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  3. Scaling Data Difficulty: Improving Coding Models via Reinfor
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Scaling Data Difficulty: Improving Coding Models via Reinforcement Learning on Fresh and Challenging Problems

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Evidence fresh

Evidence Receipt

Freshness: 2026-04-02T02:30:40.136932+00:00

Claims: 0

References: 0

Proof: unverified

Freshness: fresh

Source paper: Scaling Data Difficulty: Improving Coding Models via Reinforcement Learning on Fresh and Challenging Problems

PDF: https://arxiv.org/pdf/2603.07779v1

Source count: 0

Coverage: 17%

Last proof check: 2026-04-02T02:30:40.136Z

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Scaling Data Difficulty: Improving Coding Models via Reinforcement Learning on Fresh and Challenging Problems

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Last verification: 2026-04-02T02:30:40.136Z

Freshness: fresh

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References: 0

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Coverage: 17%

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Keep exploring

Builds On This
A Deep Dive into Scaling RL for Code Generation with Synthetic Data and Curricula
Score 4.0down
Builds On This
CoDiQ: Test-Time Scaling for Controllable Difficult Question Generation
Score 5.0down
Prior Work
Learning with Challenges: Adaptive Difficulty-Aware Data Generation for Mobile GUI Agent Training
Score 7.0stable
Prior Work
EvolveCoder: Evolving Test Cases via Adversarial Verification for Code Reinforcement Learning
Score 7.0stable
Prior Work
CODA: Difficulty-Aware Compute Allocation for Adaptive Reasoning
Score 7.0stable
Higher Viability
Breaking Training Bottlenecks: Effective and Stable Reinforcement Learning for Coding Models
Score 8.0up
Higher Viability
ReflexiCoder: Teaching Large Language Models to Self-Reflect on Generated Code and Self-Correct It via Reinforcement Learning
Score 9.0up
Competing Approach
Exploring different approaches to customize language models for domain-specific text-to-code generation
Score 7.0stable

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