An RL-guided MCTS proof search for Tamarin finds more and shorter proofs than standard search across 16 protocol models.
arXiv preprint arXiv:2305.16366 (2023).https: //arxiv.org/abs/2305.16366
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2representative citing papers
Distilling CoT from DeepSeek-R1 to Qwen2.5-7B on competition problems yields 4.76 pp accuracy gain to 69.43% and 73.1% on MATH-500, with accuracy falling as response length decreases.
citing papers explorer
-
Less Effort, Shorter Proofs: Reinforcement Learning for Security Protocol Analysis in Tamarin
An RL-guided MCTS proof search for Tamarin finds more and shorter proofs than standard search across 16 protocol models.
-
Knowledge Distillation from Large Reasoning Models to Compact Student Models: A Case Study on the John O Bryan Mathematics Competition
Distilling CoT from DeepSeek-R1 to Qwen2.5-7B on competition problems yields 4.76 pp accuracy gain to 69.43% and 73.1% on MATH-500, with accuracy falling as response length decreases.