{"as_of":"2026-08-09T07:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:af51a3a40adfec7af27d7b487961d579d1d7153aee87261f0299b8741257296b","coverage":[{"denominator":37,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":37,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:24:28.443208Z","state":"measured"},{"denominator":39,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":39,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:46:04.546329Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-19T01:11:57.095148Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.08098","snapshot_observed_at":"2026-08-07T04:46:04.546329Z","title":"Cognitive weave: Synthesizing abstracted knowledge with a spatio-temporal resonance graph,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.09656","last_updated":"2025-08-07T08:42:17Z","snapshot_observed_at":"2026-08-08T06:47:05.646052Z","submitted_at":"2025-06-11T12:25:38Z","title":"Multi-level Value Alignment in Agentic AI Systems: Survey and Perspectives","version":2},"reference_index":141,"source":"pdf_text","source_observed_at":"2026-08-07T04:46:04.546329Z"},"links":{"cited_paper":"/paper/2506.08098","citing_paper":"/paper/2506.09656"},"observation_digest":"sha256:485e565420a49d4b48d46d11104bd0fc4a28ab8f8fae2a94f4e72a08b68c236b","observation_id":"ac67e1ab-528f-4d28-ad5f-7a19dde4deea","resolution":{"observed_at":"2026-08-07T04:46:04.546329Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"cited_work":{"arxiv_id":"2506.08098","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.08098","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Cognitive weave: Synthesizing abstracted knowledge with a spatio-temporal resonance graph","venue":null,"work_id":"162ac47a-7b31-4c4a-b0b8-f9cb94327137","year":2025},"citing_paper":{"arxiv_id":"2508.03341","last_updated":"2026-04-16T06:59:15Z","snapshot_observed_at":"2026-08-02T15:32:15.163641Z","submitted_at":"2025-08-05T11:41:13Z","title":"What Deserves Memory: Adaptive Memory Distillation for LLM Agents","version":4},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-19T01:10:47.164918Z"},"links":{"cited_paper":"/paper/2506.08098","citing_paper":"/paper/2508.03341"},"observation_digest":"sha256:e14b23829cac6fd48b4f88ca3d8ee6d89288ea3d9ba7a876880af7c4a82ac4da","observation_id":"971e7625-eb3e-44be-bb47-04a33e4aac6f","resolution":{"observed_at":"2026-05-19T01:11:57.098446Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.08098/citation-record","integrity":"/paper/2506.08098/integrity","json":"/paper/2506.08098/citation-record.json","paper":"/paper/2506.08098"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.854179Z","title":"Attention is all you need,","venue":null,"work_id":"eb75e56b-839d-4abf-a389-0ca1dc9a371f","year":2017},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.330314Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:82cca875324e3fe930797c767b954c170191197646ce7bee36bf16269cabb597","observation_id":"747b34b0-b818-4fc0-9b5a-e20b376e5df8","resolution":{"observed_at":"2026-08-07T05:24:28.857368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.845912Z","title":"Language models are few-shot learners,","venue":null,"work_id":"a070ceba-71c2-4904-9203-fa2e3d4db28e","year":2020},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.334168Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:b0d8cf77378a31ac773e8177779c7a3540df106fb6158f8036ee612d0df23a76","observation_id":"5d701d5b-c2ff-4435-874e-3fe14df76d6d","resolution":{"observed_at":"2026-08-07T05:24:28.849053Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-07T05:24:28.337150Z","title":"GPT-4 technical report,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.337150Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:d5ab202c7efead8b20112298c582d556c77f68bc7c211af01538ae20757c80c9","observation_id":"7ff0907a-dcbf-4e26-86e3-b59e832003e6","resolution":{"observed_at":"2026-08-07T05:24:28.337150Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.837169Z","title":"Generative agents: Interactive simulacra of human behavior,","venue":null,"work_id":"3e4039df-67a7-4f4f-91ee-a2d246ca3c43","year":2023},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.340250Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:e6cdaefc60ed896f93a3d745a1bfc7c672d3f70b3a4e6c3b4284d50bd54c087e","observation_id":"614259e0-dda4-4d4f-b183-d1489ad8ff16","resolution":{"observed_at":"2026-08-07T05:24:28.840315Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11432","last_updated":"2025-03-02T04:04:03Z","snapshot_observed_at":"2026-08-02T07:33:16.089197Z","submitted_at":"2023-08-22T13:30:37Z","title":"A