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This article reviews the silver medal solution from the NVIDIA Nemotron Reasoning Challenge, which had 4355 participating teams. It focuses on analyzing the Delta-SVD adapter merging technology and its key role in enhancing the model's generalization ability.
Section 01
This article reviews the silver medal solution from the NVIDIA Nemotron Reasoning Challenge, which had 4355 participating teams. It focuses on analyzing the Delta-SVD adapter merging technology and its key role in enhancing the model's generalization ability.
Section 02
Section 03
NVIDIA Nemotron Model Reasoning Challenge is a Featured-level competition on the Kaggle platform with a prize pool of up to $106,388, attracting 4355 teams worldwide to compete. The core task of the competition is to train a LoRA adapter (rank ≤32) on the Nemotron-3-Nano-30B-A3B base model to maximize the model's accuracy on the "Alice's Wonderland" reasoning puzzle benchmark.
The solution achieved the following results:
| Metric | Value |
|---|---|
| Private Leaderboard Score (Final) | 0.86 |
| Medal | Silver 🥈 |
| Public Leaderboard Rank | 480 / 4355 (Top 11%) |
| Number of Submissions | 22 |
| Score Evolution | 0.54 → 0.86 |
It is worth noting that 1627 teams tied at 0.86 on the public leaderboard, making the competition extremely fierce. The real gap was in the private leaderboard performance—solutions with more stable generalization maintained 0.86 on the hidden test set, successfully advancing from the edge of the bronze medal on the public leaderboard to the silver medal zone.
Section 04
From the complete record of 22 submissions, the iterative path of the solution can be clearly seen:
Section 05
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Section 07
The core of this phase was exploring how to robustly merge multiple adapters:
Section 08
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