{"as_of":"2026-08-22T04:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:522bf23816eab2ea526f164ece720406a7679f1011caffdacfdc22712274cf43","coverage":[{"denominator":38,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":38,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T00:27:34.406741Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"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":[],"links":{"evidence":"/evidence","html":"/paper/2608.12428/citation-record","integrity":"/paper/2608.12428/integrity","json":"/paper/2608.12428/citation-record.json","paper":"/paper/2608.12428"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T00:27:35.175244Z","title":"OpenCode.https://github.com/anomalyco/opencode, 2026","venue":null,"work_id":"617ccdac-6332-4415-8124-05fed32cc1cd","year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.273056Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:0ecec1b39eb7727bfc5db152432443d9bdc3344233c0769ae6056807586100d2","observation_id":"36b41707-6e32-44c2-9616-a1661346166b","resolution":{"observed_at":"2026-08-16T00:27:35.179203Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-16T00:27:35.165331Z","title":"Claude Code.https://docs.anthropic.com/en/docs/claude-code/overview, 2025","venue":null,"work_id":"8f828522-01c0-436d-85cd-efa46dc300d2","year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.276982Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:b0f050e7fd98e598c154bbaeed4eb2e4295379fed100389979d014797b1bb3a5","observation_id":"b8eec92f-d7e2-4530-b895-0be182f1696d","resolution":{"observed_at":"2026-08-16T00:27:35.168388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-16T00:27:35.155517Z","title":"Nested Learning: The Illusion of Deep Learning Architectures","venue":null,"work_id":"33461302-7ffe-4983-b2d3-b4fe2ca56012","year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.280880Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:83bddcf941374c52369d5185a1a423b1d1bfa49f4de1583ab678ba83acbd08ca","observation_id":"66407af4-ece4-49e1-a167-2097c1eb0c74","resolution":{"observed_at":"2026-08-16T00:27:35.158939Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.23878","last_updated":"2026-08-09T08:11:11Z","snapshot_observed_at":"2026-08-16T06:39:36.582026Z","submitted_at":"2026-04-26T20:39:19Z","title":"ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems","version":3},"cited_work":{"arxiv_id":"2604.23878","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.23878","snapshot_observed_at":"2026-08-16T00:27:35.001951Z","title":"ZenBrain: A Neuroscience-Inspired 7-Layer Memory Architecture for Autonomous AI Systems","venue":"cs.AI","work_id":"b196a06e-fc3d-46ff-b9af-e3d982cc20f0","year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.284152Z"},"links":{"cited_paper":"/paper/2604.23878","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:79ea67ccdce3a454d67703f8aa153ea8c2a078052645702c113d0a3ecec553f8","observation_id":"e09a1bb6-e072-4a36-bfa8-5d24e9378148","resolution":{"observed_at":"2026-08-16T00:27:35.005527Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.19413","last_updated":"2025-04-28T01:46:35Z","snapshot_observed_at":"2026-08-14T23:23:31.683130Z","submitted_at":"2025-04-28T01:46:35Z","title":"Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.19413","snapshot_observed_at":"2026-08-16T00:27:34.287882Z","title":"Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory.https://arxiv","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.287882Z"},"links":{"cited_paper":"/paper/2504.19413","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:b4a86f339eb61ad63ad99e1b5284d88e9c0fc841cdaa9ad7f49b94dc32f3f4b8","observation_id":"9ac14647-d69f-4739-a890-889625fac194","resolution":{"observed_at":"2026-08-16T00:27:34.287882Z","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":"2026-08-16T00:27:35.143653Z","title":"MemBrain: Agent-Native Memory for AI Agents.https://github.com/ feelingai-team/MemBrain, 2026","venue":null,"work_id":"a7191acc-27e3-4f9b-a158-91016d26b6d6","year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.291806Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:af3d28285a59a71c0baa3ba827ce48a62be7f7492ad52aff82f5e62d58e2f440","observation_id":"7a8e5fc3-b9e1-4545-9a89-f76352e239d4","resolution":{"observed_at":"2026-08-16T00:27:35.147626Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2605.29640","last_updated":"2026-05-29T02:43:30Z","snapshot_observed_at":"2026-08-12T14:13:25.051382Z","submitted_at":"2026-05-28T09:07:42Z","title":"VikingMem: A Memory Base Management System for Stateful LLM-based Applications","version":2},"cited_work":{"arxiv_id":"2605.29640","doi":null,"metadata_source":"pith","pith_arxiv_id":"2605.29640","snapshot_observed_at":"2026-08-16T00:27:34.977665Z","title":"VikingMem: A Memory Base Management System for Stateful LLM-based Applications","venue":"cs.AI","work_id":"0f6b351e-4969-488b-8bab-639f86386ca9","year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.295077Z"},"links":{"cited_paper":"/paper/2605.29640","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:8dac2c17efd44f7abcaca469dc719e70e3a68fed3bdb5e251e444be5c562c45b","observation_id":"cd29532d-1f99-4271-8e62-7b5c422a31b2","resolution":{"observed_at":"2026-08-16T00:27:34.980908Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-16T00:27:34.298692Z","title":"LatentMem: Customizing Latent Memory for Multi-Agent Systems","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.298692Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:328d6640908385e7607826a40ace26bbd39cac0a089f24721336b90a93f80d10","observation_id":"d63aff70-0777-4a4a-beca-25fb28f836a1","resolution":{"observed_at":"2026-08-16T00:27:34.298692Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.14802","last_updated":"2025-06-19T21:34:45Z","snapshot_observed_at":"2026-08-16T14:13:54.817924Z","submitted_at":"2025-02-20T18:26:02Z","title":"From RAG to Memory: Non-Parametric Continual Learning for Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.14802","snapshot_observed_at":"2026-08-16T00:27:34.301924Z","title":"From RAG to Memory: Non-Parametric Continual Learning for Large Language Models.https://arxiv","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.301924Z"},"links":{"cited_paper":"/paper/2502.14802","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:59817fea3560504c547d1ea1a4730520ea6abde258e7a95db31a29f4e40f6db1","observation_id":"f1798b8c-5935-4b62-853a-a65e30a3c0d8","resolution":{"observed_at":"2026-08-16T00:27:34.301924Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T00:27:34.305840Z","title":"EverMemOS: A Self-Organizing Memory Oper- ating System for Structured Long-Horizon Reasoning.https://arxiv.org/abs/2601.02163, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.305840Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:52fd9520da27e8bba6ecf42d85a06d2bbe29df975c00945e4c4d8c4cbf3b8574","observation_id":"5c35dd04-8039-4e29-aec6-3a07f53b2afa","resolution":{"observed_at":"2026-08-16T00:27:34.305840Z","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":"2026-08-16T00:27:35.130258Z","title":"Evaluating Memory in LLM Agents via In- cremental Multi-Turn Interactions","venue":null,"work_id":"b8fbfb79-0b43-41ca-aac4-02a7efb32bb2","year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.309554Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:7bfba86a5c556b64d104d22682ed6f181b901121bf4165e8cc18659ec6d674b2","observation_id":"8a6b3e1d-a622-4ffe-86ee-b59c8aabf5ed","resolution":{"observed_at":"2026-08-16T00:27:35.135140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-16T00:27:34.313020Z","title":"Rethinking Memory Mechanisms of Foundation Agents in the Second Half: A Survey.https://arxiv.org/abs/2602.06052, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.313020Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:f1950d70394a7f9b3e615cc86ab4018f2988e6a290d06059440fe6bbcf1a278d","observation_id":"591da3ce-cee5-4f69-b0db-c3b065f87859","resolution":{"observed_at":"2026-08-16T00:27:34.313020Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2606.10677","last_updated":"2026-06-09T10:31:51Z","snapshot_observed_at":"2026-08-12T04:33:23.612481Z","submitted_at":"2026-06-09T10:31:51Z","title":"Infini Memory: Maintainable Topic Documents for Long-Term LLM Agent Memory","version":1},"cited_work":{"arxiv_id":"2606.10677","doi":null,"metadata_source":"pith","pith_arxiv_id":"2606.10677","snapshot_observed_at":"2026-08-16T00:27:34.747135Z","title":"Infini Memory: Maintainable Topic Documents for Long-Term LLM Agent