Survey on Large Language Model based Autonomous Agents","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11432","snapshot_observed_at":"2026-08-07T05:24:28.343585Z","title":"A survey on large language model based autonomous agents,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.343585Z"},"links":{"cited_paper":"/paper/2308.11432","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:81232f0ab4dac81c6475d5196dba606282c622fa6d4cce5f8d695d625fae7c0d","observation_id":"481b18da-d5a4-4f5b-805b-cd028eecaf2d","resolution":{"observed_at":"2026-08-07T05:24:28.343585Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.07864","last_updated":"2023-09-19T08:29:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-14T17:12:03Z","title":"The Rise and Potential of Large Language Model Based Agents: A Survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.07864","snapshot_observed_at":"2026-08-07T05:24:28.347361Z","title":"The rise and potential of large language model based agents: A survey,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.347361Z"},"links":{"cited_paper":"/paper/2309.07864","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:a3caa6c0edbc7c987b08ae65ccf6e81e88c89d8420c2a4ab1de1dea2a6407df7","observation_id":"e41c78af-ae25-4517-8901-12a32e9c603e","resolution":{"observed_at":"2026-08-07T05:24:28.347361Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.828594Z","title":"React: Synergizing reasoning and acting in language models,","venue":null,"work_id":"f1cb2bd0-3212-41bb-8e64-415ff3d272c0","year":2023},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.351274Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:8aede44255d619b24cef97aa354d886dff36b140a31f139080f760acb58f2d2c","observation_id":"81b4064e-ccdb-44cd-bd7e-ad5048bcdbf0","resolution":{"observed_at":"2026-08-07T05:24:28.831524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.11366","last_updated":"2023-10-10T05:21:45Z","snapshot_observed_at":"2026-07-06T15:05:53.556198Z","submitted_at":"2023-03-20T18:08:50Z","title":"Reflexion: Language Agents with Verbal Reinforcement Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.11366","snapshot_observed_at":"2026-08-07T05:24:28.354242Z","title":"Reflexion: Language agents with verbal reinforcement learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.354242Z"},"links":{"cited_paper":"/paper/2303.11366","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:2fb1a0b9f43a4a45e51a926fac7b45a9728ce68232469e8ff3a8ce316e484957","observation_id":"651a0b24-58c3-42a9-9cb2-9202afae4a82","resolution":{"observed_at":"2026-08-07T05:24:28.354242Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.820349Z","title":"Retrieval-augmented generation for knowledge-intensive NLP tasks,","venue":null,"work_id":"638a78b4-518d-4ec7-bb10-679bc8f0d919","year":2020},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.357467Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:5c0ba39256e29cd87ff8a4fa11c86497e6f68449794acabdc0b0b74b891a5c87","observation_id":"3466078b-77d1-42d2-bed6-f25377aa63ea","resolution":{"observed_at":"2026-08-07T05:24:28.823395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.811883Z","title":"Dense passage retrieval for open-domain question answering,","venue":null,"work_id":"b88ecf02-1a53-442c-930f-97745cf76e59","year":2020},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.360429Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:a5694d79ffd87a3eb73d5e7b639188466faa7e8a820a048a8cb497e2f443f9f1","observation_id":"e212b14b-e501-49cd-acc6-5871ddc5768d","resolution":{"observed_at":"2026-08-07T05:24:28.815107Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.801898Z","title":"Improving language models by retrieving from trillions of tokens,","venue":null,"work_id":"07242e39-99f6-4bd3-8aed-1e1c7c7bb487","year":2022},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.363733Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:bf4d00078cc19d6406d218476ad290e0a4b0e6d436b2b51c7859f5007512d265","observation_id":"d5dfaf88-f919-423d-8d66-9c6df2ba5dc3","resolution":{"observed_at":"2026-08-07T05:24:28.805121Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08560","last_updated":"2024-02-12T18:59:46Z","snapshot_observed_at":"2026-08-09T03:13:16.831626Z","submitted_at":"2023-10-12T17:51:32Z","title":"MemGPT: Towards LLMs as Operating Systems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08560","snapshot_observed_at":"2026-08-07T05:24:28.366756Z","title":"Memgpt: Towards llms as operating systems,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.366756Z"},"links":{"cited_paper":"/paper/2310.08560","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:1a026b7cb01d74f740ef816e1ad8e0525bb925a0ec2c5dee5899a1ff3f463e70","observation_id":"ef42de5a-89f5-4b47-8306-de090ca0917a","resolution":{"observed_at":"2026-08-07T05:24:28.366756Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02632","last_updated":"2024-02-08T14:24:40Z","snapshot_observed_at":"2026-07-06T17:25:09.951423Z","submitted_at":"2024-02-04T22:53:38Z","title":"GIRT-Model: Automated Generation of Issue Report Templates","version":2},"cited_work":{"arxiv_id":"2402.02632","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.02632","snapshot_observed_at":"2026-08-07T05:24:28.636487Z","title":"GIRT-Model: Automated Generation of Issue Report Templates","venue":"cs.SE","work_id":"2180c4c1-f321-45a7-b93c-7eb2d995f724","year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.370020Z"},"links":{"cited_paper":"/paper/2402.02632","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:d0133a9b402c2e3241b13476cf32b205822224140831ceb32a61599e9b026750","observation_id":"e71b2f40-5cb1-4374-a980-0b32940d8c4d","resolution":{"observed_at":"2026-08-07T05:24:28.640067Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05720","last_updated":"2024-09-10T08:27:55Z","snapshot_observed_at":"2026-08-02T16:02:47.275751Z","submitted_at":"2024-02-08T14:52:17Z","title":"Measurements of the Low-Acceleration Gravitational Anomaly from the Normalized Velocity Profile of Gaia Wide Binary Stars and Statistical Testing of Newtonian and Milgromian Theories","version":4},"cited_work":{"arxiv_id":"2402.05720","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.05720","snapshot_observed_at":"2026-08-07T05:24:28.624016Z","title":"Measurements of the Low-Acceleration Gravitational Anomaly from the Normalized Velocity Profile of Gaia Wide Binary Stars and Statistical Testing of Newtonian and Milgromian Theories","venue":"astro-ph.GA","work_id":"eaa4f1bf-7f1d-4afd-8763-245f18e1bcb5","year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.373561Z"},"links":{"cited_paper":"/paper/2402.05720","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:a42127b45398bab66a5089d60b6d10b0de4f3bbc15da8f0f91b3aae3d9738eed","observation_id":"d50709dc-3acd-4c70-964a-62217a75cb3e","resolution":{"observed_at":"2026-08-07T05:24:28.628141Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16725","last_updated":"2024-05-29T02:21:08Z","snapshot_observed_at":"2026-08-02T08:37:08.433593Z","submitted_at":"2024-05-26T23:48:00Z","title":"Discovery and follow-up of a quasiperiodically nulling and sub-pulse drifting pulsar with the Murchison Widefield Array","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.16725","snapshot_observed_at":"2026-08-07T05:24:28.376463Z","title":"A-MEM: An agentic memory system for llm-based agents,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.376463Z"},"links":{"cited_paper":"/paper/2405.16725","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:23571a87c40a64d3bbe1c13932f4d0754ec25ec432bac157c246e0153cb2c302","observation_id":"8edf37fe-73d5-40fc-9c58-8a9dc69f0bc6","resolution":{"observed_at":"2026-08-07T05:24:28.376463Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.02889","last_updated":"2024-11-13T18:49:47Z","snapshot_observed_at":"2026-08-08T17:19:20.640791Z","submitted_at":"2024-05-05T10:55:44Z","title":"The Griffiths phase and beyond: A large deviations study of the magnetic susceptibility of the two-dimensional bond-diluted Ising model","version":2},"cited_work":{"arxiv_id":"2405.02889","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.02889","snapshot_observed_at":"2026-08-07T05:24:28.604657Z","title":"The Griffiths phase and beyond: A large deviations study of the magnetic susceptibility of the two-dimensional bond-diluted Ising