{"as_of":"2026-08-07T04:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:71976f5470d47793b62af7a7c21e745e53636a06c013a6494a9fc244c06f49e6","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":"2026-08-06T18:16:08.381912Z","state":"measured"},{"denominator":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-06T06:34:29.942622+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-29T00:12:48.423147Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"cited_work":{"arxiv_id":"2507.08944","doi":"10.48550/arxiv.2507.08944","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.08944","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2507.08944 , year =","venue":"ArXiv.org","work_id":"3dde02ea-4e91-4fe7-b1cb-490a6c798f7b","year":2025},"citing_paper":{"arxiv_id":"2510.05307","last_updated":"2026-05-07T15:51:04Z","snapshot_observed_at":"2026-07-06T22:31:53.944103Z","submitted_at":"2025-10-06T19:18:56Z","title":"When Should Users Check? Modeling Confirmation Frequency inMulti-Step Agentic AI Tasks","version":3},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-05-18T08:59:35.944554Z"},"links":{"cited_paper":"/paper/2507.08944","citing_paper":"/paper/2510.05307"},"observation_digest":"sha256:1049952b9b5acf07d4bf067eff8c365260243c20c859024cfba48d46ea5bb1d4","observation_id":"53d3b4bb-d02a-4f99-861c-4b8c48d644c4","resolution":{"observed_at":"2026-05-18T09:01:08.858810Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"cited_work":{"arxiv_id":"2507.08944","doi":"10.48550/arxiv.2507.08944","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.08944","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2507.08944 , year =","venue":"ArXiv.org","work_id":"3dde02ea-4e91-4fe7-b1cb-490a6c798f7b","year":2025},"citing_paper":{"arxiv_id":"2605.14892","last_updated":"2026-05-15T09:12:41Z","snapshot_observed_at":"2026-08-05T08:21:06.172969Z","submitted_at":"2026-05-14T14:36:13Z","title":"Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems","version":1},"reference_index":274,"source":"arxiv_source","source_observed_at":"2026-05-15T03:07:38.232966Z"},"links":{"cited_paper":"/paper/2507.08944","citing_paper":"/paper/2605.14892"},"observation_digest":"sha256:781e8637942c2660596d735208497c0b2efa56fbc54e282553428fa86c499055","observation_id":"01c8491e-d295-4648-b67d-6fab800cf801","resolution":{"observed_at":"2026-05-15T03:08:58.203209Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"cited_work":{"arxiv_id":"2507.08944","doi":"10.48550/arxiv.2507.08944","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.08944","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2507.08944 , year =","venue":"ArXiv.org","work_id":"3dde02ea-4e91-4fe7-b1cb-490a6c798f7b","year":2025},"citing_paper":{"arxiv_id":"2605.14892","last_updated":"2026-05-15T09:12:41Z","snapshot_observed_at":"2026-08-05T08:21:06.172969Z","submitted_at":"2026-05-14T14:36:13Z","title":"Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems","version":2},"reference_index":275,"source":"arxiv_source","source_observed_at":"2026-05-19T16:51:13.491389Z"},"links":{"cited_paper":"/paper/2507.08944","citing_paper":"/paper/2605.14892"},"observation_digest":"sha256:f7bd7bfdfb0e55631399bb8c236b7fe033daad6df30c20686f8f7170ed6cbb2a","observation_id":"c9096a56-0982-4741-bcf4-c038cf674881","resolution":{"observed_at":"2026-05-19T16:52:40.003937Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"cited_work":{"arxiv_id":"2507.08944","doi":"10.48550/arxiv.2507.08944","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.08944","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2507.08944 , year =","venue":"ArXiv.org","work_id":"3dde02ea-4e91-4fe7-b1cb-490a6c798f7b","year":2025},"citing_paper":{"arxiv_id":"2605.29612","last_updated":"2026-05-28T08:47:54Z","snapshot_observed_at":"2026-08-01T18:44:32.288068Z","submitted_at":"2026-05-28T08:47:54Z","title":"CONCAT: Consensus- and Confidence-Driven Ad Hoc Teaming for Efficient LLM-Based Multi-Agent Systems","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-06-29T00:12:48.423147Z"},"links":{"cited_paper":"/paper/2507.08944","citing_paper":"/paper/2605.29612"},"observation_digest":"sha256:28fbe576b67e4bdf5600a05995bbb6c93d90296f49d0e7bb700242bfa51e2faa","observation_id":"db7f943d-00a1-459b-9086-0f215cfe336a","resolution":{"observed_at":"2026-06-29T00:22:51.407535Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.08944/citation-record","integrity":"/paper/2507.08944/integrity","json":"/paper/2507.08944/citation-record.json","paper":"/paper/2507.08944"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2401.04088","last_updated":"2024-01-08T18:47:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-01-08T18:47:34Z","title":"Mixtral of Experts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.04088","snapshot_observed_at":"2026-08-06T18:16:07.401166Z","title":"Q., Sablayrolles, A., Roux, A., Mensch, A., Savary, B., Bamford, C., Chaplot, D","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:07.401166Z"},"links":{"cited_paper":"/paper/2401.04088","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:20397459a76fbdf90700877ea8ff3f5af313b825191de3cce5802b9c36fa71fb","observation_id":"d20db80c-680d-47bc-bb0a-b65fee80d20b","resolution":{"observed_at":"2026-08-06T18:16:07.401166Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.05950","last_updated":"2023-10-04T01:53:15Z","snapshot_observed_at":"2026-08-06T11:01:07.280829Z","submitted_at":"2022-08-11T17:41:08Z","title":"Interactive