{ "fetched_at": "2026-10-25T06:32:18Z", "source_url": "https://www.kaggle.com/competitions/agent-society-challenge/data", "pages": [ { "name": "data-description", "content": "## Dataset Overview and Download Links\n\n| | len(review) | len(business) | len(user) | link |\n| ------------------------------ | ------------- | ------------- | ----------- | ------------------------------------------------------------ |\n| **Yelp** | **-** | **-** | **-** | [download](https://www.yelp.com/dataset) |\n| - | - | - | - | |\n| Industrial_and_Scientific | 412.9K | 25.8K | 51.0K | [review](https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Industrial_and_Scientific.jsonl.gz), [meta](https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Industrial_and_Scientific.jsonl.gz), [rating_only](https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/benchmark/5core/rating_only/Industrial_and_Scientific.csv.gz) |\n| Musical_Instruments | 511.8K | 24.6K | 57.4K | [review](https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Musical_Instruments.jsonl.gz), [meta](https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Musical_Instruments.jsonl.gz), [rating_only](https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/benchmark/5core/rating_only/Musical_Instruments.csv.gz) |\n| Video_Games | 814.6K | 25.6K | 94.8K | [review](https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Video_Games.jsonl.gz), [meta](https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Video_Games.jsonl.gz), [rating_only](https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/benchmark/5core/rating_only/Video_Games.csv.gz) |\n| **Amazon** | **1,739,300** | **76,000** | | |\n| - | - | - | - | |\n| Goodreads
_Children | 734,640 | 124,082 | | [review](https://datarepo.eng.ucsd.edu/mcauley_group/gdrive/goodreads/byGenre/goodreads_reviews_children.json.gz), [meta](https://datarepo.eng.ucsd.edu/mcauley_group/gdrive/goodreads/byGenre/goodreads_books_children.json.gz) |\n| Goodreads
_Comics&Graphic | 542,338 | 89,411 | | [review](https://datarepo.eng.ucsd.edu/mcauley_group/gdrive/goodreads/byGenre/goodreads_reviews_comics_graphic.json.gz), [meta](https://datarepo.eng.ucsd.edu/mcauley_group/gdrive/goodreads/byGenre/goodreads_books_comics_graphic.json.gz) |\n| Goodreads
_Poetry | 154,555 | 36,514 | | [review](https://datarepo.eng.ucsd.edu/mcauley_group/gdrive/goodreads/byGenre/goodreads_reviews_poetry.json.gz), [meta](https://datarepo.eng.ucsd.edu/mcauley_group/gdrive/goodreads/byGenre/goodreads_books_poetry.json.gz) |\n| **Goodreads** | **1,431,533** | **250,007** | | |", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Timeline", "content": "The schedule for the competition is as follows：\n1. Start of the Competition （Registration）： Dec 10th, 2024-Jun 18th, 2025.\n2. Official Competition: Dec 18th, 2024 -Jan 25th, 2025.\n\t* Development Phase: Dec 30th, 2024 - Jan 23th, 2025.\n\t* Final Phase: Jun 24th, 2025 - Jun 30th, 2025.\n3. Winner Notification and Per Invitation: Feb 3rd, 2025.\n4. Camera-ready Submission: Feb 17th, 2025.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Description", "content": "In this challenge, we are inspired by the concept of modular agent design and adopt an actionable modular design space with four key modules: **Planning**, **Reasoning**, **Tool use**, and **Memory**. These modules are orchestrated in a designed workflow: upon receiving a task query, the agent begins by decomposing it into sub-tasks through the Planning module. The Reasoning module then processes each sub-task, and when necessary, activates the Tool use module to select external tools for problem-solving. Additionally, the Memory module supports the reasoning process by accessing past observations and experiences, ensuring the agent continuously refines its actions based on feedback from the environment. The participants are tasked to construct effective agent modules that work together to enhance the agent’s ability to process information, make decisions, and interact with dynamic environments in IR tasks. \n\n### Modular Agent Design Space\nWithin this framework, participants can explore LLM agent design with three levels:\n1. Module Recombination: Designing novel agent by recombining the classic modules (reasoning, planning, tool use, and memory).\n2. Module Design: Developing or modifying modules to implement new functionalities while ensuring compatibility with the standardized framework.