FAR Pipeline Filters 5245 Combinatorics Papers to 77 Review Items

The system ingests a research direction rather than a pre-selected problem. It runs a literature-to-review cascade that extracts conjectures, applies automated checks for well-posedness and openness, then routes survivors through reasoning and triage stages. In the reported combinatorics pilot the pipeline surfaced 598 potential resolutions before human review.

Raw extraction yielded 6453 items; filtering removed duplicates, solved problems and malformed statements to leave 4717 candidates. Subsequent stages selected 598 for deeper automated scrutiny and 77 for expert inspection. Among these the authors report resolutions or partial results on multiple named conjectures.

Operational impact centers on reallocating scarce expert review time away from initial problem selection. The cascade treats frontier-model reasoning as a limited resource and concentrates it on pre-filtered artifacts. This shifts human effort from broad search to targeted validation.

Next steps require scaling the pipeline across additional fields and measuring verification rates against manual literature search baselines. Deployment records from similar recommender-style systems indicate that sustained throughput depends on maintaining low false-positive rates at each filter stage.