{"as_of":"2026-08-12T13:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9b74babed1b7df41fee7bcad027d44765987b286407835d20cee301299895b87","coverage":[{"denominator":14,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":14,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T05:47:25.771298Z","state":"measured"},{"denominator":17,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":17,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+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":"2026-07-13T11:58:11.319217Z","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":"2026-05-23T17:35:43.864558Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"cited_work":{"arxiv_id":"2412.17149","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.17149","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A multi-ai agent system for autonomous optimization of agentic ai solutions via iterative refinement and llm-driven feedback loops","venue":null,"work_id":"7b2b741e-dc58-4e32-8032-4b28de0da93a","year":2024},"citing_paper":{"arxiv_id":"2411.15594","last_updated":"2025-10-19T10:32:43Z","snapshot_observed_at":"2026-08-02T10:23:50.881300Z","submitted_at":"2024-11-23T16:03:35Z","title":"A Survey on LLM-as-a-Judge","version":6},"reference_index":201,"source":"pdf_text","source_observed_at":"2026-05-23T17:33:13.394338Z"},"links":{"cited_paper":"/paper/2412.17149","citing_paper":"/paper/2411.15594"},"observation_digest":"sha256:373d1f98ed3c427911b45dc183020364427160b579fe0d65deff4097edc3c376","observation_id":"2574e3ca-5520-4400-8517-2c96421be459","resolution":{"observed_at":"2026-05-23T17:35:43.866874Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"cited_work":{"arxiv_id":"2412.17149","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.17149","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A multi-ai agent system for autonomous optimization of agentic ai solutions via iterative refinement and llm-driven feedback loops","venue":null,"work_id":"7b2b741e-dc58-4e32-8032-4b28de0da93a","year":2024},"citing_paper":{"arxiv_id":"2603.09002","last_updated":"2026-04-26T14:13:48Z","snapshot_observed_at":"2026-08-11T02:37:54.478569Z","submitted_at":"2026-03-09T22:46:27Z","title":"Security Considerations for Multi-agent Systems","version":2},"reference_index":210,"source":"pdf_text","source_observed_at":"2026-05-15T14:12:14.160789Z"},"links":{"cited_paper":"/paper/2412.17149","citing_paper":"/paper/2603.09002"},"observation_digest":"sha256:cf9495736d010b2b82221c2020f08d90e4209ff0cc157dd552d434d6373668a3","observation_id":"03f04f47-e4c6-45eb-b5aa-6345b1bfac17","resolution":{"observed_at":"2026-05-15T14:15:55.992072Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.17149","snapshot_observed_at":"2026-07-13T11:58:11.319217Z","title":"https://doi.org/10.48550/arXiv.2412.17149","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2604.03926","last_updated":"2026-04-05T01:37:53Z","snapshot_observed_at":"2026-08-07T06:42:44.358490Z","submitted_at":"2026-04-05T01:37:53Z","title":"CODE-GEN: A Human-in-the-Loop RAG-Based Agentic AI System for Multiple-Choice Question Generation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-13T11:58:11.319217Z"},"links":{"cited_paper":"/paper/2412.17149","citing_paper":"/paper/2604.03926"},"observation_digest":"sha256:69a57ba9257ae1ccd37c3d271d2b771aaf8233b809c4ed85bfcd21a3b889d9f1","observation_id":"b155e3f2-b548-4388-9193-76e6f87b1722","resolution":{"observed_at":"2026-07-13T11:58:11.319217Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2412.17149/citation-record","integrity":"/paper/2412.17149/integrity","json":"/paper/2412.17149/citation-record.json","paper":"/paper/2412.17149"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:25.700143Z","title":"online\" 'onlinestring :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.700143Z"},"links":{"citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:fccd0070b9821ba4174be04a907039d805940de4ccea24ec25391bda2f6e8008","observation_id":"59fd81f1-de03-4dbb-ad9d-508029775403","resolution":{"observed_at":"2026-08-11T05:47:25.700143Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:25.706424Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.706424Z"},"links":{"citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:0c6c192f1c967cf78c2cdab3f34132f4672dd88fa07d5870f088be228863d8aa","observation_id":"83fa7cd9-e609-478f-8d5d-604199c9e842","resolution":{"observed_at":"2026-08-11T05:47:25.706424Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.08435","last_updated":"2025-03-02T05:13:28Z","snapshot_observed_at":"2026-08-06T11:45:45.286982Z","submitted_at":"2024-08-15T21:59:23Z","title":"Automated Design of Agentic Systems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.08435","snapshot_observed_at":"2026-08-11T05:47:25.711971Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.711971Z"},"links":{"cited_paper":"/paper/2408.08435","citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:b9ceaff0ac7d451352d6cf1a76604d6574dd2c5a95b3ebd3e067f1a61892b84b","observation_id":"998198a4-b478-478d-8614-274fa82680b1","resolution":{"observed_at":"2026-08-11T05:47:25.711971Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:25.988106Z","title":null,"venue":null,"work_id":"29036b8a-77e1-4749-a630-7b18ab591106","year":2024},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.717388Z"},"links":{"citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:2a0fa9021b4eecbb27d912e712490bb34d7892f7d2cc721cea0798b1e2a58480","observation_id":"cce98787-741b-4933-91ed-85e7c0555f58","resolution":{"observed_at":"2026-08-11T05:47:25.993647Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:25.971739Z","title":null,"venue":null,"work_id":"2f6b6ffa-4f35-42e4-b3ca-c1296e060e57","year":2023},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.723585Z"},"links":{"citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:8943647eed09aad79ea7cea000a2631ba388