Memory","venue":"cs.AI","work_id":"48d1c18f-825e-42dd-906a-80cf745b74bb","year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.317148Z"},"links":{"cited_paper":"/paper/2606.10677","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:6e84a3cf02a120eab8ce5f3ee2671695761418a23179169c36543417bad751bf","observation_id":"3b47025f-ec11-4fca-9fc4-fa60d6fb829d","resolution":{"observed_at":"2026-08-16T00:27:34.750836Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-16T00:27:35.119052Z","title":"Taylor, and Dan Roth","venue":null,"work_id":"c8d501bd-1926-43d4-baa9-1e6aa744b050","year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.320934Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:7c4baf5b9d45d67d3c4701516b561ca8e6267750593a72f6513a796fc947b5e8","observation_id":"22c00a71-b56c-4d91-8108-4e6258e1572f","resolution":{"observed_at":"2026-08-16T00:27:35.122854Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2607.17545","last_updated":"2026-07-21T02:05:36Z","snapshot_observed_at":"2026-08-14T22:23:06.341486Z","submitted_at":"2026-07-20T04:43:47Z","title":"Retain or Consolidate? Budget-Dependent Operator Selection for Language Agent Memory","version":2},"cited_work":{"arxiv_id":"2607.17545","doi":null,"metadata_source":"pith","pith_arxiv_id":"2607.17545","snapshot_observed_at":"2026-08-16T00:27:34.731746Z","title":"Retain or Consolidate? Budget-Dependent Operator Selection for Language Agent Memory","venue":"cs.AI","work_id":"ca47a40c-f1cb-42f7-8e9c-25a3d9243dc0","year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.324338Z"},"links":{"cited_paper":"/paper/2607.17545","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:f10d89e0e2eee92fe77ec1af6b369281fca5bdd7cfd6325b7e4644fd6e2e5a2b","observation_id":"4b53a249-8fa6-4777-abc9-ddb0b5d5760f","resolution":{"observed_at":"2026-08-16T00:27:34.736411Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2606.10616","last_updated":"2026-06-29T08:38:19Z","snapshot_observed_at":"2026-08-16T21:31:17.031443Z","submitted_at":"2026-06-09T09:15:33Z","title":"Learning What to Remember: Observability-Safe Memory Retention via Constrained Optimization for Long-Horizon Language Agents","version":6},"cited_work":{"arxiv_id":"2606.10616","doi":null,"metadata_source":"pith","pith_arxiv_id":"2606.10616","snapshot_observed_at":"2026-08-16T00:27:34.714822Z","title":"Learning What to Remember: Observability-Safe Memory Retention via Constrained Optimization for Long-Horizon Language Agents","venue":"cs.AI","work_id":"9a5f3a39-7f78-4483-9196-dca165551c5b","year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.328528Z"},"links":{"cited_paper":"/paper/2606.10616","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:1b95ea1283c95acf925e48a868e38bbcfd44368064d82aa8eba519de5fd0932d","observation_id":"908b075f-c986-4b2a-9e8c-5dc4282252c9","resolution":{"observed_at":"2026-08-16T00:27:34.720796Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.03724","last_updated":"2025-12-03T03:19:27Z","snapshot_observed_at":"2026-08-16T06:38:04.806216Z","submitted_at":"2025-07-04T17:21:46Z","title":"MemOS: A Memory OS for AI System","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.03724","snapshot_observed_at":"2026-08-16T00:27:34.332226Z","title":"MemOS: A Memory OS for AI System.https: //arxiv.org/abs/2507.03724, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.332226Z"},"links":{"cited_paper":"/paper/2507.03724","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:806af7e4862408e5d7364d6d9c9348870b595b50e6fac6e54c24e725b1701b42","observation_id":"03807fa5-5102-4df6-866c-27d52dd15149","resolution":{"observed_at":"2026-08-16T00:27:34.332226Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14991","last_updated":"2024-10-17T07:23:23Z","snapshot_observed_at":"2026-08-20T07:48:16.834076Z","submitted_at":"2024-06-21T09:06:45Z","title":"SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14991","snapshot_observed_at":"2026-08-16T00:27:34.335967Z","title":"SpreadsheetBench: Towards Challenging Real World Spreadsheet Manipulation.arXiv preprint arXiv:2406.14991, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.335967Z"},"links":{"cited_paper":"/paper/2406.14991","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:dad8d9b7c62709e3591be8d2efb581f21fdcde7805202fb94fa1727d8f38371c","observation_id":"2087d055-d849-4bdd-ac42-ad5109c0418f","resolution":{"observed_at":"2026-08-16T00:27:34.335967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.17753","last_updated":"2024-02-27T18:42:31Z","snapshot_observed_at":"2026-08-17T18:26:41.317652Z","submitted_at":"2024-02-27T18:42:31Z","title":"Evaluating