Accurate language identification is crucial for multilingual systems, yet traditional methods often struggle with computational efficiency and accuracy trade-offs. This challenge explores using bigram analysis—inspired by machine translation evaluation metrics—to build an efficient and accurate language identifier.
Timeline
Start
Nov 2025 Sun, France Time
End
Jan 2026 Mon, France Time
Why this track exists?
Your task is to: 1. Improve Accuracy: Enhance the baseline bigram approach to achieve higher language identification accuracy 2. Optimize Efficiency: Scale the solution for production use 3. Validation: Test your approach against a held-out validation set (provided at hackathon start)
Who is this track for?
Participants
Innovators ready to push the limits of quantum technology.
Industry Partners
Organizations seeking strategic, low-cost innovation with a direct path to prototypes.
Mentors & Experts
Leaders eager to guide and shape next-gen quantum solutions.
Prizes & Outcomes
No prizes yet.
How to get started
Get Started: Review the reference implementation, explore the bigram dataset, and build your optimized language identifier!
