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snehananavati
Sneha Nanavati

Organization

AIcrowd

Location

IN

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Challenges Entered

Improve RAG with Real-World Benchmarks

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failed 247893
graded 247892

Multi-Agent Dynamics & Mixed-Motive Cooperation

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Small Object Detection and Classification

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failed 235496

Understand semantic segmentation and monocular depth estimation from downward-facing drone images

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A benchmark for image-based food recognition

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Using AI For Buildingโ€™s Energy Management

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What data should you label to get the most value for your money?

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Interactive embodied agents for Human-AI collaboration

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Behavioral Representation Learning from Animal Poses.

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Airborne Object Tracking Challenge

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ASCII-rendered single-player dungeon crawl game

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5 Puzzles 21 Days. Can you solve it all?

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Measure sample efficiency and generalization in reinforcement learning using procedurally generated environments

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5 Puzzles 21 Days. Can you solve it all?

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Self-driving RL on DeepRacer cars - From simulation to real world

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3D Seismic Image Interpretation by Machine Learning

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5 Puzzles 21 Days. Can you solve it all?

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5 Puzzles 21 Days. Can you solve it all?

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5 Puzzles 21 Days. Can you solve it all?

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Multi-Agent Reinforcement Learning on Trains

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A benchmark for image-based food recognition

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Sample-efficient reinforcement learning in Minecraft

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5 Puzzles, 3 Weeks. Can you solve them all? ๐Ÿ˜‰

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Multi-agent RL in game environment. Train your Derklings, creatures with a neural network brain, to fight for you!

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Predicting smell of molecular compounds

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5 Problems 21 Days. Can you solve it all?

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5 Puzzles 21 Days. Can you solve it all?

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5 Puzzles, 3 Weeks | Can you solve them all?

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Grouping/Sorting players into their respective teams

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5 Problems 15 Days. Can you solve it all?

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5 Problems 15 Days. Can you solve it all?

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5 PROBLEMS 3 WEEKS. CAN YOU SOLVE THEM ALL?

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Remove Smoke from Image

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Classify Rotation of F1 Cars

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Can you classify Research Papers into different categories ?

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Can you dock a spacecraft to ISS ?

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Multi-Agent Reinforcement Learning on Trains

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Multi-Class Object Detection on Road Scene Images

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Localization, SLAM, Place Recognition, Visual Navigation, Loop Closure Detection

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Detect Mask From Faces

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Identify Words from silent video inputs.

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A Challenge on Continual Learning using Real-World Imagery

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graded 200977

Music source separation of an audio signal into separate tracks for vocals, bass, drums, and other

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failed 247893
graded 247892

Make Informed Decisions with Shopping Knowledge

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Participant Rating
vrv 0
cadabullos 0
cavalier_anonyme 0
Participant Rating

Meta Comprehensive RAG Benchmark: KDD Cup 2

Why am I not qualified for this round.

15 days ago

Can you please check again? The qualifying criteria for Round 1b has now been removed, so you should be able to make a submission now.

The team's challenge has team-freeze in effect

24 days ago

Hi ryo2,

This issue has been fixed. Can you please try again.

๐Ÿ“น Office Hour #1 Recording and Slides | Using Llama 3 Models

About 1 month ago

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.

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

:bar_chart: Slide Deck: Access the presentation slides here.

:rocket: 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

โ€ผ๏ธ Imp: Challenge Updates [24 April 2024]

About 1 month ago

Hello everyone,

Here are some updates for the challenge:

  • We added the โ€œquery_timeโ€ to the generate_answer function as an input.
  • Weโ€™ve corrected an error in the โ€œnumber of days leftโ€ 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

Meta KDD Cup 24 - CRAG - Retrieval Summarization

Why am I not eligible to participate?

15 days ago

Have you clicked on the participate button and accepted the challenge rules?

Why am I not eligible to participate?

15 days ago

You should be able to make a submission now.

EPFL-CSS-233-f19e38

CS233-2024-FashionMNIST

16 days ago

We will be competing for who gets the best accuracy and F1 score on the FashionMNIST dataset. Your ranking will not be used for grading, however you are required to participate. Letโ€™s see how your models do compared to the others!

You will be uploading your results file in the โ€œsubmissionsโ€ tab of the challenge. Everyone in the team gets 5 submissions per day. Winners get chocolates!

Note: Before you save test dataset predictions, print out the shape and make sure it is of shape (N,) (and not (N,1) etc.)

Good luck and have fun!

Task 1: Predicting Room Indoor Temperature

Predicting Temperature And Power Consumption In An

Task 2: Predicting Energy consumption

Amazon KDD Cup 2024: Multi-Task Online Shopping Ch

๐Ÿ“น Office Hour #2 Recording

29 days ago

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 .

:movie_camera: 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

๐Ÿ’ป Office Hour: May 1, 2024, Wednesday 10AM CST

About 1 month ago

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.

:alarm_clock: May 1, 2024, Wednesday 4AM CET/10AM CST
:point_right: 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.

:video_camera: Office Hour Highlights:

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

:woman_teacher: 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.

:speech_balloon: If you canโ€™t attend, leave your questions in the comments, and the organizers will address them during the session.

:spiral_calendar: 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

๐Ÿ“น Office Hour #1 Recording

About 1 month ago

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.

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

:date: 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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