Very Long-Term Conversational Memory of LLM Agents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.17753","snapshot_observed_at":"2026-08-16T00:27:34.339662Z","title":"Evaluating Very Long-Term Conversational Memory of LLM Agents.https: //arxiv.org/abs/2402.17753, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.339662Z"},"links":{"cited_paper":"/paper/2402.17753","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:e31120be23d0a7b2fe6d8bae58f854d9617a47808d876c61bf1ec3c81bba5591","observation_id":"20c09995-272e-44a1-b76a-190e25638c76","resolution":{"observed_at":"2026-08-16T00:27:34.339662Z","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":"2026-08-16T00:27:35.108099Z","title":"memU: Your Personal Memory, Across Every Agent.https://github.com/ NevaMind-AI/memU, 2025","venue":null,"work_id":"4eb2a332-279a-4025-aa99-005d9e999e8e","year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.343480Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:1f3c20e1c1ed72c6c1038a7f34a784161c30502a9229413b65be22d95d24a73d","observation_id":"361e5dff-a0de-4786-aacf-a3b60f1f01ae","resolution":{"observed_at":"2026-08-16T00:27:35.111902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-16T00:27:35.096408Z","title":"OpenAI Codex CLI.https://github.com/openai/codex, 2025","venue":null,"work_id":"a5ff9b85-6ef0-4f24-a9b4-d5babd389202","year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.347779Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:0e8ff23b0d3b53ab93c52d9319922eb6fb626703effe393a8cbfad206630072f","observation_id":"bc7d22dc-e296-4ad6-9203-5d9412385c78","resolution":{"observed_at":"2026-08-16T00:27:35.100428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-16T00:27:35.083871Z","title":"OpenClaw: An Open Platform for AI Agent Task Execution.https: //docs.openclaw.ai/, 2026","venue":null,"work_id":"af739cce-66cd-4bdd-93da-47e7b2510f3a","year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.351689Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:6fd03df258e826a82faec51269772b2e6c7040fe4cdc33f9149b44b9f4534891","observation_id":"401dff73-ca6f-42df-aa15-cb006eee88f4","resolution":{"observed_at":"2026-08-16T00:27:35.088282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2512.15374","last_updated":"2026-05-28T03:31:48Z","snapshot_observed_at":"2026-08-18T04:49:08.004198Z","submitted_at":"2025-12-17T12:25:05Z","title":"SCOPE: Prompt Evolution for Enhancing Agent Effectiveness","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2512.15374","snapshot_observed_at":"2026-08-16T00:27:34.354982Z","title":"SCOPE: Prompt Evolution for Enhancing Agent Effectiveness.https: //arxiv.org/abs/2512.15374, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.354982Z"},"links":{"cited_paper":"/paper/2512.15374","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:fcf4b8c33bef8ca36d454a97b7b0465ee91cb53e6c6c085a1bd5a53730517aed","observation_id":"a5f4e47c-d017-4bb5-8601-c5ffad137cd1","resolution":{"observed_at":"2026-08-16T00:27:34.354982Z","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":"2026-08-16T00:27:35.070838Z","title":"MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Re- trieval Augmentation","venue":null,"work_id":"c9935fee-7329-44a2-97b7-7313ce06e708","year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.358868Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:62900e0d082903b58d1d597d52de5ab34691d1c603237d2609be00b2e59d0153","observation_id":"09a781f8-c3e3-4998-b397-109f24d303a5","resolution":{"observed_at":"2026-08-16T00:27:35.075105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.13956","last_updated":"2025-01-20T16:52:48Z","snapshot_observed_at":"2026-08-16T13:40:23.316949Z","submitted_at":"2025-01-20T16:52:48Z","title":"Zep: A Temporal Knowledge Graph Architecture for Agent Memory","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.13956","snapshot_observed_at":"2026-08-16T00:27:34.362137Z","title":"Zep: A Temporal Knowledge Graph Architecture for Agent Memory.https://arxiv.org/abs/ 