📹 Office Hour #2 Recording

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📹 Office Hour #2 Recording

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📹 Office Hour #2 Recording

Hello all,

Thank you to everyone who joined the Office Hour for the Multi-Task Online Shopping Challenge for LLMs. If you missed the live session check out the recording here .

Recording Available: Watch the session by watching the recording here .

This session featured discussions with our expert, Yilun Jin, covering the info on phase 2 and updates of the challenge, along with a live Q&A.

Feel free to share your thoughts or questions in the comments!

Warm regards,
Team AIcrowd

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💻 Office Hour: May 1, 2024, Wednesday 10AM CST

Hello all,

We invite you to join the next Office Hour for the Amazon KDD Cup 2024. This session provides an excellent opportunity to engage directly with the organizers, explore the intricacies of the challenge, and get your questions answered.

May 1, 2024, Wednesday 4AM CET/10AM CST
Join the Office Hour on Zoom

For those unable to attend, we will provide a recording of the session. Feel free to post your questions here beforehand, and we will address them during the office hour.

Office Hour Highlights:

• Direct engagement with the organizer
• Live Q&A session
• Opportunity to share your feedback

Meet the Speaker:

Yilun Jin: PhD student at the Hong Kong University of Science and Technology and former intern at the Amazon Rufus team. Yilun is the main curator of the ShopBench dataset and has conducted extensive experiments on it.

If you can’t attend, leave your questions in the comments, and the organizers will address them during the session.

Mark your calendars, prepare your questions, and join us live for the Office Hour.

Looking forward to seeing you there!
Team Amazon KDD Cup 2024

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📹 Office Hour #1 Recording

Hello all,

Thank you to everyone who joined the Office Hour for the Multi-Task Online Shopping Challenge for LLMs. If you missed the live session, you can still engage by watching the recording here.

Recording Available: Catch up on the session by watching the recording here.

Pick Your Time: For our next office hour, please share your preferred timing in the comments below!

This session featured detailed discussions with our expert, Yilun Jin, covering the basics and updates of the challenge, along with a live Q&A.

Feel free to share your thoughts or questions in the comments!

Warm regards,
Team AIcrowd

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💻 Office Hour: 24th April, Wednesday, 16:00 CET

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💻 Office Hour: 24th April, Wednesday, 16:00 CET

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💻 Office Hour: 24th April, Wednesday, 16:00 CET

Hello all,

We invite you to join the Office Hour for the Amazon KDD Cup 2024. This session provides an opportunity to interact with the organizers, delve deep into the challenge details, and have your questions addressed directly by the organisers.

24th April, Wednesday, 16:00 CET
Join the Office Hour on Zoom

For those unable to attend, we will share a recording of the office hours. Feel free to post your questions here, and we will address them during office hours.

Office Hour Highlights:

• Direct engagement with the organizer
• Live Q&A session
• Share your feedback

Meet the Speaker:

Yilun Jin: PhD student at the Hong Kong University of Science and Technology and former intern at the Amazon Rufus team. Yilun is the main curator of the ShopBench dataset and has conducted extensive experiments on it.

If you can’t attend, leave your questions in the comments, and the organizers will address them during the session.

Mark your calendars, prepare your questions, and join the live Office Hour.

Looking forward to seeing you there!
Team Amazon KDD Cup 2024

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📹 Office Hour #1 Recording and Slides | Using Llama 3 Models

Hello all,

Thank you to everyone who joined the Office Hour for the Meta Comprehensive RAG (CRAG) Challenge. If you missed the live session, you can still engage by watching the recording and reviewing the slide deck.

Recording Available: Catch up on the session by watching the recording here.

Slide Deck: Access the presentation slides here.

Using Llama 3 Models: Participants can use Llama 3 Models to build their RAG solutions. Llama 3 models can be downloaded here.

This session featured detailed discussions with our experts Xiao Yang and Kai Sun, covering the CRAG benchmarks, updates on the challenge, and a live Q&A.

Feel free to share your thoughts or questions in the comments!

Warm regards,
Team AIcrowd

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‼️ Imp: Challenge Updates [24 April 2024]

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‼️ Imp: Challenge Updates [24 April 2024]

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‼️ Imp: Challenge Updates [24 April 2024]

Hello everyone,

Here are some updates for the challenge:

• We added the “query_time” to the generate_answer function as an input.
• We’ve corrected an error in the “number of days left” displayed on the main page; it will now accurately show that the challenge ends on 5/20/2024.
• We are working on a batch inference solution and will share it soon. During the interim, we will increase the time-out limit for each example to 30s. Please note we might reduce this limit to a smaller number when the batch inference solution settles.

