Paper-replication workflow enables coding agents to systematically replicate computational claims from ML papers

We introduce Paper-replication, a workflow that makes each selected paper claim a target with recorded evidence, and implement it as a coding-agent skill.

All twelve workspaces pass the completion gate, and all 158 recorded targets are matched with report coverage.

Paper-replication makes completion depend on workspace evidence and validation checks rather than on the agent's final message.

Even in this completed workspace state, repeated runs differ in how papers are divided into targets, in numerical fidelity to the source papers, in elapsed replication time, in the number of intermediate executions replaced before final evidence is accepted, and in the rules used to accept evidence.