\n3. Workflow Construction: Designing the overall structure and interaction flow of the agentic system to effectively integrate the modules and achieve the desired outcomes. \n\nWith the standard IO interfaces of these modules, participants can easily integrate different classic modules, facilitating the discovery of novel agent architectures through module recombination. This approach allows for the reuse of prior successful designs, significantly lowering the barrier for participants who may not have deep knowledge of LLM agents.Besides, this challenge also supports more in-depth agent design, allowing participants to reprogram each module and even rewrite the entire workflow. One key motivation of our challenge design is to ensure the discovered modules, with standard IO interfaces, can be reused in future research and applications, benefiting the LLM agent and web community. In the final phase, submissions will be required to adhere to a modular design.\n\nSpecificly, this challenge consists of two tracks: **User Behavior Modeling Track**, which focuses on simulating user behavior in specific scenarios by leveraging their historical actions and accessible environmental data.In this track, we utilized datasets from **Yelp**, **Amazon**, and **Goodreads** to build a text simulation environment that allows participants to come up with new solutions to these problems in an interactive environment in agentic mode, ensuring a comprehensive and diverse evaluation of user behaviors; **Recommendation Track**, which emphasizes building personalized recommendation assistants that provide users with appropriate suggestions tailored to particular contexts. These tracks focus on key problems in information retrieval (IR), like understanding user intent, context-aware decision-making, and adaptive response generation. They aim to advance research in behavioral modeling and recommendation systems, driving innovation in how information is retrieved and applied to support users in various situations.In the User Behavior Modeling Track, participants must design agents to simulate user reviews and star ratings. In the Recommendation Track, participants are tasked with using agents to generate rankings based on the current user's preferences. \n\nHere is the **Resource & Code base**: [This Link](https://github.com/tsinghua-fib-lab/WebSocietySimulator).", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "rules", "content": "# Terms and Conditions\n\n## Competition Format\n\n### Rules\n1. Participants should devise LLM agentic workflows within the predefined modular design space, including:\n - **Module Recombination**\n - **Module Design**\n - **Workflow Construction**\n \nUniform LLMs will be provided for evaluating the submitted workflows. The use of external models, training of external models, or utilization of external tools is strictly prohibited.\n\n2. During the evaluation of submitted agents, any direct interaction with the original dataset is strictly prohibited. All data access must go through the interaction tools provided by the competition organizers.\n\n3. Participants are permitted to utilize inference services from any platform during the **Development Phase**. However, during the **Evaluation Phase**, all submitted agents will be evaluated exclusively on the Infinigence AI Tech platform.\n\n4. Submission limits:\n - **Development Phase**: Each participant may submit up to **2 times per day**, with a maximum of **100 submissions** allowed throughout the phase.\n - **Evaluation Phase**: Each participant is allowed a maximum of **2 submissions** within the designated time frame.\n\n5. Evaluation will be **time- and token-limited**.\n\n6. Any form of dishonest conduct is strictly prohibited and will result in **immediate disqualification** if detected.\n\n---\n\n### Schedule\n- **October 2024**: Competition organization building, competition planning, and proposal writing.\n- **November 2024**: Preparation of competition materials and promotion of the competition.\n- **December 2024**: Acceptance of participant registrations.\n- **Official Competition**:\n - Participants submit solutions, and organizers evaluate and maintain a public leaderboard.\n- **February 2025**: Notification of winners, invitation of winners to write papers, and preparation of the competition presentation.\n\n---\n\n### Fairness Mechanisms\n1. **Public Leaderboard**: The organizers will provide a public leaderboard for all participants to monitor and review performance.\n2. **Rigorous Review**: Submissions will undergo a thorough review to ensure compliance with competition rules and the integrity of results.\n3. **Equal Access to Resources**: The organizers will ensure all participants have access to sufficient and fair computational resources.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "abstract", "content": "The **AgentSociety Challenge** is an innovative competition designed to explore the potential of large language model (LLM) agents in modeling online social interaction and enhancing information retrieval systems. **The competition organizers will select the winners and recommend participants to submit their solutions as research papers for inclusion in the WWW’25 companion proceedings.** Authors of accepted papers will have the opportunity to present their work at the conference which is held in Sydney. [WWW Accepted-Competitions](https://www2025.thewebconf.org/accepted-competitions ).