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arXiv1d ago
4.5

Limits of Difficulty Scaling: Hard Samples Yield Diminishing Returns in GRPO-Tuned SLMs

Suraj Yadav, Siddharth Yadav, Parth Goyal

View original ↗

Analysis

Viral velocity
low
Implementation gapYES
Novelty5/10
Categorypaper
Topics
reasoningfine-tuningslmrl

Opportunity Brief

Develop a benchmarking toolkit that maps the plateau points of SLMs during GRPO/RL tuning. This tool should provide automated 'difficulty-scaling' analysis to help developers stop training once they hit diminishing returns.

Suggested repo: grpo-limit

"Know exactly when your SLM stops learning: Automated difficulty-plateau detection."

Estimated effort: 20h