{"schemaVersion":1,"target":{"type":"reading","id":"8400e4f062c1cf71ff857695cdc4a2066d7d7d5d3b4edc62e41d31643ebb8261","revision":"14658e80-4d5e-4fca-8700-b996ffaebd46","revisionKind":"publication-id","title":"arXiv cs.AI: Wang and coauthors propose training forecasters to keep errors from echoing","url":"https://escapemeridian.com/readings/arxiv-cs-ai-wang-and-coauthors-propose-training-forecasters-to-8400e4f0"},"source":{"type":"source","id":"https://arxiv.org/abs/2611.07473","revision":"7d5471c594d0ff33a208a7b0c67cbc0db238cbe8c11ee5d0b9a9482d14e35db3","revisionKind":"sha256-source-text","title":"Echoes of Error: Residual-Directional Local Rollout Consistency for Timeseries Forecasting","url":"https://arxiv.org/abs/2611.07473"},"status":"available","items":[],"next":null,"scope":"Explicit citations in public readings and public file attachments to this reading. Shared topics are not citations. Other artifact types need an explicit reference adapter."}