\n\n### About Token Support \nTo support participants, we will provide API-key access during the development phase. This will be offered through InfinigenceAI, with the following specifications: RPM=100, TPM=60000, RPD=10000,and the ability to call models such as Qwen-72b-instruct. If you wish to use the API, please send your identification documents via email. Required documents include your full name, organization, proof of participation in this competition, track of participation and any other relevant identification details. Once your verification is completed, we will send you the API key. Please note that the number of API keys is **limited**.\n\n## Award \nTo encourage and reward excellence, the competition will offer prizes for first, second, and third place **FOR EACH TRACK**. The first place team will receive 3,000 USD, the second place team will receive 1,000 USD, and the third place team will receive 500 USD. (all pre-tax)", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "User Behavior Modeling Track", "content": "### Introduction\n\nIn this track, participants will use a classic open-source dataset to simulate social interactions and information access behaviors on social media. This is crucial for designing effective information retrieval algorithms for web applications. Using LLM-based agents, participants will combine historical user behavior records and interact with the environment to model how users might review businesses and engage with reviews. The track focuses on **User Preference Simulation**: Participants should design LLM agents that can understand user preferences and behavior patterns to model user preferences. The agent may integrate user characteristics, business attributes, and other users' reviews to form a comprehensive judgment. Each review must include two components: a star rating (a numerical score reflecting the user's opinion) and review text (detailed commentary providing specific feedback). This track explores the potential and scalability of LLM agents in simulating human behavior, offering insights into their applications in behavioral modeling.\n\n### Evaluation\nIn the User Behavior Modeling Track, participants are expected to use LLM agents to model user interactions with recommended items (e.g., businesses on Yelp), including star ratings and review texts. The evaluation for this track will use quantitative metrics to assess the accuracy of the models in simulating user behavior. Specifically, the predicted star ratings are compared with the ground truth using Mean Absolute Error (MAE) after normalizing the values to the range [0,1]. The MAE is calculated as: $MAE = \\frac{1}{N} \\sum_{i=1}^{N} |\\hat{s_{ni}} - s_{ni}|$ , where $N$ is the total number of reviews, and $\\hat{s_{ni}}$ and$s_{ni}$ are the $i$-th normalized predicted star and normalized ground truth, respectively. For the generated review texts, semantic similarity will be evaluated across predefined sentiment dimensions, such as emotional tone, sentiment attitude, and topic relevance. For emotional tone and sentiment attitude, we first calculate the values using predefined models, normalize them to the range [0,1], and compute the MAE. For topic relevance, we calculate the cosine distance between text embeddings, defined as: $d = 1 - \\frac{u \\cdot v}{\\|u\\|_2 \\cdot \\|v\\|_2}$. Finally, after obtaining the individual results, the final error score will be a weighted sum of these metrics.\n\nCheckout [User Behavior Modeling Evaluation](https://github.com/tsinghua-fib-lab/WebSocietySimulator/blob/main/websocietysimulator/tools/evaluation_tool.py) for more calculation details.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "foundational-rules", "content": "The following Kaggle Competition Foundational Rules (“ Foundational Rules ”) apply to every competition regardless of whether the Sponsor creates competition-specific rules. Any competition-specific rules provided by the Sponsor are in addition to these rules, and in the case of any conflict or inconsistency, these Foundational Rules control and nullify contrary competition-specific rules.\n###GENERAL COMPETITION RULES - BINDING AGREEMENT\n####1. ELIGIBILITY\na. To be eligible to enter the Competition, you must be:\n1. a registered account holder at Kaggle.com; \n2. the older of 18 years old or the age of majority in your jurisdiction of residence (unless otherwise agreed to by Competition Sponsor and appropriate parental/guardian consents have been obtained by Competition Sponsor); \n3. not a resident of Crimea, so-called Donetsk People's Republic (DNR) or Luhansk People's Republic (LNR), Cuba, Iran, Syria, or North Korea; and\n4. not a person or representative of an entity under U.S. export controls or sanctions (see: [https://www.treasury.gov/resourcecenter/sanctions/Programs/Pages/Programs.aspx][1]).