{"as_of":"2026-08-21T01:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:33577c993697ad6e4a20584c06c3ff1f587528d233d3d6c9d9a0c56af4976281","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":1,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T08:24:32.296192Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-11T20:36:11.909271Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.21807","last_updated":"2025-03-25T06:28:42Z","snapshot_observed_at":"2026-08-16T19:49:18.468446Z","submitted_at":"2025-03-25T06:28:42Z","title":"LERO: LLM-driven Evolutionary framework with Hybrid Rewards and Enhanced Observation for Multi-Agent Reinforcement Learning","version":1},"cited_work":{"arxiv_id":"2503.21807","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.21807","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"ca052660-341b-47f7-b724-494722a0a99d","year":2025},"citing_paper":{"arxiv_id":"2604.23345","last_updated":"2026-04-25T15:07:46Z","snapshot_observed_at":"2026-08-11T00:21:28.081788Z","submitted_at":"2026-04-25T15:07:46Z","title":"Bridging Reasoning and Action: Hybrid LLM-RL Framework for Efficient Cross-Domain Task-Oriented Dialogue","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-05-08T08:24:32.296192Z"},"links":{"cited_paper":"/paper/2503.21807","citing_paper":"/paper/2604.23345"},"observation_digest":"sha256:8f1a012c8a26c4f401ece117f5ea4a4c3a126baf649d6763959bd649296c5479","observation_id":"8bef8d3f-f745-4e0e-925c-8a5bf1d973a7","resolution":{"observed_at":"2026-05-11T20:36:11.911929Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2503.21807/citation-record","integrity":"/paper/2503.21807/integrity","json":"/paper/2503.21807/citation-record.json","paper":"/paper/2503.21807"},"outbound":[],"paper":{"arxiv_id":"2503.21807","last_updated":"2025-03-25T06:28:42Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-16T19:49:18.468446Z","submitted_at":"2025-03-25T06:28:42Z","title":"LERO: LLM-driven Evolutionary framework with Hybrid Rewards and Enhanced Observation for Multi-Agent Reinforcement Learning"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2503.21807."}