{"as_of":"2026-08-11T08:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:70a39f45b9336a77439bffac5deb1d0b0640cc1066d455f29c59440f7c0a6679","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":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T18:11:28.101723Z","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":"2026-06-30T12:34:38.866552Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2409.07487","last_updated":"2024-09-13T19:42:12Z","snapshot_observed_at":"2026-08-10T12:32:19.829238Z","submitted_at":"2024-09-04T19:00:59Z","title":"MoA is All You Need: Building LLM Research Team using Mixture of Agents","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.07487","snapshot_observed_at":"2026-08-09T18:11:28.101723Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.00674","last_updated":"2025-02-02T05:23:29Z","snapshot_observed_at":"2026-08-09T18:06:03.044123Z","submitted_at":"2025-02-02T05:23:29Z","title":"Rethinking Mixture-of-Agents: Is Mixing Different Large Language Models Beneficial?","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-09T18:11:28.101723Z"},"links":{"cited_paper":"/paper/2409.07487","citing_paper":"/paper/2502.00674"},"observation_digest":"sha256:ede341d41ea7b9ea51841faa404a845e5da11e3148e13ce3103ac7c6e7a003c0","observation_id":"c3860c71-e172-46a8-b888-aafa58327361","resolution":{"observed_at":"2026-08-09T18:11:28.101723Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.07487","last_updated":"2024-09-13T19:42:12Z","snapshot_observed_at":"2026-08-10T12:32:19.829238Z","submitted_at":"2024-09-04T19:00:59Z","title":"MoA is All You Need: Building LLM Research Team using Mixture of Agents","version":2},"cited_work":{"arxiv_id":"2409.07487","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.07487","snapshot_observed_at":"2026-06-30T12:34:38.866552Z","title":"MoA is all you need: Building LLM research team using mixture of agents","venue":null,"work_id":"cc28c5f5-6ce8-413b-87ec-97f121aaf415","year":2024},"citing_paper":{"arxiv_id":"2512.22579","last_updated":"2026-05-07T07:31:10Z","snapshot_observed_at":"2026-08-11T06:13:24.875236Z","submitted_at":"2025-12-27T12:42:47Z","title":"SANet: A Semantic-aware Agentic AI Networking Framework for Cross-layer Optimization in 6G","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-16T19:21:51.147059Z"},"links":{"cited_paper":"/paper/2409.07487","citing_paper":"/paper/2512.22579"},"observation_digest":"sha256:96e406654a19ab9ef125c7968104f9c154032b92626f700cdba0eedc7f9f303d","observation_id":"8f16f154-00da-4599-86b9-4d9ab187a59c","resolution":{"observed_at":"2026-05-16T19:23:19.692503Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.07487","last_updated":"2024-09-13T19:42:12Z","snapshot_observed_at":"2026-08-10T12:32:19.829238Z","submitted_at":"2024-09-04T19:00:59Z","title":"MoA is All You Need: Building LLM Research Team using Mixture of Agents","version":2},"cited_work":{"arxiv_id":"2409.07487","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.07487","snapshot_observed_at":"2026-06-30T12:34:38.866552Z","title":"MoA is all you need: Building LLM research team using mixture of agents","venue":null,"work_id":"cc28c5f5-6ce8-413b-87ec-97f121aaf415","year":2024},"citing_paper":{"arxiv_id":"2605.25030","last_updated":"2026-05-24T12:15:27Z","snapshot_observed_at":"2026-08-01T15:31:44.956983Z","submitted_at":"2026-05-24T12:15:27Z","title":"MimirRAG: A Multi-Agent RAG Framework for Financial Data Retrieval with Metadata Integration","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-30T12:27:46.629948Z"},"links":{"cited_paper":"/paper/2409.07487","citing_paper":"/paper/2605.25030"},"observation_digest":"sha256:5c739d55ceef4a5697230754f755b2f3019086f607e295f799615477e17f4f59","observation_id":"de9c038a-9a13-40d0-b209-d3a3f467840a","resolution":{"observed_at":"2026-06-30T12:34:38.868163Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2409.07487/citation-record","integrity":"/paper/2409.07487/integrity","json":"/paper/2409.07487/citation-record.json","paper":"/paper/2409.07487"},"outbound":[],"paper":{"arxiv_id":"2409.07487","last_updated":"2024-09-13T19:42:12Z","latest_version":2,"primary_category":"q-fin.CP","snapshot_observed_at":"2026-08-10T12:32:19.829238Z","submitted_at":"2024-09-04T19:00:59Z","title":"MoA is All You Need: Building LLM Research Team using Mixture of Agents"},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.07487."}