\n\nb. Competitions are open to residents of the United States and worldwide, except that if you are a resident of Crimea, so-called Donetsk People's Republic (DNR) or Luhansk People's Republic (LNR), Cuba, Iran, Syria, North Korea, or are subject to U.S. export controls or sanctions, you may not enter the Competition. Other local rules and regulations may apply to you, so please check your local laws to ensure that you are eligible to participate in skills-based competitions. The Competition Host reserves the right to forego or award alternative Prizes where needed to comply with local laws. If a winner is located in a country where prizes cannot be awarded, then they are not eligible to receive a prize.\n\nc. If you are entering as a representative of a company, educational institution or other legal entity, or on behalf of your employer, these rules are binding on you, individually, and the entity you represent or where you are an employee. If you are acting within the scope of your employment, or as an agent of another party, you warrant that such party or your employer has full knowledge of your actions and has consented thereto, including your potential receipt of a Prize. You further warrant that your actions do not violate your employer's or entity's policies and procedures. \n\nd. The Competition Sponsor reserves the right to verify eligibility and to adjudicate on any dispute at any time. If you provide any false information relating to the Competition concerning your identity, residency, mailing address, telephone number, email address, ownership of right, or information required for entering the Competition, you may be immediately disqualified from the Competition.\n\n####2. SPONSOR AND HOSTING PLATFORM\n\na. The Competition is sponsored by Competition Sponsor named above. The Competition is hosted on behalf of Competition Sponsor by Kaggle Inc. (\"Kaggle\"). Kaggle is an independent contractor of Competition Sponsor, and is not a party to this or any agreement between you and Competition Sponsor. You understand that Kaggle has no responsibility with respect to selecting the potential Competition winner(s) or awarding any Prizes. Kaggle will perform certain administrative functions relating to hosting the Competition, and you agree to abide by the provisions relating to Kaggle under these Rules. As a Kaggle.com account holder and user of the Kaggle competition platform, remember you have accepted and are subject to the Kaggle Terms of Service at [www.kaggle.com/terms][2] in addition to these Rules.\n\n####3. COMPETITION PERIOD\na. For the purposes of Prizes, the Competition will run from the Start Date and time to the Final Submission Deadline (such duration the “Competition Period”). The Competition Timeline is subject to change, and Competition Sponsor may introduce additional hurdle deadlines during the Competition Period. Any updated or additional deadlines will be publicized on the Competition Website. It is your responsibility to check the Competition Website regularly to stay informed of any deadline changes. YOU ARE RESPONSIBLE FOR DETERMINING THE CORRESPONDING TIME ZONE IN YOUR LOCATION.\n\n####4. COMPETITION ENTRY\na. NO PURCHASE NECESSARY TO ENTER OR WIN. To enter the Competition, you must register on the Competition Website prior to the Entry Deadline, and follow the instructions for developing and entering your Submission through the Competition Website. Your Submissions must be made in the manner and format, and in compliance with all other requirements, stated on the Competition Website (the \"Requirements\"). Submissions must be received before any Submission deadlines stated on the Competition Website. Submissions not received by the stated deadlines will not be eligible to receive a Prize.\nb. Submissions may not use or incorporate information from hand labeling or human prediction of the validation dataset or test data records.\nc. If the Competition is a multi-stage competition with temporally separate training and/or test data, one or more valid Submissions may be required during each Competition stage in the manner described on the Competition Website in order for the Submissions to be Prize eligible.\nd. Submissions are void if they are in whole or part illegible, incomplete, damaged, altered, counterfeit, obtained through fraud, or late. Competition Sponsor reserves the right to disqualify any entrant who does not follow these Rules, including making a Submission that does not meet the Requirements. \n\n####5. INDIVIDUALS AND TEAMS\na. Individual Account. You may make Submissions only under one, unique Kaggle.com account. You will be disqualified if you make Submissions through more than one Kaggle account, or attempt to falsify an account to act as your proxy. You may submit up to the maximum number of Submissions per day as specified on the Competition Website. \nb. Teams. If permitted under the Competition Website guidelines, multiple individuals may collaborate as a Team; however, you may join or form only one Team. Each Team member must be a single individual with a separate Kaggle account. You must register individually for the Competition before joining a Team. You must confirm your Team membership to make it official by responding to the Team notification message sent to your Kaggle account. Team membership may not exceed the Maximum Team Size stated on the Competition Website.