select up to two (2) Final Submissions for judging.
####3. COMPETITION TIMELINE
a. Competition Timeline dates (including Entry Deadline, Final Submission Deadline, Start Date, and Team Merger Deadline, as applicable) are reflected on the competition’s Overview > Timeline page.
####4. COMPETITION DATA

a. Data Access and Use.  
You may access and use the Competition Data for non-commercial purposes only, including for participating in the Competition and on Kaggle.com forums, and for academic research and education. The Competition Sponsor reserves the right to disqualify any Participant who uses the Competition Data other than as permitted by the Competition Website and these Rules.
b. Data Security.
1. You agree to use reasonable and suitable measures to prevent persons who have not formally agreed to these Rules from gaining access to the Competition Data. You agree not to transmit, duplicate, publish, redistribute or otherwise provide or make available the Competition Data to any party not participating in the Competition. You agree to notify Kaggle immediately upon learning of any possible unauthorized transmission of or unauthorized access to the Competition Data and agree to work with Kaggle to rectify any unauthorized transmission or access.
####5. WINNER LICENSE 

a. Under Section 2.8 (Winners Obligations) of the General Rules below, you hereby grant and will grant the Competition Sponsor the following license(s) with respect to your Submission if you are a Competition winner:
*Open Source: You hereby license and will license your winning Submission and the source code used to generate the Submission under an Open Source Initiative-approved license (see [www.opensource.org] (http://www.opensource.org)) that in no event limits commercial use of such code or model containing or depending on such code.
b. You may be required by the Sponsor to provide a detailed description of how the winning Submission was generated, to the Competition Sponsor’s specifications, as outlined in Section 2.8, Winner’s Obligations. This may include a detailed description of methodology, where one must be able to reproduce the approach by reading the description, and includes a detailed explanation of the architecture, preprocessing, loss function, training details, hyper-parameters, etc. The description should also include a link to a code repository with complete and detailed instructions so that the results obtained can be reproduced.
####6. EXTERNAL DATA AND TOOLS

a. You may use data other than the Competition Data (“External Data”) to develop and test your Submissions. However, you will ensure the External Data is either publicly available and equally accessible to use by all Participants of the Competition for purposes of the competition at no cost to the other Participants, or satisfies the Reasonableness criteria as outlined in Section 2.6.b below. The ability to use External Data under this Section does not limit your other obligations under these Competition Rules, including but not limited to Section 2.8 (Winners Obligations).
b. The use of external data and models is acceptable unless specifically prohibited by the Host. Because of the potential costs or restrictions (e.g., “geo restrictions”) associated with obtaining rights to use external data or certain software and associated tools, their use must be “reasonably accessible to all” and of “minimal cost”. Also, regardless of the cost challenges as they might affect all Participants during the course of the competition, the costs of potentially procuring a license for software used to generate a Submission, must also be considered. The Host will employ an assessment of whether or not the following criteria can exclude the use of the particular LLM, data set(s), or tool(s):
1. Are Participants being excluded from a competition because of the "excessive" costs for access to certain LLMs, external data, or tools that might be used by other Participants. The Host will assess the excessive cost concern by applying a “Reasonableness” standard (the “Reasonableness Standard”). The Reasonableness Standard will be determined and applied by the Host in light of things like cost thresholds and accessibility.
c. Automated Machine Learning Tools (“AMLT”)
1. Individual Participants and Teams may use automated machine learning tool(s) (“AMLT”) (e.g., Google toML, H2O Driverless AI, etc.) to create a Submission, provided that the Participant or Team ensures that they have an appropriate license to the AMLT such that they are able to comply with the Competition Rules.
####7. ELIGIBILITY

a. Unless otherwise stated in the Competition-Specific Rules above or prohibited by internal policies of the Competition Entities, employees, interns, contractors, officers and directors of Competition Entities may enter and participate in the Competition, but are not eligible to win any Prizes. "Competition Entities" means the Competition Sponsor, Kaggle Inc., and their respective parent companies, subsidiaries and affiliates. If you are such a Participant from a Competition Entity, you are subject to all applicable internal policies of your employer with respect to your participation.
####8. WINNER’S OBLIGATIONS

a. As a condition to being awarded a Prize, a Prize winner must fulfill the following obligations:
1. Deliver to the Competition Sponsor the final model's software code as used to generate the winning Submission and associated documentation. The delivered software code should follow [these documentation guidelines][5], must be capable of generating the winning Submission, and contain a description of resources required to build and/or run the executable code successfully. For avoidance of doubt, delivered software code should include training code, inference code, and a description of the required computational environment. 

a. To the extent that the final model’s software code includes generally commercially available software that is not owned by you, but that can be procured by the Competition Sponsor without undue expense, then instead of delivering the code for that software to the Competition Sponsor, you must identify that software, method for procuring it, and any parameters or other information necessary to replicate the winning Submission; Individual Participants and Teams who create a Submission using an AMLT may win a Prize. However, for clarity, the potential winner’s Submission must still meet the requirements of these Rules, including but not limited to Section 2.5 (Winners License), Section 2.8 (Winners Obligations), and Section 3.14 (Warranty, Indemnity, and Release).”
b. Individual Participants and Teams who create a Submission using an AMLT may win a Prize. However, for clarity, the potential winner’s Submission must still meet the requirements of these Rules,
2. Grant to the Competition Sponsor the license to the winning Submission stated in the Competition Specific Rules above, and represent that you have the unrestricted right to grant that license;
3. Sign and return all Prize acceptance documents as may be required by Competition Sponsor or Kaggle, including without limitation: (a) eligibility certifications; (b) licenses, releases and other agreements required under the Rules; and (c) U.S. tax forms (such as IRS Form W-9 if U.S. resident, IRS Form W-8BEN if foreign resident, or future equivalents).
####9. GOVERNING LAW

a. Unless otherwise provided in the Competition Specific Rules above, all claims arising out of or relating to these Rules will be governed by California law, excluding its conflict of laws rules, and will be litigated exclusively in the Federal or State courts of Santa Clara County, California, USA. The parties consent to personal jurisdiction in those courts. If any provision of these Rules is held to be invalid or unenforceable, all remaining provisions of the Rules will remain in full force and effect.