Code Generation via Test-Driven User-Intent Formalization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.05950","snapshot_observed_at":"2026-08-06T18:16:07.497407Z","title":"K., Naik, A., Sakkas, G., Choudhury, P., von Veh, C., Musuvathi, M., Inala, J","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:07.497407Z"},"links":{"cited_paper":"/paper/2208.05950","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:bfa38a6189091c5972834c383b0662146a2b0320cc81e7d16450de7a530eb91c","observation_id":"165dbbe9-9212-4c52-bbe3-e20dc0d0055d","resolution":{"observed_at":"2026-08-06T18:16:07.497407Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.07814","last_updated":"2022-02-08T23:16:31Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-02-08T23:16:31Z","title":"Competition-Level Code Generation with AlphaCode","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.07814","snapshot_observed_at":"2026-08-06T18:16:07.638447Z","title":"H., Chung, J., Kushman, N., Schrit- twieser, J., Leblond, R., Eccles, T., Keeling, J., Gi- meno, F., Lago, A","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:07.638447Z"},"links":{"cited_paper":"/paper/2203.07814","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:30dfc8a6af666954b1988da669cf9c131f53f92a5aac3e5428d7686c8fb08f4f","observation_id":"494f2503-53e6-4123-89c6-e054ad4e07df","resolution":{"observed_at":"2026-08-06T18:16:07.638447Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.07814","last_updated":"2022-02-08T23:16:31Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-02-08T23:16:31Z","title":"Competition-Level Code Generation with AlphaCode","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.07814","snapshot_observed_at":"2026-08-06T18:16:07.713872Z","title":"URL https: //doi.org/10.48550/arXiv.2203.07814","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:07.713872Z"},"links":{"cited_paper":"/paper/2203.07814","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:3c0ad4f75f7863f5fadfd848ee613870454148108f23887602672023570faa64","observation_id":"5436ed05-784e-4e37-addb-852ae0809229","resolution":{"observed_at":"2026-08-06T18:16:07.713872Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.07088","last_updated":"2024-02-23T20:35:30Z","snapshot_observed_at":"2026-07-06T16:30:50.253688Z","submitted_at":"2023-10-11T00:01:41Z","title":"Diversity of Thought Improves Reasoning Abilities of LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.07088","snapshot_observed_at":"2026-08-06T18:16:07.841509Z","title":"Ning, X., Lin, Z., Zhou, Z., Wang, Z., Yang, H., and Wang, Y","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:07.841509Z"},"links":{"cited_paper":"/paper/2310.07088","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:f7cae7e782316c7da8ea4ff427a0994479a2b9c89a976583513fecdd81a42a1f","observation_id":"60c40728-0570-408f-a273-2e2793668043","resolution":{"observed_at":"2026-08-06T18:16:07.841509Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.03733","last_updated":"2024-10-18T23:53:07Z","snapshot_observed_at":"2026-07-06T19:11:09.921186Z","submitted_at":"2024-09-05T17:44:49Z","title":"Planning In Natural Language Improves LLM Search For Code Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.03733","snapshot_observed_at":"2026-08-06T18:16:07.971713Z","title":"Planning in natural language improves llm search for code gen- eration, 2024a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:07.971713Z"},"links":{"cited_paper":"/paper/2409.03733","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:55122c36f9d571d2717ec97df67046273dfdd87a53ba278f146ef9b48f7a9816","observation_id":"957e30f5-1a50-4be3-9197-b80b6e3d36b2","resolution":{"observed_at":"2026-08-06T18:16:07.971713Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.04692","last_updated":"2024-06-07T07:04:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-06-07T07:04:10Z","title":"Mixture-of-Agents Enhances Large Language Model Capabilities","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.04692","snapshot_observed_at":"2026-08-06T18:16:08.035362Z","title":"Mixture-of-agents enhances large language model capabilities","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:08.035362Z"},"links":{"cited_paper":"/paper/2406.04692","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:d7989d789ff6371618488400640d18d10873e49232ace6595c09099dd72b88f5","observation_id":"fb1283e5-f510-4d37-988a-0cfec6dea89d","resolution":{"observed_at":"2026-08-06T18:16:08.035362Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.08155","last_updated":"2023-10-03T20:47:10Z","snapshot_observed_at":"2026-07-31T19:03:03.494918Z","submitted_at":"2023-08-16T05:57:52Z","title":"AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.08155","snapshot_observed_at":"2026-08-06T18:16:08.182092Z","title":"Un- leashing