\nc. Team Merger. Teams may request to merge via the Competition Website. Team mergers may be allowed provided that: (i) the combined Team does not exceed the Maximum Team Size; (ii) the number of Submissions made by the merging Teams does not exceed the number of Submissions permissible for one Team at the date of the merger request; (iii) the merger is completed before the earlier of: any merger deadline or the Competition deadline; and (iv) the proposed combined Team otherwise meets all the requirements of these Rules. \nd. Private Sharing. No private sharing outside of Teams. Privately sharing code or data outside of Teams is not permitted. It's okay to share code if made available to all Participants on the forums.\n\n####6. SUBMISSION CODE REQUIREMENTS\na. Private Code Sharing. Unless otherwise specifically permitted under the Competition Website or Competition Specific Rules above, during the Competition Period, you are not allowed to privately share source or executable code developed in connection with or based upon the Competition Data or other source or executable code relevant to the Competition (“Competition Code”). This prohibition includes sharing Competition Code between separate Teams, unless a Team merger occurs. Any such sharing of Competition Code is a breach of these Competition Rules and may result in disqualification.\nb. Public Code Sharing. You are permitted to publicly share Competition Code, provided that such public sharing does not violate the intellectual property rights of any third party. If you do choose to share Competition Code or other such code, you are required to share it on Kaggle.com on the discussion forum or notebooks associated specifically with the Competition for the benefit of all competitors. By so sharing, you are deemed to have licensed the shared code under an Open Source Initiative-approved license (see [www.opensource.org][3]) that in no event limits commercial use of such Competition Code or model containing or depending on such Competition Code.\nc. Use of Open Source. Unless otherwise stated in the Specific Competition Rules above, if open source code is used in the model to generate the Submission, then you must only use open source code licensed under an Open Source Initiative-approved license (see [www.opensource.org][4]) that in no event limits commercial use of such code or model containing or depending on such code.\n\n####7. DETERMINING WINNERS\na. Each Submission will be scored and ranked by the evaluation metric stated on the Competition Website. During the Competition Period, the current ranking will be visible on the Competition Website's Public Leaderboard. The potential winner(s) are determined solely by the leaderboard ranking on the Private Leaderboard, subject to compliance with these Rules. The Public Leaderboard will be based on the public test set and the Private Leaderboard will be based on the private test set.\nb. In the event of a tie, the Submission that was entered first to the Competition will be the winner. In the event a potential winner is disqualified for any reason, the Submission that received the next highest score rank will be chosen as the potential winner.\n\n####8. NOTIFICATION OF WINNERS & DISQUALIFICATION\na. The potential winner(s) will be notified by email. \nb. If a potential winner (i) does not respond to the notification attempt within one (1) week from the first notification attempt or (ii) notifies Kaggle within one week after the Final Submission Deadline that the potential winner does not want to be nominated as a winner or does not want to receive a Prize, then, in each case (i) and (ii) such potential winner will not receive any Prize, and an alternate potential winner will be selected from among all eligible entries received based on the Competition’s judging criteria.\nc. In case (i) and (ii) above Kaggle may disqualify the Participant. However, in case (ii) above, if requested by Kaggle, such potential winner may provide code and documentation to verify the Participant’s compliance with these Rules. If the potential winner provides code and documentation to the satisfaction of Kaggle, the Participant will not be disqualified pursuant to this paragraph.