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snehananavati
Sneha Nanavati

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Challenges Entered

Generate Synchronised & Contextually Accurate Videos

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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 Building’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 dataset and open-ended challenge for music recommendation research

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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? πŸ˜‰

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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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vrv 0
cadabullos 0
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Participant Rating

Sounding Video Generation (SVG) Challenge 2024

πŸ“Ή Welcome to Sounding Video Generation Challenge 2024

About 2 months ago

The Sounding Video Generation (SVG) Challenge 2024 is a competition to create AI models that make videos where the visuals match perfectly with sounds, like a dog barking in sync with the video. Participants will work to improve how well sounds and scenes align, with prizes for the best results.

ADVANCING AUDIO-VISUAL SYNCHRONISATION

Join the Sounding Video Generation (SVG) Challenge 2024, a groundbreaking competition at the intersection of video generation and audio-visual synchronisation. This innovative challenge invites participants to build state-of-the-art AI models that generate perfectly aligned and contextually accurate videos guided by audio.

Use your machine learning expertise to advance the frontier of audio-visual synchronisation, transforming datasets into dynamic, synchronised videos. With the right code and creativity, you’ll contribute to a rapidly evolving field that’s set to redefine how we generate and experience multi-modal content.

dataset-preview

:bookmark_tabs: The Task
Develop models that generate videos with synchronised and contextually relevant audio in two specialised tracks:

  • Temporal Alignment Track: Create videos where the audio is perfectly synchronised with the video content in time (e.g., a dog barking exactly when seen in the video). Find the starter kit here.
  • Spatial Alignment Track: Develop models that produce videos with spatially aligned audio, creating a real sense of direction and space. Find the starter kit here.

Both tracks aim to push the boundaries of multi-modal AI, offering a unique platform to benchmark cutting-edge solutions in this underexplored domain.

:computer:Check out the starter-kits for Temporal Alignment Track and Spatial Alignment Track.
:file_cabinet: Download the resources for the challenge Temporal Alignment Track and Spatial Alignment Track.

:date: Timeline

  • Warmup Round: 29th Oct 2024
  • Phase I: 2nd Dec 2024
  • Phase II: 3rd Jan 2025
  • Challenge End: 25th Mar 2025

:moneybag: Prizes
The challenge boasts a prize pool of USD 35,000 split across both tracks. The top three teams or participants in each track will be rewarded as follows:

  • Track 1: Temporal Alignment ($17,500)
    • :1st_place_medal: First place: USD 10,000
    • :2nd_place_medal: Second place: USD 5,000
    • :3rd_place_medal: Third place: USD 2,500
  • Track 2: Spatial Alignment ($17,500)
    • :1st_place_medal: First place: USD 10,000
    • :2nd_place_medal: Second place: USD 5,000
    • :3rd_place_medal: Third place: USD 2,500

Join a Thriving Community
Collaborate with like-minded researchers, practitioners, and AI enthusiasts eager to share ideas, team up, and drive innovation in this captivating challenge.

Sign up now for the SVG Challenge 2024 and start building your models in the warm-up round!

πŸ’¬ Feedback & Suggestions

About 2 months ago

We are constantly trying to improve this challenge for you and would appreciate any feedback you might have! :raised_hands:

Please reply to this thread with your suggestions and feedback on making the challenge better for you!

  • What have been your major pain points so far?
  • What would you like to see improved?

All The Best!

πŸ‘₯ Looking for teammates?

About 2 months ago

Competing is more fun with a team!

Introduce yourself here, and find others who are looking to team up! :sparkles:

:writing_hand: Format:

  • A short introduction about you and your background.
  • What brings you to this challenge?
  • Some ideas you wish to explore as a part of this challenge?

All The Best!

Meta Comprehensive RAG Benchmark: KDD Cup 2-9d1937

[Issue resolved] We were asked to submit the revision but revision functionality is disabled

3 months ago

The deadline is now updated on OpenReview too. Please try to make a submission again.

Final Evaluation Process & Team Scores

4 months ago

There are no manual scores, only auto-scores.

πŸ† Meta CRAG Challenge 2024 Winners Announcement

4 months ago

August 02, 2024 11:59PM UTC-0, updated in the post.

πŸ† Meta CRAG Challenge 2024 Winners Announcement

4 months ago

Hello Participants,

We are excited to announce the winners of the Meta CRAG Challenge 2024. We appreciate your patience as we completed the due diligence process for the annotations.

We want to thank all participants for their efforts and contributions to improve RAG solutions. Over the last four months, the Meta CRAG Challenge has seen over 2000 participants from various countries, making over 5500 submissions. Below are the winners for each task. The final evaluation process can be found here: Final Evaluation Process & Team Scores

Task 1: Retrieval Summarization

  • :1st_place_medal: Team db3
  • :2nd_place_medal: Team md_dh
  • :3rd_place_medal: Team ElectricSheep
  • :bouquet: Simple_w_condition Question: Team dummy_model
  • :bouquet: Set Question: Team dummy_model
  • :bouquet: Comparison Question: Team dRAGonRAnGers
  • :bouquet: Aggregation Question: Team dummy_model
  • :bouquet: Multi-hop Question: Team bumblebee7
  • :bouquet: Post-processing Question: Team dRAGonRAnGers
  • :bouquet: False Premise Question: Team ETSLab

