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snehananavati
Sneha Nanavati

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Challenges Entered

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Build an LLM agent for five real-world games

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Detecting Energy Flexibility in Buildings

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Create Context-Aware, Dynamic, and Immersive In-Game Dialogue

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Improve RAG with Real-World Benchmarks | KDD Cup 2025

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Automating Building Data Classification

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failed 280150

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 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 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? 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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Generate Videos with Temporal and Semantic Audio Sync

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Create Videos with Spatially Aligned Stereo Audio

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Build Context-Aware Conversational NPC Agents

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Task-Oriented Conversational AI for NPC Agents

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Participant Rating
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cadabullos 0
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ReachAMY 0
pravesh_tiwari 0
Participant Rating

Orak Game Agent Challenge

๐Ÿ’ฌ Feedback & Suggestions

5 days ago

Hi @seokwoo_song Please refer to this post for clarification on model limits: Clarification on Track 1 โ€œ8B parameter limitโ€

๐Ÿ’ฌ Feedback & Suggestions

7 days ago

Hello all, Thanks for the feedback. Weโ€™re reviewing it and exploring how we can better support you with the submission process.

๐Ÿ’ฌ Feedback & Suggestions

10 days ago

Hello @vk_c,

  1. You can use this Discourse forum for all queries and feedback. Additionally, we have a Discord text channel for collaboration: AIcrowd
  2. All the details on compute credits, how they are distributed, and the process to apply for them can be found here: ๐Ÿช™ How to claim compute credits
  3. The challenge is open to all individuals.

All the best!

๐Ÿ’ฌ Feedback & Suggestions

10 days ago

Hello @cheong_wei_xun
Details on compute credits and how to claim them can be found here: ๐Ÿช™ How to claim compute credits

Questions about tracks and credits

14 days ago

Hello!

  1. Yes, a team is able to join and make submissions for both the tracks. Please ensure to form your team by 12th December 2025.
  2. Details on the credits and how to claim them will be announced soon. Thank you for your patience and for participating in this challenge.

When will the sponsored Brev credits be made available?

14 days ago

Hello @inchangbaek,
Details on the credits and how to claim them will be announced soon. Thank you for your patience and for participating in this challenge.

๐Ÿ’ฌ Feedback & Suggestions

24 days 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!

๐Ÿ‘ฅ Looking for teammates?

24 days ago

Solving challenges is more fun with a team!

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

  • Introduce yourself and share a bit about your background.
  • What brings you to this challenge?

Team registration deadline: 12 Dec 2025

All the best!

Flextrack Challenge 2025

Open-Source License

About 2 months ago

Hello @slimmer
MIT license would also be fine. Please use either Apache 2.0 or MIT license.

Important Update

2 months ago

:warning: Update (October 10th, 2025)
This announcement has been superseded by a newer post:
:point_right: Phase 2 โ€” We hear you ! Hereโ€™s how weโ€™re updating the plan
Please refer to the latest update for the final Phase 2 format, dataset, and scoring details.
(This original announcement remains for archival reference only.)

Please note some key updates about the challenge:

Phase 1 (Competition Phase)

  • Ends on Sunday, 19 October 2025.
  • Includes submission of the Solution Documentation.

Phase 2

  • Expected to open between 20 and 22 October 2025, 23:59 UTC.
  • The Solution Documentation deadline is extended to this window.

Phase 2 Format

  • Multiple one-year datasets will be sliced into shorter, equal-length context windows.
  • Slices will include a mix of previously seen and new sites.
  • In Phase 2, participants will make a single prediction per time series. This is to prevent look-ahead.
  • Phase 2 is designed to ensure fairness and reward models that can generalise, are context-aware, and are transferable across sites.

Scoring and Final Ranking

  • The final ranking will factor in two components with equal weight:
    1. the score from the Phase 1 private dataset (SiteF), and
    2. the score from Phase 2.
  • Within Phase 2, scores will be the equal-weighted average across all slices and sites.

Scoring Code and Starter Kit

  • We will publish the scoring script and a minimal code sample in the starter kit.
  • These materials will be available when Phase 2 opens.

Challenge Description Clarification

  • Participants must predict each timestamp tโ‚€ using only inputs where t_input โ‰ค tโ‚€.
  • Training data includes ground-truth time series and demand response flags.
  • Models should learn consumption patterns both when demand response is inactive and when it is active.

๐Ÿ“น Townhall Recording & Q&A with Challenge Organisers | How to use digital twin data to predict demand response capacity

3 months ago

Hi Ryan, Thanks for flagging this. The end date in the pill on challenge banner is now fixed.

๐Ÿ“น Townhall Recording & Q&A with Challenge Organisers | How to use digital twin data to predict demand response capacity

3 months ago

Each participant can only make one submission.

  • If you are competing as part of a team, your team submits one entry total.
  • If you are competing individually, you submit one entry on your own.

๐Ÿ“น Townhall Recording & Q&A with Challenge Organisers | How to use digital twin data to predict demand response capacity

3 months ago

Hello all,

Thank you to everyone who joined FlexTrack Challenge 2025 Townhall #1. In this session, we introduced the challenge and explored how digital twin data from commercial buildings can be used to forecast demand response flags and capacities.

If you missed it, you can catch up here:
:video_camera: Watch the recording: https://youtu.be/oKBcMxAQ3vg
:page_facing_up: Download the slides: Flextrack Townhall โ€“ Google Drive

Highlights from the session:

  • Context on the evolving role of prosumers, batteries, and smart devices in the National Electricity Market (NEM)
  • Overview of the synthetic dataset, generated from digital twins of commercial office buildings
  • Key variables like weather, HVAC setpoints, internal loads, and demand response flags
  • Approach to building generalizable, context-aware models that work across multiple building sites
  • Details on evaluation metrics, submission format, and documentation requirements
  • Q&A on temporal modelling, model transferability, and real-world use cases for aggregators and VPP operators
  • New! Top teams will have the chance to co-author a research publication based on their solutions
  • Synthetic data design: sites modeled across different Australian climate zones for realistic diversity
  • Final submission reminder: competition phase ends October 19, 2025, with one combined CSV per team

If you have questions or ideas to share, drop them in the comments below so the community and organisers can help.

Team FlexTrack

Live Q&A with Challenge Organisers ๐Ÿ“Š Join the Townhall on Sept 22!

3 months ago

We will share the recording in the next day or two!

New to the challenge - participation rules

3 months ago

Hi Priya,

The competition phase is open to all!

All the best

Why does it show that the competition round is completed?

3 months ago

Hi @priya12
Yes, you can directly participate in Phase 2.

snehananavati has not provided any information yet.