Thank you for your participation!
Team CRAG

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🧑‍💻 Office Hour for the Comprehensive RAG (CRAG) Challenge

@jeongeum_seok @ry_j Recording and slide deck will be shared in the next 24 hours. The link will be posted on discourse and shared through email as well.

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🧑‍💻 Office Hour for the Comprehensive RAG (CRAG) Challenge

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🧑‍💻 Office Hour for the Comprehensive RAG (CRAG) Challenge

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🧑‍💻 Office Hour for the Comprehensive RAG (CRAG) Challenge

Hello all,

We invite you to join the Office Hour for the Comprehensive RAG (CRAG) Challenge. This Office Hour is a chance to interact with the organisers, gain deep insights into the dataset and problem statement, and get your questions answered.

23rd April, 2024, 18:00 PST
Join the Office Hour on Zoom

For those unable to attend, a recording will be available. Feel free to post your questions here, and the organisers will answer them during the event.

Office Hour Highlights:

• Direct engagement with organisers
• Collaborative discussions with other attendees
• In-depth understanding of CRAG benchmarks
• What’s next in the challenge
• Live Q&A

Meet the speakers

• Xiao Yang: Applied Research Scientist at Meta Reality Labs, PhD in Statistics from Yale, focusing on retrieval augmented generation.
• Kai Sun: Research scientist at Meta, PhD from Cornell, organizer of Gomocup and chair for major NLP conferences.
• Xin Luna Dong: Principal Scientist at Meta, expert in building intelligent personal assistants and knowledge graphs, ACM and IEEE Fellow.

If you can’t attend, leave your questions in the comments, and the organisers will be answered during the session.

Mark your calendars, prepare your questions, and join the live Office Hour.

Looking forward to seeing you there!
Team AIcrowd

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💬 Welcome to KDD Cup 2024: CRAG Comprehensive RAG Benchmark Challenge

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Tentative Challenge Winners

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Tentative Challenge Winners

Hello all,

Thank you for your participation in the Commonsense Persona-Grounded Dialogue Challenge. While we finalize the results through due diligence, we are pleased to announce the tentative winners for both tasks.

Please note that these are tentative results. We will notify you once the final winners are confirmed after the due diligence process is complete.

Best regards,
Team CPDC

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🏆 Generative Interior Design Challenge: Top 3 Teams

Dear Teams,

Thank you for participating in the Generative Interior Design Challenge! We are excited to announce the top three teams selected by an expert jury to advance to the final competition phase, which will take place on April 17 at the Machines Can See Summit in Dubai.

Here is the selection procedure we followed:

• Phase 1 (Jan 30 - Apr 1): Ranking based on the public test. All teams scoring above the baseline were selected for the next phase.
• Phase 2 (Apr 2 - Apr 3): Ranking based on the private test, with the top five teams advancing to the next phase for jury review.
• Phase 3 (Apr 4 - Apr 5): The expert jury ranked and selected the top three teams. Each jury member chose the best result among five generated images across six room categories and three empty scenes per category, doing so repeatedly. The names of the teams were concealed during the voting process. The three teams with the highest number of votes were chosen to proceed to the final phase.

Our jury consisted of experts in interior design, real estate development, and artificial intelligence.

As a result of Phases 1 and 2, the top five teams selected (in alphabetical order) are: Decem, EVATeam, Saidinesh_pola, StableDesign, and XenonStack.

Finally, the top three teams selected by the jury for Phase 3 (in alphabetical order) are:

• Decem (@decem, @littleduck007, @daniel_wang8)
• StableDesign (@Mykola_Lavreniuk, @bartosz_ludwiczuk)
• XenonStack (@xenonstack, @akashpandey_108, @xs296-piydhi)

These teams are now officially selected for the award. Congratulations!

We would like to note that the top three teams selected by the jury also rank among the top four on the public leaderboard of the competition.

We extend our thanks to all participating teams and look forward to the last competition phase on April 17 in Dubai. There, the final ranking will be determined jointly by the expert jury and the audience at the Machines Can See Summit.

Congratulations again, and we look forward to seeing everyone at Machines Can See on April 17th at the Museum of the Future!

Best wishes,
The Generative Interior Design Challenge Organizing Team

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