Task 2: Knowledge Graph and Web Retrieval

  • :1st_place_medal: Team db3
  • :2nd_place_medal: Team APEX
  • :3rd_place_medal: Team md_dh
  • :bouquet: Simple_w_condition Question: Team ElectricSheep
  • :bouquet: Set Question: Team ElectricSheep
  • :bouquet: Comparison Question: Team dRAGonRAnGers
  • :bouquet: Aggregation Question: Team ElectricSheep
  • :bouquet: Multi-hop Question: Team ElectricSheep
  • :bouquet: Post-processing Question: Team ElectricSheep
  • :bouquet: False Premise Question: Team Future

Task 3: End-to-End Retrieval-Augmented Generation

  • :1st_place_medal: Team db3
  • :2nd_place_medal: Team APEX
  • :3rd_place_medal: Team vslyu-team
  • :bouquet: Simple_w_condition Question: Team StarTeam
  • :bouquet: Set Question: Team md_dh
  • :bouquet: Comparison Question: Team dRAGonRAnGers
  • :bouquet: Aggregation Question: Team md_dh
  • :bouquet: Multi-hop Question: Team ETSLab
  • :bouquet: Post-processing Question: Team md_dh
  • :bouquet: False Premise Question: Team Riviera4

We welcome all teams to submit a technical report to the 2024 KDD Cup RAG Workshop. The report should follow the KDD submission format.

  • Submission link: OpenReview
  • Submission deadline: 11:59 UTC, Aug 2, 2024
  • Submission format: Submissions are limited to 8 pages (excluding references), must be in PDF, and use the ACM Conference Proceeding template (two-column format). For more details, please refer to: KDD 2024 ADS Track Call for Papers

We extend our sincere gratitude to all participants who contributed to this event!

All the best,
Meta & AIcrowd

Final Evaluation Process & Team Scores

4 months ago

Hello Participants,

We want to thank all participants for their efforts and contributions to improving RAG systems. This post provides information about the final evaluation process and shares the final scores.

Manual annotation:

For stage 2 in this challenge, we first conducted auto-evaluation for all the teams that provided submission numbers in Phase 2. We then selected the top 15 teams’ submissions according to the auto-eval scores for manual evaluation. The final scores are determined by the scores calculated from the manual grading labels. Automatic and manual evaluation details can be found in the paper.

Weighting:

We applied traffic weights to the questions to understand the solutions in real-world use cases. The traffic weights come from a real QA use case and are generated as follows. Within each domain, we first clustered the questions into question types with the exact definition of the CRAG questions. Then, we derived the weights for each type based on aggregated data reflective of user interactions. We applied the weight to each CRAG question to bridge the result to reflect user experience and reported the macro average scores across all domains (i.e., giving the same weight to all domains).

Code validation

We conducted a code review for the winning solutions to ensure the validity of the codes. For example, we checked whether there was any prompt attack to mislead the auto-evaluation and whether the solutions used too many hard-coded answers.

The scores from the winning teams are listed below.

Task Team Score
Task 1 db3 28.40%
md_dh 24%
ElectricSheep 21.8%
Task 2 db3 42.7%
APEX 41.0%
md_dh 31.0%
Task 3 db3 47.8%
APEX 44.9%
vslyu-team 25.6%

The scores from the winning teams are listed below.

Task Question Type Team Score
Task 1 simple_w_condition dummy_model 17.9
set dummy_model 21.25
comparison dRAGonRAnGers 37
aggregation dummy_model 21.5
multi_hop bumblebee7 16.8
post_processing dRAGonRAnGers 8.6
false_premise ETSLab 65.2
Task 2 simple_w_condition ElectricSheep 23.9
set ElectricSheep 36.65
comparison dRAGonRAnGers 38
aggregation ElectricSheep 18.75
multi_hop ElectricSheep 23.2
post_processing ElectricSheep 11.75
false_premise Future 64.6
Task 3 simple_w_condition StarTeam 42.2
set md_dh 31.7
comparison dRAGonRAnGers 37.25
aggregation md_dh 26.6
multi_hop ETSLab 25.7
post_processing md_dh 8.3
false_premise Riviera4 72.2

We extend our sincere gratitude to all participants who contributed to this event!

All the best,

Meta & AIcrowd

Has the Winner Notification already been sent?

4 months ago

My previous reply clearly states that the winner announcement will be made after the due diligence process is completed. Nowhere does it specify that it will be sent only to the winning participants. As is the standard practice for all challenges, the winner announcement email will be sent to all participating teams and candidates once the due diligence process is over.

‼️ ⏰ Select Submission ID before 20th June, 2024 23:55 UTC

4 months ago

The winners are not announced yet. You will receive an email about the winner announcement once the due diligence is completed.

Has the Winner Notification already been sent?

4 months ago

The winners are not announced yet. You will receive an email about the winner announcement once the due diligence is completed.

Amazon KDD Cup 2024: Multi-Task Online Shopping Ch

Change Team Name Request

4 months ago

Your team name has been updated to BMI_DLUT.

Change Team Name Request

4 months ago

Hello, Your team name has been updated to AML_LabCityU

snehananavati has not provided any information yet.