model","venue":"cond-mat.dis-nn","work_id":"cfd52175-b4a8-45d8-8113-2b624170275b","year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.379275Z"},"links":{"cited_paper":"/paper/2405.02889","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:6b99dd146da249867c31a4be550baa097304b99c4d9ed77874596673f2a2d249","observation_id":"c812f97d-36a7-4aab-bc6b-045bbd3aa37d","resolution":{"observed_at":"2026-08-07T05:24:28.608143Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09032","last_updated":"2023-11-15T15:25:08Z","snapshot_observed_at":"2026-07-06T16:47:57.524339Z","submitted_at":"2023-11-15T15:25:08Z","title":"Nahida: In-Band Distributed Tracing with eBPF","version":1},"cited_work":{"arxiv_id":"2311.09032","doi":null,"metadata_source":"pith","pith_arxiv_id":"2311.09032","snapshot_observed_at":"2026-08-07T05:24:28.588939Z","title":"Nahida: In-Band Distributed Tracing with eBPF","venue":"cs.OS","work_id":"f0e76a1e-e2f4-4c8a-b15c-685551ca56a8","year":2023},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.382266Z"},"links":{"cited_paper":"/paper/2311.09032","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:a242878a356d442b017071a59e73cf5d386c94054d1d700b98e1e250e8576fcc","observation_id":"f73c81c7-c236-40c8-90dd-793be1755c0e","resolution":{"observed_at":"2026-08-07T05:24:28.594977Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.17603","last_updated":"2024-01-31T05:13:53Z","snapshot_observed_at":"2026-08-01T15:09:41.348646Z","submitted_at":"2024-01-31T05:13:53Z","title":"Topology-Aware Latent Diffusion for 3D Shape Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.17603","snapshot_observed_at":"2026-08-07T05:24:28.385744Z","title":"Mem0: A memory layer for ai agents,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.385744Z"},"links":{"cited_paper":"/paper/2401.17603","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:7c2416130ac454cdcd0156c89ee8644334e1fd685ba92b43c193f1da8478df64","observation_id":"b38816b8-fb3b-498b-8515-65a388b4932e","resolution":{"observed_at":"2026-08-07T05:24:28.385744Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.792973Z","title":"Kadavy,Digital Zettelkasten: Principles, Methods, & Examples","venue":null,"work_id":"dbf7256b-b27d-4982-ab9e-3e1e5d642ad8","year":2021},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.388632Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:9975a1a0a6529dd8c74210b88d4a5ee17354b8441e2f92da9271d3f8a00d38bd","observation_id":"7326db42-0e38-475b-899d-26fbed126c66","resolution":{"observed_at":"2026-08-07T05:24:28.796246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.783908Z","title":"Graphiti: Temporal knowledge graphs for llm applications,","venue":null,"work_id":"103ecca5-332b-4fdf-8a7d-e8b52215ff6c","year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.391738Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:01e9ae5b4be2a7970230d8c9ff20e4d16bb54d1a982806e1fb2336933250fd1f","observation_id":"3553ad49-d0ea-4839-a171-d1602e3ebf15","resolution":{"observed_at":"2026-08-07T05:24:28.787232Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.775047Z","title":"Spatio-temporal memory system,","venue":null,"work_id":"80c65a80-4940-43da-8f89-206ce12cabf4","year":2013},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.395718Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:fe085b99ba11d6bfeb149bf4d1c8ac40052500d1cea0f7ae344ca74bd34d3da9","observation_id":"94f7ef3b-9469-4835-a75f-02132d676871","resolution":{"observed_at":"2026-08-07T05:24:28.778441Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.16967","last_updated":"2024-08-30T02:01:56Z","snapshot_observed_at":"2026-08-07T04:02:32.468028Z","submitted_at":"2024-08-30T02:01:56Z","title":"MemLong: Memory-Augmented Retrieval for Long Text Modeling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.16967","snapshot_observed_at":"2026-08-07T05:24:28.398517Z","title":"Memlong: Memory-augmented retrieval for long text modeling,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.398517Z"},"links":{"cited_paper":"/paper/2408.16967","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:fb1dfa7d62af114a73a884ffa6475a895bb2d6a45d11e04e8df88d634b125a96","observation_id":"1a385f16-5773-4506-9fd8-6d27c8505d0d","resolution":{"observed_at":"2026-08-07T05:24:28.398517Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.766041Z","title":"Focused transformer: Contrastive training for context