\nd. Competition Sponsor reserves the right to disqualify any Participant from the Competition if the Competition Sponsor reasonably believes that the Participant has attempted to undermine the legitimate operation of the Competition by cheating, deception, or other unfair playing practices or abuses, threatens or harasses any other Participants, Competition Sponsor or Kaggle.\ne. A disqualified Participant may be removed from the Competition leaderboard, at Kaggle's sole discretion. If a Participant is removed from the Competition Leaderboard, additional winning features associated with the Kaggle competition platform, for example Kaggle points or medals, may also not be awarded.\nf. The final leaderboard list will be publicly displayed at Kaggle.com. Determinations of Competition Sponsor are final and binding.\n\n####9. PRIZES\na. Prize(s) are as described on the Competition Website and are only available for winning during the time period described on the Competition Website. The odds of winning any Prize depends on the number of eligible Submissions received during the Competition Period and the skill of the Participants. \nb. All Prizes are subject to Competition Sponsor's review and verification of the Participant’s eligibility and compliance with these Rules, and the compliance of the winning Submissions with the Submissions Requirements. In the event that the Submission demonstrates non-compliance with these Competition Rules, Competition Sponsor may at its discretion take either of the following actions: (i) disqualify the Submission(s); or (ii) require the potential winner to remediate within one week after notice all issues identified in the Submission(s) (including, without limitation, the resolution of license conflicts, the fulfillment of all obligations required by software licenses, and the removal of any software that violates the software restrictions).\nc. A potential winner may decline to be nominated as a Competition winner in accordance with Section 3.8.\nd. Potential winners must return all required Prize acceptance documents within two (2) weeks following notification of such required documents, or such potential winner will be deemed to have forfeited the prize and another potential winner will be selected. Prize(s) will be awarded within approximately thirty (30) days after receipt by Competition Sponsor or Kaggle of the required Prize acceptance documents. Transfer or assignment of a Prize is not allowed. \ne. You are not eligible to receive any Prize if you do not meet the Eligibility requirements in Section 2.7 and Section 3.1 above.\nf. If a Team wins a monetary Prize, the Prize money will be allocated in even shares between the eligible Team members, unless the Team unanimously opts for a different Prize split and notifies Kaggle before Prizes are issued.\n\n####10. TAXES\na. ALL TAXES IMPOSED ON PRIZES ARE THE SOLE RESPONSIBILITY OF THE WINNERS. Payments to potential winners are subject to the express requirement that they submit all documentation requested by Competition Sponsor or Kaggle for compliance with applicable state, federal, local and foreign (including provincial) tax reporting and withholding requirements. Prizes will be net of any taxes that Competition Sponsor is required by law to withhold. If a potential winner fails to provide any required documentation or comply with applicable laws, the Prize may be forfeited and Competition Sponsor may select an alternative potential winner. Any winners who are U.S. residents will receive an IRS Form-1099 in the amount of their Prize.\n\n####11. GENERAL CONDITIONS\na. All federal, state, provincial and local laws and regulations apply.\n\n####12. PUBLICITY\na. You agree that Competition Sponsor, Kaggle and its affiliates may use your name and likeness for advertising and promotional purposes without additional compensation, unless prohibited by law.\n\n####13. PRIVACY\na. You acknowledge and agree that Competition Sponsor and Kaggle may collect, store, share and otherwise use personally identifiable information provided by you during the Kaggle account registration process and the Competition, including but not limited to, name, mailing address, phone number, and email address (“Personal Information”). Kaggle acts as an independent controller with regard to its collection, storage, sharing, and other use of this Personal Information, and will use this Personal Information in accordance with its Privacy Policy <[www.kaggle.com/privacy][6]>, including for administering the Competition. As a Kaggle.com account holder, you have the right to request access to, review, rectification, portability or deletion of any personal data held by Kaggle about you by logging into your account and/or contacting Kaggle Support at <[www.kaggle.com/contact][7]>.