862c53723af18c2cd5ff59247819","observation_id":"36c952e7-55aa-45ed-a608-519b07d73c8a","resolution":{"observed_at":"2026-08-11T05:47:25.976711Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.11584","last_updated":"2024-04-17T17:32:41Z","snapshot_observed_at":"2026-08-04T23:37:27.678120Z","submitted_at":"2024-04-17T17:32:41Z","title":"The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.11584","snapshot_observed_at":"2026-08-11T05:47:25.728481Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.728481Z"},"links":{"cited_paper":"/paper/2404.11584","citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:6df021b650677ae2ee61ba3c6289f95486d658c0373e805b41dc0f884d87794a","observation_id":"80cf0cd6-4cec-4b58-a3e8-2a6dd9e145e9","resolution":{"observed_at":"2026-08-11T05:47:25.728481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:25.955977Z","title":null,"venue":null,"work_id":"1bde7eed-33c8-4d6b-a32f-6625b35271af","year":2024},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.733788Z"},"links":{"citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:ff12ba9c87096e5d654a38f1eca076e5863eb21996845e6d1920fdde96ea1bef","observation_id":"b583745f-9921-494d-a6d7-0f89d74697c4","resolution":{"observed_at":"2026-08-11T05:47:25.960806Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.03502","last_updated":"2024-07-03T21:01:12Z","snapshot_observed_at":"2026-08-10T23:24:12.708652Z","submitted_at":"2024-07-03T21:01:12Z","title":"AgentInstruct: Toward Generative Teaching with Agentic Flows","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.03502","snapshot_observed_at":"2026-08-11T05:47:25.739286Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.739286Z"},"links":{"cited_paper":"/paper/2407.03502","citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:44d85c12c5d13630b7551a156ae6b91f815b8e365e349e8fac181c880152347a","observation_id":"9968fb31-5f08-4fdb-a3ae-4f850efc3636","resolution":{"observed_at":"2026-08-11T05:47:25.739286Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.06627","last_updated":"2024-06-06T21:39:09Z","snapshot_observed_at":"2026-08-10T08:42:26.735412Z","submitted_at":"2024-02-09T18:59:29Z","title":"Feedback Loops With Language Models Drive In-Context Reward Hacking","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.06627","snapshot_observed_at":"2026-08-11T05:47:25.745361Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.745361Z"},"links":{"cited_paper":"/paper/2402.06627","citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:1a3fcdaa878f48210a5288371ff758525411376846015a0ae960b33bcc16bb80","observation_id":"cafc8b8c-707b-4662-a46b-89424dff79a9","resolution":{"observed_at":"2026-08-11T05:47:25.745361Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:25.939885Z","title":null,"venue":null,"work_id":"fdade0af-cc35-4965-9566-9967785131c5","year":2024},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.750973Z"},"links":{"citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:15c767d3f53ada51752e4c03f196548cd4c5e65d62b31c20a0e0bf85b244f239","observation_id":"9b700709-b1b5-48e2-9dfd-1626f6d547c1","resolution":{"observed_at":"2026-08-11T05:47:25.944866Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:25.924069Z","title":null,"venue":null,"work_id":"978c0b55-fc38-46fd-8bf2-db4f1af6610a","year":2023},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.756154Z"},"links":{"citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:c4c8abe41f7cc6c3455a0ed48860836da3b5eb658e6bf780a01e70dfb6ffaaf0","observation_id":"7e0e2c1b-4ae5-47e5-a7fe-dfc8816384d2","resolution":{"observed_at":"2026-08-11T05:47:25.928829Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.06336","last_updated":"2025-09-02T19:53:40Z","snapshot_observed_at":"2026-08-04T22:44:17.785568Z","submitted_at":"2024-09-10T08:47:23Z","title":"Towards Agentic AI on Particle Accelerators","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.06336","snapshot_observed_at":"2026-08-11T05:47:25.760998Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.760998Z"},"links":{"cited_paper":"/paper/2409.06336","citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:1cf70e0e6ca5a0198936fec5c1c0ef38f484bc0602e65b63d738200f596de16c","observation_id":"baf5501d-c5e7-4c35-8c76-e6fff3a3da75","resolution":{"observed_at":"2026-08-11T05:47:25.760998Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:47:25.906371Z","title":null,"venue":null,"work_id":"3f4b5f33-d3d4-47a8-9ee3-596af7bfce34","year":2024},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.766385Z"},"links":{"citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:9f1c33205ab41d627117ab50911c68eae9fe2eecbb5a1b48ae3e7d33156d0ea2","observation_id":"2f4ab687-9a3c-4292-a9cb-7fa7ba44bdfa","resolution":{"observed_at":"2026-08-11T05:47:25.912552Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02052","last_updated":"2025-02-27T20:13:19Z","snapshot_observed_at":"2026-08-09T14:28:14.551525Z","submitted_at":"2024-10-02T21:42:35Z","title":"ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02052","snapshot_observed_at":"2026-08-11T05:47:25.771298Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-11T05:47:25.771298Z"},"links":{"cited_paper":"/paper/2410.02052","citing_paper":"/paper/2412.17149"},"observation_digest":"sha256:476087f9d49e53b889f40a47c5ce130d7c2ae49d03d83b6ca4d1e276eb455293","observation_id":"315bd876-a5fd-4726-9ff1-3db28bed851b","resolution":{"observed_at":"2026-08-11T05:47:25.771298Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.17149","last_updated":"2024-12-22T20:08:04Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-11T21:15:02.457765Z","submitted_at":"2024-12-22T20:08:04Z","title":"A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops"},"reference_resolution":{"displayed":14,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":14},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 3 inbound Pith citation observations for arXiv:2412.17149."}