scaling,","venue":null,"work_id":"db1c71db-fbf8-4437-b174-08ae88e9f365","year":2023},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.401618Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:dcefa4a12b4ed209683b9980a4cedb238513490bf77eb67d2e425babff981b8a","observation_id":"823cb76b-5b4b-47cd-822d-6ae88421e702","resolution":{"observed_at":"2026-08-07T05:24:28.769337Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.404313Z","title":"A graph- based approach for conversational ai-driven personal memory capture and retrieval in a real-world application,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.404313Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:c8146d3956d0f5ebcfa05515c30aaf30bfe56504aa1f10ee6b2954081c48ec0e","observation_id":"6d06888f-8d2c-4027-a852-ab6868e6cb5b","resolution":{"observed_at":"2026-08-07T05:24:28.404313Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.13501","last_updated":"2024-04-21T01:49:46Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-04-21T01:49:46Z","title":"A Survey on the Memory Mechanism of Large Language Model based Agents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.13501","snapshot_observed_at":"2026-08-07T05:24:28.407183Z","title":"A survey on the memory mechanism of large language model based agents,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.407183Z"},"links":{"cited_paper":"/paper/2404.13501","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:b15fc372706182d3e3fc0280f3d5fd5ff978f1c9fd2bfbd0134eab0dc5d35d23","observation_id":"9e9bf190-7ac4-4a80-af41-ab54b51901ec","resolution":{"observed_at":"2026-08-07T05:24:28.407183Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.21760","last_updated":"2025-07-31T23:26:12Z","snapshot_observed_at":"2026-08-07T16:32:03.464415Z","submitted_at":"2025-03-27T17:57:28Z","title":"MemInsight: Autonomous Memory Augmentation for LLM Agents","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.21760","snapshot_observed_at":"2026-08-07T05:24:28.410403Z","title":"Meminsight: Autonomous memory augmentation for llm agents,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.410403Z"},"links":{"cited_paper":"/paper/2503.21760","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:b910c208b3f322e023de9966ba88e8d3265983848983163e08e0d49d29994d73","observation_id":"e7ae0dbd-7552-43d7-9f20-f42b194fe966","resolution":{"observed_at":"2026-08-07T05:24:28.410403Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.757035Z","title":"\" my agent understands me better","venue":null,"work_id":"dbe5055c-d4c1-4fbc-801e-5436b0880387","year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.413739Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:3d501ea759ccb45bfe1b2f358f729fb537ff788c6b20729596b6bcd89c4539b8","observation_id":"dae3deb1-28ae-47d1-9841-e3174d4c630e","resolution":{"observed_at":"2026-08-07T05:24:28.760217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.07429","last_updated":"2024-09-11T17:21:00Z","snapshot_observed_at":"2026-08-07T15:35:11.892405Z","submitted_at":"2024-09-11T17:21:00Z","title":"Agent Workflow Memory","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.07429","snapshot_observed_at":"2026-08-07T05:24:28.416472Z","title":"Agent workflow memory,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.416472Z"},"links":{"cited_paper":"/paper/2409.07429","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:01afe2109ace3d23d97ec954e92a201bbaf3a4b89f03af8497ec5b6180ff681a","observation_id":"0668dc39-8d99-4bc2-a777-6bdce162952d","resolution":{"observed_at":"2026-08-07T05:24:28.416472Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.04363","last_updated":"2025-05-15T10:57:51Z","snapshot_observed_at":"2026-08-04T20:25:50.849634Z","submitted_at":"2024-07-05T09:06:47Z","title":"AriGraph: Learning Knowledge Graph World Models with Episodic Memory for LLM Agents","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.04363","snapshot_observed_at":"2026-08-07T05:24:28.419745Z","title":"Arigraph: Learning knowledge graph world models with episodic memory for llm agents,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.419745Z"},"links":{"cited_paper":"/paper/2407.04363","citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:8f63db3bd2e416611df684560fcf6897df20443da8c79bb0a3a313e6543ffbcf","observation_id":"9762c2aa-e7a8-4ead-b967-b52f5215ca69","resolution":{"observed_at":"2026-08-07T05:24:28.419745Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.747969Z","title":"Azure openai service models - gpt-4 and gpt-4 turbo (o4 mini is often an internal/shorthand reference for gpt-4 