Enigmata: Scaling logical reasoning in large language models with synthetic verifiable puzzles

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• MathConstraint: Automated Generation of Verified Combinatorial Reasoning Instances for LLMs cs.LG · 2026-05-08 · unverdicted · none · ref 10

  MathConstraint generates scalable, automatically verifiable combinatorial problems where LLMs achieve 18.5-66.9% accuracy without tools but roughly double that with solver access.

• Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key cs.AI · 2026-05-07 · unverdicted · none · ref 62 · 2 links

  RL training compute for logical reasoning follows a power law in proof depth whose exponent rises with logic expressiveness, and more expressive training yields larger gains on downstream benchmarks.

• A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions cs.LG · 2026-04-19 · accept · none · ref 1

  The paper delivers the first systematic taxonomy and hierarchical framework for data-efficient reinforcement learning post-training of large language models across data-centric, training-centric, and framework-centric views.

• Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration cs.LG · 2026-04-13 · unverdicted · none · ref 4

  NExt accelerates RLVR training for LLMs by nonlinearly extrapolating low-rank parameter trajectories extracted from LoRA runs.