\nb. As part of Competition Sponsor performing this contract between you and the Competition Sponsor, Kaggle will transfer your Personal Information to Competition Sponsor, which acts as an independent controller with regard to this Personal Information. As a controller of such Personal Information, Competition Sponsor agrees to comply with all U.S. and foreign data protection obligations with regard to your Personal Information. Kaggle will transfer your Personal Information to Competition Sponsor in the country specified in the Competition Sponsor Address listed above, which may be a country outside the country of your residence. Such country may not have privacy laws and regulations similar to those of the country of your residence.\n\n####14. WARRANTY, INDEMNITY AND RELEASE \na. You warrant that your Submission is your own original work and, as such, you are the sole and exclusive owner and rights holder of the Submission, and you have the right to make the Submission and grant all required licenses. You agree not to make any Submission that: (i) infringes any third party proprietary rights, intellectual property rights, industrial property rights, personal or moral rights or any other rights, including without limitation, copyright, trademark, patent, trade secret, privacy, publicity or confidentiality obligations, or defames any person; or (ii) otherwise violates any applicable U.S. or foreign state or federal law.\nb. To the maximum extent permitted by law, you indemnify and agree to keep indemnified Competition Entities at all times from and against any liability, claims, demands, losses, damages, costs and expenses resulting from any of your acts, defaults or omissions and/or a breach of any warranty set forth herein. To the maximum extent permitted by law, you agree to defend, indemnify and hold harmless the Competition Entities from and against any and all claims, actions, suits or proceedings, as well as any and all losses, liabilities, damages, costs and expenses (including reasonable attorneys fees) arising out of or accruing from: (a) your Submission or other material uploaded or otherwise provided by you that infringes any third party proprietary rights, intellectual property rights, industrial property rights, personal or moral rights or any other rights, including without limitation, copyright, trademark, patent, trade secret, privacy, publicity or confidentiality obligations, or defames any person; (b) any misrepresentation made by you in connection with the Competition; (c) any non-compliance by you with these Rules or any applicable U.S. or foreign state or federal law; (d) claims brought by persons or entities other than the parties to these Rules arising from or related to your involvement with the Competition; and (e) your acceptance, possession, misuse or use of any Prize, or your participation in the Competition and any Competition-related activity.\nc. You hereby release Competition Entities from any liability associated with: (a) any malfunction or other problem with the Competition Website; (b) any error in the collection, processing, or retention of any Submission; or (c) any typographical or other error in the printing, offering or announcement of any Prize or winners.\n\n####15. INTERNET\na. Competition Entities are not responsible for any malfunction of the Competition Website or any late, lost, damaged, misdirected, incomplete, illegible, undeliverable, or destroyed Submissions or entry materials due to system errors, failed, incomplete or garbled computer or other telecommunication transmission malfunctions, hardware or software failures of any kind, lost or unavailable network connections, typographical or system/human errors and failures, technical malfunction(s) of any telephone network or lines, cable connections, satellite transmissions, servers or providers, or computer equipment, traffic congestion on the Internet or at the Competition Website, or any combination thereof, which may limit a Participant’s ability to participate.\n\n####16. RIGHT TO CANCEL, MODIFY OR DISQUALIFY\na. If for any reason the Competition is not capable of running as planned, including infection by computer virus, bugs, tampering, unauthorized intervention, fraud, technical failures, or any other causes which corrupt or affect the administration, security, fairness, integrity, or proper conduct of the Competition, Competition Sponsor reserves the right to cancel, terminate, modify or suspend the Competition. Competition Sponsor further reserves the right to disqualify any Participant who tampers with the submission process or any other part of the Competition or Competition Website. Any attempt by a Participant to deliberately damage any website, including the Competition Website, or undermine the legitimate operation of the Competition is a violation of criminal and civil laws. Should such an attempt be made, Competition Sponsor and Kaggle each reserves the right to seek damages from any such Participant to the fullest extent of the applicable law.