omni mini if it exists, or a similar compact gpt-4 variant),","venue":null,"work_id":"cee87b50-8f82-4a10-83bb-3152ec7dee11","year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.422770Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:b8dacc5c181471077ddae5988981278f34ef51250b64bb20e38860b8e2fe3d65","observation_id":"8aaad5cf-3bf0-4150-961f-ffd928a1a252","resolution":{"observed_at":"2026-08-07T05:24:28.751453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.425727Z","title":"Sentence-bert: Sentence embeddings using siamese bert-networks,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.425727Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:dc0d126b0b7a9508f3920fd589a03927cf1ae2d6127120bfbf3794f4a3333ce5","observation_id":"255633cc-75c8-4524-84bc-1cbf248af4c3","resolution":{"observed_at":"2026-08-07T05:24:28.425727Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.732721Z","title":"Billion-scale similarity search with gpus,","venue":null,"work_id":"df8762dc-8475-4a85-9cac-ae7554a60e5d","year":2019},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.428526Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:c184fcbad79e21e2acad2ddc24d75bf54aa59dca23e4fe7b3a212451421c6eed","observation_id":"a0be65de-4586-4173-af91-dfa7caab9b4b","resolution":{"observed_at":"2026-08-07T05:24:28.736088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.723059Z","title":"Robotouille: A recipe for large language model evaluation in interactive environments,","venue":null,"work_id":"ec881dd6-6353-4c9f-96eb-4617f315f347","year":2024},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.431375Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:32d9e5f2c14cc8c232e60507d52043ac58cded471148d50cb5afa98682d5c9ef","observation_id":"3a7e5c17-5dfa-4ec1-ad55-1eefc0cf50ff","resolution":{"observed_at":"2026-08-07T05:24:28.726273Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.713981Z","title":"BLEU: a method for automatic evaluation of machine translation,","venue":null,"work_id":"d3161a8e-bf76-49c5-bc37-2bb5106b09d4","year":2002},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.434517Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:b56acf6609a9ee11ea246e9aad4121cfb0cb9ecc745febf668a5c46b715a2d17","observation_id":"4f4f5203-4892-42a6-8a20-ae1414779eb5","resolution":{"observed_at":"2026-08-07T05:24:28.717527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.704960Z","title":"ROUGE: A package for automatic evaluation of summaries,","venue":null,"work_id":"8a4da9fc-e044-4be6-ba00-ec2174fbcfc3","year":2004},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.437362Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:e5f9ecc95966e076d6edf764f27901f7acda04b6cd1d8e712996b1e695b01d79","observation_id":"f09558ec-84e0-4603-a382-ba8f14f7c232","resolution":{"observed_at":"2026-08-07T05:24:28.708406Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.695083Z","title":null,"venue":null,"work_id":"02e4e5f9-ba24-4d50-af1b-fcdafc59e122","year":1991},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.440242Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:bd54ba1526571deed9aa56bcdf91c489f218c5178808efd370cb97b35349ada8","observation_id":"b6d74b78-5459-4306-9c88-915e7867b9cf","resolution":{"observed_at":"2026-08-07T05:24:28.698870Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:24:28.685678Z","title":"Modeling by shortest data description,","venue":null,"work_id":"8ac02f7a-af38-435a-ab51-3b752a27e278","year":1978},"citing_paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:28.443208Z"},"links":{"citing_paper":"/paper/2506.08098"},"observation_digest":"sha256:5448bafc9732f314270d34eee36805c3bdd2cd56c77b89308e40147db6b6b9f4","observation_id":"cd34ef4c-59b0-40b7-8bfc-cf0bb0319991","resolution":{"observed_at":"2026-08-07T05:24:28.689036Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.08098","last_updated":"2025-06-09T18:00:46Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-08T20:59:09.215091Z","submitted_at":"2025-06-09T18:00:46Z","title":"Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph"},"reference_resolution":{"displayed":37,"state_counts":{"malformed_identifier":0,"metadata_mismatch":3,"parse_uncertain":0,"unresolved":15,"verified_exact":1,"verified_fuzzy":18},"total_outbound_references":37},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 2 inbound Pith citation observations for arXiv:2506.08098."}