depth-scaling

DeepLoop introduces a residual scaling method for looped Transformers that adjusts for parameter visits, improving stability and performance when physical blocks are reused across multiple rounds.

Introduces the Complexity Ceiling Benchmark (CCB) that evaluates LLM reasoning decay as the number of sequential steps increases across three domains. Finds a consistent geometric per-step decay and that all models collapse on transitive social logic within 5 steps, even with strong overall accuracy.