{"as_of":"2026-08-02T15:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a43d6f4f61db190a25851f34500d419955db62d8a8a795ac76edc0b6fb6bab4a","coverage":[{"denominator":66,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":66,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T17:24:16.645107Z","state":"measured"},{"denominator":67,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":67,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-02T06:30:47.504484+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":"2026-07-14T07:51:15.549754Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.02162","snapshot_observed_at":"2026-07-14T07:51:15.549754Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.10987","last_updated":"2026-07-13T01:19:13Z","snapshot_observed_at":"2026-08-02T08:08:42.284530Z","submitted_at":"2026-07-13T01:19:13Z","title":"[AAFLOW+] Stateful Operator Abstraction with Zero-Copy Distributed KV Cache Orchestration for Multi-Agent Workflows","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-14T07:51:15.549754Z"},"links":{"cited_paper":"/paper/2605.02162","citing_paper":"/paper/2607.10987"},"observation_digest":"sha256:e2d42f0e011815cce507449dbfaacea439288fb0260efadac1165dd06c991a64","observation_id":"d5911a16-d20f-42be-893d-7cf1418649ae","resolution":{"observed_at":"2026-07-14T07:51:15.549754Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2605.02162/citation-record","integrity":"/paper/2605.02162/integrity","json":"/paper/2605.02162/citation-record.json","paper":"/paper/2605.02162"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2508.20737","last_updated":"2025-08-28T13:00:28Z","snapshot_observed_at":"2026-07-06T22:20:02.908814Z","submitted_at":"2025-08-28T13:00:28Z","title":"Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol","version":1},"cited_work":{"arxiv_id":"2508.20737","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.20737","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Rethinking testing for llm applications: Characteristics, challenges, and a lightweight interaction protocol","venue":null,"work_id":"5737fa8b-da86-477a-b77c-2e861fde50b6","year":2025},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"cited_paper":"/paper/2508.20737","citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:cd586ab60bbf0a247f4c15713322ffac83abd0b7822f16fda4d848ab8797698c","observation_id":"6262d467-f1b4-4798-9d3d-e3fe8c67f793","resolution":{"observed_at":"2026-05-11T17:36:06.490183Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"What is llamaindex ?","venue":null,"work_id":"b3407d96-5def-4c6b-9edd-b79dee8b2f13","year":null},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:31d72ead3e5b500d44689b91d832525f71aac9215834ec1e964481eb05ab0a3d","observation_id":"603f6c06-1d20-4ab2-a273-83c3beb31ce9","resolution":{"observed_at":"2026-05-26T07:56:54.657602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Available: https://www .ibm.com/think/topics/llamaindex","venue":null,"work_id":"cf644ed1-aa08-4d33-95cd-c19916f4ba22","year":null},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:b761cb1c81379abe1e11c7431ff75339ff300cecfc789c287a8307f783b55c63","observation_id":"d2e91725-a3c2-495c-868e-932a121b5928","resolution":{"observed_at":"2026-05-26T07:56:54.661268Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Optimize vector databases, enhance rag-driven generative ai","venue":null,"work_id":"a6d347c1-536e-4b48-91d5-d766cd7ae789","year":2024},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:ff4a891fc46613e601e200f39c1fbbaccedbc79957eec576e76cd69041ea5e13","observation_id":"91a8a50e-253c-42be-bd93-82ff3d74526e","resolution":{"observed_at":"2026-05-26T07:56:54.653788Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Performance comparison of dask and apache spark on hpc systems for neuroimaging","venue":null,"work_id":"1c37f8f2-0f6b-4e1f-b18b-9f32a482a152","year":null},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:a201da593218d21ac5210e328176c0267e68b64498333ae7e883306fa7b999b3","observation_id":"7fc1bd7e-965c-4758-993f-cab7612d942f","resolution":{"observed_at":"2026-05-26T07:56:54.649609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1002/cpe.7635","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Available: https://doi.org/10.1002/cpe.7635","venue":null,"work_id":"8f1d291a-8dff-4ed7-9995-4a6a028f1c89","year":null},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:cad453bd9f955498ea0deacf003062262643f8bb3c1de4cd4ec6686b1647b917","observation_id":"8e859c01-4cf2-4763-a206-dfb489719790","resolution":{"observed_at":"2026-05-08T20:09:07.583401Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.16676","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T11:08:03.239160Z","title":"Dataflow: An llm-driven framework for unified data preparation and workflow automation in the era of data-centric ai","venue":null,"work_id":"9e62ea65-b553-4785-bdcc-233ea04c38e5","year":2025},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:7836d2df311afc3c77aaac92957a353a647567a7df304f008831d89bdbc6df4e","observation_id":"f32512f5-d847-4cc6-950d-539677446af2","resolution":{"observed_at":"2026-05-11T17:36:06.485772Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"High performance dataframes from parallel processing patterns","venue":null,"work_id":"891be35d-5964-4727-a53e-6990c2027a0d","year":2022},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:80b349fd6568e67456f94610585c765e32175232039c38ea02fff98b3636fc2a","observation_id":"1a94449e-6bd3-41ce-a491-c87e08021c78","resolution":{"observed_at":"2026-05-26T07:56:54.554630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2509.18869","doi":"10.48550/arxiv.2509.18869","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T12:15:01.137692Z","title":"On the reproducibility limitations of rag systems","venue":null,"work_id":"954e0fcc-30b0-4438-8747-1c2963632c9c","year":2025},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:6a5193b429f6c841dd88b319438f6208b06df2e4078805684dd084b6aa52c3ae","observation_id":"cd01f63f-109f-4066-8059-b2496dd2be30","resolution":{"observed_at":"2026-05-08T20:09:07.560896Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Simplify your rag application architecture with llamain- dex + postgresml","venue":null,"work_id":"1105945f-1012-4d0d-a9de-34019f1f1877","year":2025},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:4d027bc8f4bc183356a5864376195e9a63ae0d199708278a3a556f61c48d26e3","observation_id":"e17e47d4-fe0d-4767-b934-13f294a16087","resolution":{"observed_at":"2026-05-26T07:56:54.595294Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"How to achieve 10x perfor- mance with vector database for llm using lancedb and pyarrow","venue":null,"work_id":"46fa21e9-c741-410d-bfea-8c762c7dc052","year":2025},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:7ac8b23e3b4ca79fb340c8b450d20b826fe359a377a61b3e3b1033f38ad7f637","observation_id":"693eea7e-97f7-401e-b5dd-c2bd31ca3663","resolution":{"observed_at":"2026-05-26T07:56:54.575272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/works56498.2022.00009","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T18:15:00.863488Z","title":"Radical-pilot and parsl: Executing heterogeneous workflows on hpc platforms","venue":null,"work_id":"a381b345-c535-41bc-a050-9c647e612e9e","year":2022},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:b4f1a93e87b9d77150b266d919bfd5e832d34d326db3cffab78566e8834c67d9","observation_id":"9701daf8-5f69-4174-9897-e6c62996eadd","resolution":{"observed_at":"2026-05-08T20:09:07.531372Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Retrieval-augmented generation for knowledge-intensive nlp tasks","venue":null,"work_id":"9b512c8d-9fd3-41eb-b42d-8c9a0eff165f","year":2020},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:bccee2816dcf4de058ca195d0b24477aa1e48b9c1c639b6c7177aadeddde2621","observation_id":"e90ae3a1-4996-44b6-8e2f-027102faa289","resolution":{"observed_at":"2026-05-26T07:56:54.558854Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"React: Synergizing reasoning and acting in language models","venue":null,"work_id":"156a7018-b3af-49a4-87e4-3b18029a4bd0","year":null},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:00fb6a68abcd1d4fe2de07e6d979e21af755fcbc17053f27a8e6a7cf7f65b518","observation_id":"3141fca8-44ef-4223-921a-f2ce7a259fa8","resolution":{"observed_at":"2026-05-26T07:56:54.544614Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Available: https://openreview .net/pdf?id=WE_vluYUL-X","venue":null,"work_id":"d4711dd6-5b85-449b-a833-e3abc08a959c","year":null},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:989942e4bef4ef3f967f14b9f8f2e434f2b736dc2a52da158123abc70d3868e1","observation_id":"2e33a63c-ed40-4b04-9e41-d48a6f19e2ee","resolution":{"observed_at":"2026-05-26T07:56:54.614791Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.5555/3666122.3666499","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T12:15:01.137692Z","title":"Reflexion: language agents with verbal reinforcement learning","venue":null,"work_id":"cfe341ef-c37a-41b7-abdb-303677ab422b","year":2023},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:2b002a42bfbfc0533c8e439603853d05beb63d21dba7a965d3445b48a5dd2c86","observation_id":"534b5295-dec5-4e79-8653-9c7dba8c6809","resolution":{"observed_at":"2026-05-08T20:09:07.435990Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-07-14T16:20:06.63707+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T16:20:06.63707+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Retrieval-augmented generation for knowledge-intensive nlp tasks","venue":null,"work_id":"f23c37e3-996f-444e-8af0-0f698128beca","year":2020},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:3ea183c25985161ed47ed98cda3d483ccf8351c7a066c961a14a3a8de72261c9","observation_id":"5b2f3097-de55-449f-bcac-ccf0ccbaa1db","resolution":{"observed_at":"2026-05-08T20:09:07.486238Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/pic.2014.6972327","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T12:15:00.875560Z","title":"Accelerating embarrassingly parallel algorithm on intel mic","venue":null,"work_id":"8c65473c-18c7-4b5c-8556-073cca9e0879","year":2014},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:06d48029b4df363e7d5954035adbd20b6daa96a05fe54719e0dfc77c61b152e3","observation_id":"1922bd65-37fd-4c8e-8b03-9b019fb90a8c","resolution":{"observed_at":"2026-05-08T20:09:07.409941Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/hoti.2015.13","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ucx: An open source framework for hpc network apis and beyond","venue":null,"work_id":"43a63b9a-2ef2-46b6-80e1-be27d2e891a6","year":2015},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:34552be41b1b4d1eca8b52d1e32845eb3e77d0c90eaf7f01c346f98553610aab","observation_id":"e529c97d-c691-4ce6-88eb-f7e722c695c3","resolution":{"observed_at":"2026-05-08T20:09:07.524461Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-07-14T16:20:06.126561+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T16:20:06.126561+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.jpdc.2005.03.010","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-02T07:16:44.358079Z","title":"Mpi for python","venue":null,"work_id":"54c1fd5a-d409-446e-a042-ca74e5f246cf","year":2005},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:57b44e989964b7298fea568244278bdb762c2842b40f1df9fa1c622468404d74","observation_id":"fbba8747-4463-4c5a-a855-6b0982b201ad","resolution":{"observed_at":"2026-05-08T20:09:07.421229Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/smds49396.2020.00022","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T12:15:00.875560Z","title":"High performance data engineering everywhere","venue":null,"work_id":"a3402362-cfb6-4c34-af13-c50b4516006b","year":2020},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:f207f838f055b2ebc67ba8d90e7f117e32d42b4c68b759f4be4d037e52bca3d9","observation_id":"fa26aa9c-61d2-4586-9005-13954dd1419e","resolution":{"observed_at":"2026-05-08T20:09:07.516690Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-07-14T16:20:06.92978+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T16:20:06.92978+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.future.2023.07.007","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"In-depth analysis on parallel processing patterns for high-performance dataframes","venue":null,"work_id":"ab2dcceb-829d-4d73-8ea3-721cc2d26f1e","year":2023},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:db22f3073d074858736cc5139524420cd84dfd3a950eb4846c0d3b9d78de00aa","observation_id":"b937d7ef-4a9c-4bd5-b50d-da2b60251d6e","resolution":{"observed_at":"2026-05-08T20:09:07.472345Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-07-14T16:20:04.94262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T16:20:04.94262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-032-10507-3_11","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep rc: A scalable data engineering and deep learning pipeline","venue":null,"work_id":"2e0f5720-bd84-461d-a786-92edc962480e","year":2025},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:bb5aaba8b64cc3672bf3045ed35931c00c96927c3940785ef98d0b51c07ee070","observation_id":"9562d67f-d484-4f8a-bd34-3f683431628d","resolution":{"observed_at":"2026-05-08T20:09:07.567449Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-07-14T16:20:05.604099+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T16:20:05.604099+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2512.20795","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Available: https://arxiv.org/abs/2512.20795","venue":null,"work_id":"7eebdf9e-8160-4e50-bcdc-78b8744e8098","year":null},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:24aea0532208d3a48ac269f8801c4d5433bc79e3f4ca235228a45e235d9275c5","observation_id":"fc648be5-08e4-4e29-bb7e-909d19eba904","resolution":{"observed_at":"2026-05-11T17:36:06.477810Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Architecture","venue":null,"work_id":"74e10698-e5b0-4ed2-8651-a1c53536c278","year":2022},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:9f6c9373f2a290036c53c56acc819752e7f11cbad0321e8f77cb847f5585fa2a","observation_id":"b4ee0b3c-a5f5-43a7-862c-5ba6427b0bd8","resolution":{"observed_at":"2026-05-26T07:56:54.567576Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-031-74430-3_5","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Radical-cylon: A heterogeneous data pipeline for scientific computing","venue":null,"work_id":"db9b405c-95ba-4d47-9d32-cee6b1508417","year":2024},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:c335655bdd85b42a52f05026f5d6bd3c0466ff91fb277ea97b5f0b319d114794","observation_id":"a3b0eb5c-23f8-4e52-8719-0742f24da22b","resolution":{"observed_at":"2026-05-08T20:09:07.509586Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-07-14T16:20:05.879417+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T16:20:05.879417+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1109/tpds.2021.3105994","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T12:15:00.875560Z","title":"Design and performance characterization of radical-pilot on leadership-class platforms","venue":null,"work_id":"6e5f0d05-6b8b-49ce-abb4-151f545a92f0","year":2022},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:311bc2e02bc2f3c3617438106892246d10f8039422c72b7fa4195dc75e3fbdb7","observation_id":"242511ea-4629-476f-b3cd-743f91e9696e","resolution":{"observed_at":"2026-05-08T20:09:07.492159Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-07-14T16:20:04.372297+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T16:20:04.372297+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Gloo: Collective communications library with various primitives for multi-machine training","venue":null,"work_id":"846d7f6e-1f6b-4c3d-a148-64b1cd003b3a","year":2023},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:931d4f3593792fd4e6dda588691a9f4035bf08fb97b3cfba359949202fb705bb","observation_id":"4f767713-36f3-4708-8991-4b8a1cdfec47","resolution":{"observed_at":"2026-05-26T07:56:54.525729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Combining serverless and high-performance computing paradigms to support ml data-intensive applications","venue":null,"work_id":"77c77c42-cf98-4937-b4ce-4bda3d6f4982","year":2026},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:8c6e74c186afbe639f26326646861c31b6ad60434244bbc8ca9357f54b0050aa","observation_id":"190801ce-5457-42ee-ad76-042308f506ef","resolution":{"observed_at":"2026-05-26T07:56:54.587042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"5660.2022","doi":"10.1109/bigdata55660.2022","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Bernstam, Martin J Citardi, and Hua Xu","venue":null,"work_id":"df4bb6cd-2bf1-4908-a235-fcdcc60ba22d","year":2022},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:dfc3a0d443d29d0ec205a34632cb83629b9baee5ed4f41317fd71141bc402146","observation_id":"8184da97-a43b-4c1b-87d9-5473b895efbe","resolution":{"observed_at":"2026-05-11T17:36:06.474000Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.3389/fhpcp.2024.1384619","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T00:15:00.872479Z","title":"Supercharging distributed computing environments for high-performance data engineering","venue":null,"work_id":"bad1cb23-e75e-4f2b-af48-3faaf5885c12","year":2024},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:aef4c5f6a397575b022144c2acc631b4c5814676aa3dc121b6537593d28b9851","observation_id":"fb82ca8f-168f-437e-8738-5a2a2d9348ad","resolution":{"observed_at":"2026-05-08T20:09:07.505159Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-07-14T16:20:04.630476+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T16:20:04.630476+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Context