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Post-Training Language Models for Gold-Medal Performance in Coding Competitions

Competitive programming has become a key test of large language model reasoning, with international competitions such as IOI and ICPC representing its most challenging settings. We present an end-to-end specialization pipeline combining large-scale problem curation, synthetic reasoning traces, supervised fine-tuning (SFT), and reinforcement learning (RL). Using 22,000 curated problems, we train…

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Loss Landscapes of LLMs: The Map Beneath Gradient Descent

Hello, I'm Shrijith Venkatramana, and I'm building LiveReview — a blast-radius aware AI code review built for your business-critical systems.

  • Loss landscapes of LLMs are complex, non-bowl-like structures
  • Gradient descent guides model parameters downhill in high-dimensional space
  • Hessian matrix reveals landscape curvature, aiding training insights

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