Expand References
Turn one to three seed papers into a structured follow-up reading list. Use this when the human already has anchor papers and wants the next papers to read.
Arguments
- Positional arguments are the seed papers. Quote multi-word titles.
--negative <paper>may be repeated to push the workflow away from an unwanted cluster.--pool all-cs|recentselects the Semantic Scholar recommendation pool.--limit <n>controls how many raw recommendations are requested before reranking.--per-bucket-limit <n>caps each curated bucket after scoring.
Workflow
- Run
python scripts/run.py .... - Read
result.closest_neighborsfor the immediate next reads. - Read
result.bridge_papersfor papers that connect multiple seeds. - Read
result.foundational,result.methodological,result.recent, andresult.surveys_or_benchmarksfor curated slices of the neighborhood. - If the result is sparse or off-topic, adjust the seed set or add
--negativepapers and rerun.
Output
- The script prints the unified JSON envelope described in
output_contract.md. - The underlying workflow result is
ExpandReferencesResult.to_dict(). result.notescaptures dropped records and other execution notes.
When To Escalate
- Fewer than one clear seed paper is available.
- The resolved seeds are obviously duplicates or wrong papers.
- The output is empty even after trying better seeds or a different recommendation pool.