rot: How increasing input tokens impacts llm performance","venue":null,"work_id":"4309a611-22be-4e31-a435-376159081328","year":2025},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:d2babeda1a0e711361483915b00eb6caaebd0ea2272841e9bc6be4b3fac7e4a9","observation_id":"a7cb1ef0-77f7-4431-8f9c-b1c7398dff2a","resolution":{"observed_at":"2026-05-26T07:56:54.591138Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Generative benchmarking","venue":null,"work_id":"efed891f-afe2-45ce-8b40-2f3a62b222d4","year":2025},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:89610cb67b00ff0db741ad92b2f3166b9b3359f93e404758cc787e124265af92","observation_id":"5cb1e164-f34c-472c-86b5-6b9842b7380f","resolution":{"observed_at":"2026-05-26T07:56:54.641533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Billion-scale similarity search with GPUs","venue":null,"work_id":"889ee61e-958f-4d5b-a1ec-a58ad96ad33d","year":2021},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:e219a1a6575c4b8d2aa18d32a1a7f6c78b075c3c3907564e52d1016c7614bacc","observation_id":"df02d4e9-9819-419f-840c-09d8243c1ac1","resolution":{"observed_at":"2026-05-08T20:09:07.452071Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Llamaindex: Data framework for connecting large language models to data","venue":null,"work_id":"36ab0066-c3b5-4283-89df-0291dda4d25b","year":2023},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:ef0d70534d3f064a54153d28dce65e6983c12d4af7539ab6d3c3e19ae8412972","observation_id":"27da2dc2-0c03-42a0-a9be-962cb68ed08f","resolution":{"observed_at":"2026-05-26T07:56:54.632646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Evaluating chunking strategies for retrieval","venue":null,"work_id":"734cc53c-8487-4930-ae0a-a3b0bda0ce52","year":2024},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:b5fb52e6fdc6ee206e789f31a82b4761dbe651e6b8e62dd93aa4722d28620f46","observation_id":"4887839f-54ad-4009-a2db-5d34b29107f9","resolution":{"observed_at":"2026-05-26T07:56:54.515452Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Pinecone: Scalable vector database for machine learning applications","venue":null,"work_id":"8cec8671-8306-4bc7-a072-2f20bacd2b73","year":2023},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:b1753136f69c636dbb15123c9f8fb7d86c76e19b55c908e447f0888333140e8a","observation_id":"7b5a19b0-77ba-4322-830a-2a4c0e0aac37","resolution":{"observed_at":"2026-05-26T07:56:54.571461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"From rag to agents: Building intelligent systems with memory and tools","venue":null,"work_id":"18ef846e-7634-44b1-be33-a177a5dc6e7a","year":2022},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:bdbd7529dc92030916a0409e7e4a98b103594b9b6586fdc1462800df2c485913","observation_id":"eb3678c2-8c73-415d-9015-05445a67f4c7","resolution":{"observed_at":"2026-05-26T07:56:54.610262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Building custom ai workflows using langchain tools","venue":null,"work_id":"d4184d32-32cd-4a98-bfc1-bea59cf8c583","year":2024},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:7eeacbf50e7ad6c96284a982d7b3c3c0a5419b33ba261d3357c7926a30ad3b88","observation_id":"b27fd118-fb7b-472b-818f-c078b4ecc653","resolution":{"observed_at":"2026-05-26T07:56:54.538863Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Langgraph: Stateful multi-agent workflows","venue":null,"work_id":"e188d134-0c73-4849-b6c8-5564b90e1f80","year":2024},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:39391e408c340cf0b1360bbff05bebce18ce82bc72d090e055842c45cedc4777","observation_id":"dd403100-795c-495a-ab57-170b38cd7c12","resolution":{"observed_at":"2026-05-26T07:56:54.603304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.32388/r27sw4","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Exploration of llm multi- agent application implementation based on langgraph+ crewai","venue":null,"work_id":"2e402c97-6650-4a91-af9f-5d23da377ad1","year":2024},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:ab89cc0b812a55f6802ebb4a6bdfaf6f374b4b620693a8654d38389cecf547df","observation_id":"80327400-4aa3-470a-a49a-347c54b97259","resolution":{"observed_at":"2026-05-08T20:09:07.459854Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"[Online]","venue":null,"work_id":"9750d30e-dbce-443c-bcf3-cf285776b735","year":2026},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:1d9b2ee044e26e5cea8f5b79760bd580e3c8cba70ad2c93bc1a0c6bd8a85b08e","observation_id":"7509212a-c1ce-412a-be59-f5707b489fa1","resolution":{"observed_at":"2026-05-26T07:56:54.620005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Autogen: Enabling next-gen llm applications via multi-agent conversation","venue":null,"work_id":"f2337fed-bf98-4376-a845-be7c60ae2123","year":2024},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:bd9d4e33045dde1fe32519996e79cf44d810fc3c802baa711333861a6a915776","observation_id":"a83a2d05-52cf-4029-989f-6f9ea95e72da","resolution":{"observed_at":"2026-05-26T07:56:54.624330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Ray: A distributed framework for emerging {AI} applications","venue":null,"work_id":"9f30e87c-1c74-478b-b4e1-d4207383d548","year":2018},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:c4571269b09a607e08a865ba53a915e45d1bc5bb23a78baf480252a9b2ddc9cc","observation_id":"c2b98c87-d731-4fdb-9d7d-a5d0b6516e86","resolution":{"observed_at":"2026-05-26T07:56:54.529950Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"[Online]","venue":null,"work_id":"1d0aca4e-9847-4543-8606-d892ab5e3768","year":2024},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:b2a0b93e420008cda5da34f546454c94552ced89c852567947afd7075dc52428","observation_id":"5a2fb825-f67e-4e3d-8e0b-b1ac2eeea595","resolution":{"observed_at":"2026-05-26T07:56:54.645054Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Dask: Parallel computation with blocked algorithms and task scheduling","venue":null,"work_id":"833dc1cb-f0ef-4a8d-9ae8-1d2a70d39125","year":2015},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:198dbb7114ea4a3f353d55274f380987f2154078c1265d0f40d4551eba3c49c8","observation_id":"b0526855-fe7b-4fda-a502-e6a095890fc9","resolution":{"observed_at":"2026-05-26T07:56:54.579121Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.23374","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Higress-rag: A holistic optimization framework for enterprise retrieval-augmented generation via dual hybrid retrieval, adaptive routing, and crag","venue":null,"work_id":"f9b4c591-3a25-43f1-a8c1-7cfc36128e38","year":2025},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:872013c326f1daf31e37a73934ee9a60c11a1fbb7c55dcef2588c30ce9078a0c","observation_id":"950be97a-44d7-42c5-8844-11f59235001d","resolution":{"observed_at":"2026-05-11T17:36:06.467932Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Higress","venue":null,"work_id":"6f2c3ffb-78c2-4134-96eb-06207e2e83fc","year":2026},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:1be9ccc6a000c6f057e2959e855a98652ba2ca88081df284d4f5c56976722e01","observation_id":"68698627-cb03-4e64-97dc-7b99d77baa6e","resolution":{"observed_at":"2026-05-26T07:56:54.606592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Apache spark: a unified engine for big data processing","venue":null,"work_id":"915d53c7-b899-4d19-949e-e01daaad482d","year":null},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:8ff186c89cd148fea27be5a40b84a99597c0e31488136718bfaedc77e67321af","observation_id":"7de74b6c-216a-4c70-bfc0-ab922f39e386","resolution":{"observed_at":"2026-05-26T07:56:54.637791Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1145/2934664","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T18:51:08.354209Z","title":"Apache Spark: A Unified Engine for Big Data Processing","venue":null,"work_id":"f3ae0df3-1d04-4074-842e-4e4131f5ace9","year":2016},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:73d06bc29762db97af79066c2890b70309b806dc01d819579fb8931518833b4c","observation_id":"eb8b00e7-cab3-41ca-bb53-a39b96024f85","resolution":{"observed_at":"2026-05-08T20:09:07.417067Z","resolver_source":"doi","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-07-14T16:20:07.502117+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T16:20:07.502117+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Apache flink: Stream and batch processing in a single engine","venue":null,"work_id":"5f30d3a5-7964-4514-9c25-e9ee7b8c4979","year":2015},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:cc1005e65080a5588f7ccee10385bdb97cc7dbe7e114aba20dd162781e71ec7f","observation_id":"02a3b36b-7353-49cd-b4b3-8f5a58290b03","resolution":{"observed_at":"2026-05-26T07:56:54.550262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.14778/3407790.3407807","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T00:15:00.872479Z","title":"Towards scalable dataframe