the emergent cognitive synergy in large language models: A task-solving agent through multi-persona self- collaboration","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:08.182092Z"},"links":{"cited_paper":"/paper/2308.08155","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:8e82098928afd264fce3242f43cd1bcdea3e91cba33b798377b32ee69d5986a3","observation_id":"40aa0b32-ba10-45af-84a7-000bf8a21fcf","resolution":{"observed_at":"2026-08-06T18:16:08.182092Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.01005","last_updated":"2025-04-21T20:10:11Z","snapshot_observed_at":"2026-07-06T20:15:36.280948Z","submitted_at":"2025-01-02T02:02:20Z","title":"FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.01005","snapshot_observed_at":"2026-08-06T18:16:08.381912Z","title":"Zhang, E., Sullivan, N., Haynes, B., Krishna, R., and Bal- azinska, M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:08.381912Z"},"links":{"cited_paper":"/paper/2501.01005","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:97a4717b4292a6f20628655afb9a83071c2094479966c6210ef4b1956190f86c","observation_id":"d28156b6-6f05-4d74-bd6d-7c5ed56f5370","resolution":{"observed_at":"2026-08-06T18:16:08.381912Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-07T01:45:38.840969Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-06T18:16:07.257912Z","title":"Dao, T., Fu, D","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:07.257912Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:cfbd0baf4e545cc77a3270833adb7609a5b3e08ac70934cb4bebbde64fd276d1","observation_id":"e9409660-f924-4733-b7b6-40ad4e116b3f","resolution":{"observed_at":"2026-08-06T18:16:07.257912Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.05950","last_updated":"2023-10-04T01:53:15Z","snapshot_observed_at":"2026-08-06T11:01:07.280829Z","submitted_at":"2022-08-11T17:41:08Z","title":"Interactive Code Generation via Test-Driven User-Intent Formalization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.05950","snapshot_observed_at":"2026-08-06T18:16:07.573958Z","title":"URL https://doi","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:07.573958Z"},"links":{"cited_paper":"/paper/2208.05950","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:c723b2fc8d019454ffc3a183d10c39d03e3a543d28f073e1670d8c984ec749b5","observation_id":"2e83699c-9f70-4118-8a21-9df1ad7760d6","resolution":{"observed_at":"2026-08-06T18:16:07.573958Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.15364","last_updated":"2024-10-20T11:40:31Z","snapshot_observed_at":"2026-08-06T17:53:01.500247Z","submitted_at":"2024-10-20T11:40:31Z","title":"Scene Graph Generation with Role-Playing Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.15364","snapshot_observed_at":"2026-08-06T18:16:07.119084Z","title":"Scene graph genera- tion with role-playing large language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:07.119084Z"},"links":{"cited_paper":"/paper/2410.15364","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:1580447ac2c3dd8843590ce613e6d4475ea9abdd28744ec3b0922f4b3f118e7b","observation_id":"d308fd2c-7f0f-43e6-8655-0543706b364d","resolution":{"observed_at":"2026-08-06T18:16:07.119084Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04468","last_updated":"2024-11-07T06:36:19Z","snapshot_observed_at":"2026-08-04T17:52:28.620519Z","submitted_at":"2024-11-07T06:36:19Z","title":"Magentic-One: A Generalist Multi-Agent System for Solving Complex Tasks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04468","snapshot_observed_at":"2026-08-06T18:16:07.343518Z","title":"Guo, T., Guo, K., Nan, B., Liang, Z., Guo, Z., Chawla, N","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:07.343518Z"},"links":{"cited_paper":"/paper/2411.04468","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:4cae88d6acd3a4931804009dbca49582975554a6dd3f1157299c4dd9a7028b5c","observation_id":"de73f55a-8210-4078-9d3b-2cb71fc9e25d","resolution":{"observed_at":"2026-08-06T18:16:07.343518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21787","last_updated":"2024-12-30T19:03:24Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:57:25Z","title":"Large Language Monkeys: Scaling Inference Compute with Repeated Sampling","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21787","snapshot_observed_at":"2026-08-06T18:16:07.050301Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-06T18:16:07.050301Z"},"links":{"cited_paper":"/paper/2407.21787","citing_paper":"/paper/2507.08944"},"observation_digest":"sha256:bb5e5ad0d91070a6a0441e26bbd92a9a271b63456ea4927e551eff9dd062b71d","observation_id":"b5217b81-e7ee-4f5e-ba56-2521a5436d6c","resolution":{"observed_at":"2026-08-06T18:16:07.050301Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.08944","last_updated":"2025-07-11T18:09:22Z","latest_version":1,"primary_category":"cs.MA","snapshot_observed_at":"2026-08-06T18:06:17.826841Z","submitted_at":"2025-07-11T18:09:22Z","title":"Optimizing Sequential Multi-Step Tasks with Parallel LLM Agents"},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 4 inbound Pith citation observations for arXiv:2507.08944."}