LEAD: Breaking the No-Recovery Bottleneck in Long-Horizon Reasoning

Apple · 1 month ago · 16

Researchers identified a "no-recovery bottleneck" in large language models attempting long-horizon reasoning tasks, where errors on difficult steps become irreversible despite task decomposition. They developed Lookahead-Enhanced Atomic Decomposition (LEAD), which combines short-horizon future validation with overlapping rollouts to maintain stability while enabling error correction. The method allows Claude o4-mini to solve Checkers Jumping puzzles up to complexity n=13, compared to n=11 with extreme decomposition approaches.