Adaptive Parallel Monte Carlo Tree Search for Efficient Test-time Compute Scaling

ArXi:2604.00510v1 Announce Type: new Monte Carlo Tree Search (MCTS) is an effective test-time compute scaling (TTCS) method for improving the reasoning performance of large language models, but its highly variable execution time leads to severe long-tail latency in practice. Existing optimizations such as positive early exit, reduce latency in favorable cases but are less effective when search continues without meaningful progress. We