\n\n####17. NOT AN OFFER OR CONTRACT OF EMPLOYMENT\na. Under no circumstances will the entry of a Submission, the awarding of a Prize, or anything in these Rules be construed as an offer or contract of employment with Competition Sponsor or any of the Competition Entities. You acknowledge that you have submitted your Submission voluntarily and not in confidence or in trust. You acknowledge that no confidential, fiduciary, agency, employment or other similar relationship is created between you and Competition Sponsor or any of the Competition Entities by your acceptance of these Rules or your entry of your Submission.\n\n####18. DEFINITIONS\na. \"Competition Data\" are the data or datasets available from the Competition Website for the purpose of use in the Competition, including any prototype or executable code provided on the Competition Website. The Competition Data will contain private and public test sets. Which data belongs to which set will not be made available to Participants. \nb. An “Entry” is when a Participant has joined, signed up, or accepted the rules of a competition. Entry is required to make a Submission to a competition.\nc. A “Final Submission” is the Submission selected by the user, or automatically selected by Kaggle in the event not selected by the user, that is/are used for final placement on the competition leaderboard.\nd. A “Participant” or “Participant User” is an individual who participates in a competition by entering the competition and making a Submission.\ne. The “Private Leaderboard” is a ranked display of Participants’ Submission scores against the private test set. The Private Leaderboard determines the final standing in the competition.\nf. The “Public Leaderboard” is a ranked display of Participants’ Submission scores against a representative sample of the test data. This leaderboard is visible throughout the competition.\ng. A “Sponsor” is responsible for hosting the competition, which includes but is not limited to providing the data for the competition, determining winners, and enforcing competition rules.\nh. A “Submission” is anything provided by the Participant to the Sponsor to be evaluated for competition purposes and determine leaderboard position. A Submission may be made as a model, notebook, prediction file, or other format as determined by the Sponsor.\ni. A “Team” is one or more Participants participating together in a Kaggle competition, by officially merging together as a Team within the competition platform.\n\n [1]: https://www.treasury.gov/resource-center/sanctions/Programs/Pages/Programs.aspx\n [2]: http://www.kaggle.com/terms\n [3]: http://www.opensource.org\n [4]: http://www.opensource.org\n [5]: https://www.kaggle.com/WinningModelDocumentationGuidelines\n [6]: http://www.kaggle.com/privacy\n [7]: http://www.kaggle.com/contact\n", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Recommendation Track", "content": "### Introduction\nIn this track, participants will develop an LLM agent that acts as a recommendation assistant. Participants are expected to design recommendation agents capable of handling tasks across diverse scenarios. Each task involves a specific user and a list of item candidates. Participants will need to extract the user's preferences and item information from datasets to generate personalized recommendations. This track explores the potential of LLM agents in recommendation tasks, offering new perspectives and application scenarios for advancing next-generation information retrieval and recommendation systems.\n\n### Evaluation\nIn the Recommendation Track, participants are tasked with designing a recommendation agent that ranks the most likely item a user would select from a list of candidates. The ground truth for each task is generated using a predefined LLM agent that simulates user choices from a list of items based on the provided context and task query. The evaluation will measure how accurately the designed LLM agents rank the ground truth items. For each task, the model should rank a list of 20 candidate items, which will be then evaluated using the Top-N Hit Rate (with $N=1,3,5$).\n\nCheckout [Recommendation Evaluation](https://github.com/tsinghua-fib-lab/WebSocietySimulator/blob/main/websocietysimulator/tools/evaluation_tool.py) for more calculation details.", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Submission Guidance", "content": "**Coming soon**", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false }, { "name": "Prizes", "content": "To encourage and reward excellence, the competition will offer prizes for first, second, and third place **FOR EACH TRACK**. The first place team will receive 3,000 USD, the second place team will receive 1,000 USD, and the third place team will receive 500 USD. (all pre-tax)\n\nTotal Prizes Available: [6]\n- **1st Place** - [3000 USD]\n- **2nd Place** - [1000 USD]\n- **3rd Place** - [500 USD]", "isPublished": false, "hasIsPublished": false, "postTitle": "", "hasPostTitle": false, "mimeType": "", "hasMimeType": false } ] }