systems","venue":null,"work_id":"2651c239-e57c-447b-825b-5e88bb2d6351","year":2033},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:2e35374a5a86f28dfa93c4bad7d0b4e6a68a88461cc483967d27cc9a9f7cd794","observation_id":"55941a38-eaca-4f42-837f-fb19d7bb3e7d","resolution":{"observed_at":"2026-05-08T20:09:07.542355Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-07-14T16:20:05.276337+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T16:20:05.276337+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1145/3508396.3512875","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T00:15:00.872479Z","title":"Incremental perception on real time 3d data","venue":null,"work_id":"e9635288-5818-467c-84c9-4899d3f14762","year":2022},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:c6965d7460ea8079e25f1673d66081b1dba84d953e4efda91115820e454250e8","observation_id":"ada0e7b0-142a-4b8a-b32b-736313b4c0d3","resolution":{"observed_at":"2026-05-08T20:09:07.576363Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Parsl: Pervasive parallel programming in python","venue":null,"work_id":"f578ca28-b9b5-4895-8a69-3ba5a2482f0b","year":2019},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:735422a240eaae8b7fdd0165387daf96e3ec50a85e69f7d1f10bd3e4529efd39","observation_id":"661f657d-7cad-4fab-b799-7670fd3113b1","resolution":{"observed_at":"2026-05-08T20:09:07.465899Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"High-level messaging patterns","venue":null,"work_id":"81c547b6-22b6-48b7-aceb-a11a3a663db6","year":null},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:2cb82838f8e28ef4cc967fa2dd8752e82b0a292ed24cfc12df7a2596f38a7556","observation_id":"bb89429d-1833-496e-a004-c4db9ecc2b3b","resolution":{"observed_at":"2026-05-26T07:56:54.599763Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Available: https://zguide .zeromq.org/docs/chapter2/ #High-Level-Messaging-Patterns\"","venue":null,"work_id":"ee9d2f51-b6da-43a9-8f25-545ff8dc35cd","year":null},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:1196455bb7de3267362a52b9061c77167a5c9808730218b37f5ed2dc30afd30e","observation_id":"e9a48e16-abef-4761-9a7b-18436c877b4c","resolution":{"observed_at":"2026-05-26T07:56:54.520783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"file/3738514","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pathways: Asynchronous distributed dataflow for ml","venue":null,"work_id":"a416b663-a9e3-4b94-8c6d-de935f7a7a6a","year":2022},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:e0bdfdae3d294559d1bea9e26b82f396cd484e1bb62db35be0df25a38331265a","observation_id":"8f4b4b94-54ef-4f34-8bd8-08504cbf93b5","resolution":{"observed_at":"2026-05-11T17:36:06.452265Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.15032","last_updated":"2022-04-19T11:57:54Z","snapshot_observed_at":"2026-07-06T12:02:59.925382Z","submitted_at":"2021-10-28T11:32:14Z","title":"OneFlow: Redesign the Distributed Deep Learning Framework from Scratch","version":6},"cited_work":{"arxiv_id":"2110.15032","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2110.15032","snapshot_observed_at":"2026-07-04T07:09:38.138172Z","title":"45 Geng Zhang, Xuanlei Zhao, Kai Wang, and Yang You","venue":null,"work_id":"4b54f68c-9e04-4726-83ed-ad871b3542f2","year":2021},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"cited_paper":"/paper/2110.15032","citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:b7e445457e332eff9469a228cc55d71efaa98409beea5270d4a311e6670efde8","observation_id":"4faf7e6e-51d3-4d18-b49b-78374033f2aa","resolution":{"observed_at":"2026-05-11T17:36:06.461783Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Dspy: Compiling declarative language model calls into self-improving pipelines","venue":null,"work_id":"d69b6721-2d73-40a2-9665-54d1669cad3b","year":2024},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:167b2be55f43a5277857e7f4ba9bf569a0e41937f914a2b6be80a630d8f0a405","observation_id":"b46834dc-04bb-46d1-aaeb-4d0e63164f4a","resolution":{"observed_at":"2026-05-26T07:56:54.563255Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"and Zhang, Hao and Stoica, Ion , booktitle =","venue":null,"work_id":"d28bfac0-e89d-40ac-a856-32d159505db7","year":2023},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:c199c21873a01470c42752912df24c12bf7e9f135e6c8a60c13be5928bc9ff4a","observation_id":"cba958ab-dae0-4f51-bfcd-e2a3a109d6ad","resolution":{"observed_at":"2026-05-08T20:09:07.399290Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.5555/3737916.3739916","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T12:15:01.137692Z","title":"Sglang: efficient execution of structured language model programs","venue":null,"work_id":"5275ac79-a5d3-4b99-b141-96b5903e781f","year":2024},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:83235003839638469e69a33584a6cb4deeffb159a149520ff5e6303a1c2dfb86","observation_id":"a5c68d89-cb78-4110-8a54-3598030faa4b","resolution":{"observed_at":"2026-05-08T20:09:07.442420Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-07-14T16:20:07.757333+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T16:20:07.757333+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1145/3696410.3714805","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T00:15:00.872479Z","title":"Memorag: Boosting long context processing with global memory-enhanced retrieval augmentation","venue":null,"work_id":"229a8d6f-7737-4a93-8f7b-04aaa0d61127","year":2025},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:2a2b8afe71acfc8f8f6a5391b6ee2b66ab708310eb48b6697d0d26ffa46b313b","observation_id":"f8ef0dd0-dc26-45dd-b6fb-a7b70ce1d534","resolution":{"observed_at":"2026-05-08T20:09:07.555027Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.16071","last_updated":"2025-03-20T12:04:40Z","snapshot_observed_at":"2026-07-06T20:56:00.594770Z","submitted_at":"2025-03-20T12:04:40Z","title":"Tuning LLMs by RAG Principles: Towards LLM-native Memory","version":1},"cited_work":{"arxiv_id":"2503.16071","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.16071","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Tuning llms by rag principles: Towards llm-native memory","venue":null,"work_id":"bc3f03d2-cca0-45de-bd23-a6f6ea4fec97","year":2025},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"cited_paper":"/paper/2503.16071","citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:055fc786ed1aa84f550a89585da54887d7920c4bef204fce2e0b98ceabb01e89","observation_id":"5ac532f7-4c7f-46a3-a5da-e6398c2b4b2d","resolution":{"observed_at":"2026-05-11T17:36:06.456179Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"From RAG to memory: Non-parametric continual learning for large language models","venue":null,"work_id":"567c607d-91f9-4bc2-b373-29891a596a7d","year":2025},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:6c5562606a0e87a41b5aa9cbfcff94e0e2fef03352a9dc2433c33a1ec7e10894","observation_id":"caf43e4c-780c-4002-b3f4-6b61a2f881aa","resolution":{"observed_at":"2026-05-26T07:56:54.534295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Cue rag: Dynamic multi-output cue memory under h framework for retrieval-augmented generation","venue":null,"work_id":"00d44e81-b952-4876-9191-5be7a1f72ed5","year":null},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:da65754d7f1055499a767e7c4a771ea61b94a736020c6a08d1f3f45c79b951d1","observation_id":"9a2a9650-a279-42d6-8581-a3e738978c94","resolution":{"observed_at":"2026-05-26T07:56:54.628718Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+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":"2026-06-05T21:23:00.469572Z","title":"Available: https://www .sciencedirect.com/science/article/ pii/S0925231225009075","venue":null,"work_id":"d70889cf-1bdf-4719-805b-904d14a15f12","year":null},"citing_paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-08T17:24:16.645107Z"},"links":{"citing_paper":"/paper/2605.02162"},"observation_digest":"sha256:9a2880cdd60252cd4d628b1fc5afbafafa653ba025b005bf8dc62b985bfaee12","observation_id":"afbcd2ad-1a1e-4da4-8c9e-2a778d788430","resolution":{"observed_at":"2026-05-26T07:56:54.582958Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-02T06:30:47.504484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2605.02162","last_updated":"2026-05-04T02:39:13Z","latest_version":1,"primary_category":"cs.DC","snapshot_observed_at":"2026-07-06T23:15:18.048504Z","submitted_at":"2026-05-04T02:39:13Z","title":"AAFLOW: Scalable Patterns for Agentic AI Workflows"},"reference_resolution":{"displayed":66,"state_counts":{"malformed_identifier":1,"metadata_mismatch":3,"parse_uncertain":0,"unresolved":0,"verified_exact":27,"verified_fuzzy":35},"total_outbound_references":66},"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":"2026-08-02T06:30:47.504484+00:00","source":"crossref"},{"observed_at":"2026-08-02T06:30:44.765945+00:00","source":"retraction_watch"}],"thesis":"As of 2 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 1 inbound Pith citation observation for arXiv:2605.02162."}