2501.13956, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.362137Z"},"links":{"cited_paper":"/paper/2501.13956","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:a996c2d34c96c07bc6f7c581e5bf6bca3fb5b6b661957f8d188cc465cf06862e","observation_id":"eec96d53-4f67-444b-9a01-bf8f1b192380","resolution":{"observed_at":"2026-08-16T00:27:34.362137Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.27760","last_updated":"2026-05-26T23:18:43Z","snapshot_observed_at":"2026-07-06T23:37:27.309837Z","submitted_at":"2026-05-26T23:18:43Z","title":"SkillGrad: Optimizing Agent Skills Like Gradient Descent","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.27760","snapshot_observed_at":"2026-08-16T00:27:34.366302Z","title":"SkillGrad: Optimizing Agent Skills Like Gradient Descent.https://arxiv.org/abs/2605.27760, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.366302Z"},"links":{"cited_paper":"/paper/2605.27760","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:a447dde1e8e64eaf785bc220660eeffaefbf6c9b1fbc3a493c546daaf85c81c8","observation_id":"0cb8ddf7-00f0-4ad7-bd92-9ce2401c4a3f","resolution":{"observed_at":"2026-08-16T00:27:34.366302Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.07957","last_updated":"2025-07-10T17:40:11Z","snapshot_observed_at":"2026-08-16T07:12:52.228757Z","submitted_at":"2025-07-10T17:40:11Z","title":"MIRIX: Multi-Agent Memory System for LLM-Based Agents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.07957","snapshot_observed_at":"2026-08-16T00:27:34.370190Z","title":"Mirix: Multi-Agent Memory System for LLM-Based Agents.https://arxiv.org/abs/2507.07957, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.370190Z"},"links":{"cited_paper":"/paper/2507.07957","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:ea39d1b397c9e64b1d00ca40eff6be5cd4e16d0c7f25e775a370e409f83fbb04","observation_id":"efcda376-5ea5-4290-a661-0036a310adcd","resolution":{"observed_at":"2026-08-16T00:27:34.370190Z","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":"2026-08-16T00:27:35.057724Z","title":"MemoryLLM: Towards Self-Updatable Large Language Models","venue":null,"work_id":"0895b9c0-8c6f-485d-bb2c-ee0d9639165b","year":2024},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.373982Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:762f9108fdd560bdf0e3311edc3da389946b16535355b43f54c5b34fb1c202de","observation_id":"cf23e5bc-54c5-4c6a-b561-7576c9b203b6","resolution":{"observed_at":"2026-08-16T00:27:35.062240Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-16T00:27:34.377545Z","title":"G-MemLLM: Gated Latent Memory Augmentation for Long-Context Reasoning in Large Language Models.https://arxiv.org/abs/2602.00015, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.377545Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:6e5ef5a23aca9ee9f11e6bc60b3f5af11dfee8cd69f33b31d111d77cabf64e05","observation_id":"8f0b06bf-da37-44c6-a399-853985fe0ec0","resolution":{"observed_at":"2026-08-16T00:27:34.377545Z","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":"2026-08-16T00:27:35.044987Z","title":"G- Memory: Tracing Hierarchical Memory for Multi-Agent Systems","venue":null,"work_id":"fc039cd2-4e82-422b-a568-d69f843dbb91","year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.380697Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:7c1ab6da55e242d672cce144d09560808abb6f8dbb06ee396fed798da91bcd2b","observation_id":"510afe31-4fcb-443f-9b87-f8039f0c4db9","resolution":{"observed_at":"2026-08-16T00:27:35.049388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-16T00:27:35.033523Z","title":"MemGen: Weaving Generative Latent Memory for Self-Evolving Agents","venue":null,"work_id":"73e7e18e-886f-491f-a0f6-43eb1eb3f934","year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.383512Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:8ea6643944e65879698c86f9d1043711cf14480bf1883c840a6ee1e469b41230","observation_id":"f4099144-e2d2-4722-bf5b-5a7e2184b0ea","resolution":{"observed_at":"2026-08-16T00:27:35.037644Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2512.18746","last_updated":"2025-12-21T14:26:14Z","snapshot_observed_at":"2026-08-13T00:07:33.525517Z","submitted_at":"2025-12-21T14:26:14Z","title":"MemEvolve: Meta-Evolution of Agent Memory Systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2512.18746","snapshot_observed_at":"2026-08-16T00:27:34.386384Z","title":"MemEvolve: Meta-Evolution of Agent Memory Systems","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.386384Z"},"links":{"cited_paper":"/paper/2512.18746","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:1f4c7a78f955e981990958e181db57bd9e5f24dc6428462b4efe7af383e6d7d6","observation_id":"10add27a-e89a-4e26-a62e-e3fab8e00419","resolution":{"observed_at":"2026-08-16T00:27:34.386384Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2602.02474","last_updated":"2026-05-24T19:01:09Z","snapshot_observed_at":"2026-08-03T05:25:38.558727Z","submitted_at":"2026-02-02T18:53:28Z","title":"MemSkill: Learning and Evolving Memory Skills for Self-Evolving Agents","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2602.02474","snapshot_observed_at":"2026-08-16T00:27:34.389654Z","title":"MemSkill: Learning and Evolving Memory Skills for Self-Evolving Agents","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.389654Z"},"links":{"cited_paper":"/paper/2602.02474","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:057ad78606c55088639c332b59ffdbebb275eac04deff72fc1be05e0e528584a","observation_id":"dc0c45b5-da1f-4b2f-81bc-81d670efd570","resolution":{"observed_at":"2026-08-16T00:27:34.389654Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.03192","last_updated":"2026-02-12T05:43:57Z","snapshot_observed_at":"2026-08-19T10:43:51.970075Z","submitted_at":"2026-01-06T17:14:50Z","title":"MemRL: Self-Evolving Agents via Runtime Reinforcement Learning on Episodic Memory","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.03192","snapshot_observed_at":"2026-08-16T00:27:34.393027Z","title":"MemRL: Self-Evolving Agents via Runtime Reinforcement Learning on Episodic Memory","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.393027Z"},"links":{"cited_paper":"/paper/2601.03192","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:0852050fddd62d32d8676020760fdc33cf441712fbc6af8709df444a1e63b986","observation_id":"088f4ee3-bd1a-45d2-ac21-d21549b807d0","resolution":{"observed_at":"2026-08-16T00:27:34.393027Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.15877","last_updated":"2026-06-25T10:23:51Z","snapshot_observed_at":"2026-08-11T10:56:12.400638Z","submitted_at":"2026-04-17T09:26:25Z","title":"Experience Compression Spectrum: Unifying Memory, Skills, and Rules in LLM Agents","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.15877","snapshot_observed_at":"2026-08-16T00:27:34.396387Z","title":"Experience Compression Spectrum: Unifying Memory, Skills, and Rules in LLM Agents","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.396387Z"},"links":{"cited_paper":"/paper/2604.15877","citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:7c8caa08b6b274d614227a2b5fd280ddd8177989f53606b55b395c069b151126","observation_id":"85417cb2-154d-4597-9ea7-b128cb8a26bd","resolution":{"observed_at":"2026-08-16T00:27:34.396387Z","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":"2026-08-16T00:27:35.020877Z","title":"A Survey on the Memory Mechanism of Large Language Model- based Agents.ACM Transactions on Information Systems, 2025","venue":null,"work_id":"97ea0ccd-fee8-48ba-916d-9da8b5f74ac8","year":2025},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.399962Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:8ace3a1a10fda712f664275d373cb0517e7cfb6d597500842ec4a149cf919b44","observation_id":"2f019dd1-eec6-41a0-bded-43e7dbea14e1","resolution":{"observed_at":"2026-08-16T00:27:35.025838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-16T00:27:34.403462Z","title":"ExpeL: LLM Agents Are Experiential Learners","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.403462Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:8eb8221e90da5f1e39315e5b97a82822b6e464e9e70f5fbb3bfd532007b5201b","observation_id":"5215b1b1-a0d4-48ed-9cb6-b21d95cd9b78","resolution":{"observed_at":"2026-08-16T00:27:34.403462Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T00:27:34.406741Z","title":"entity type","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T00:27:34.406741Z"},"links":{"citing_paper":"/paper/2608.12428"},"observation_digest":"sha256:10ddd8cc712a0ba6cca00d5f23c70411d3a5ab9fcdc50213c1b02452c6cc8644","observation_id":"dd0c338e-bc9a-4fdb-87a1-b7bba146746a","resolution":{"observed_at":"2026-08-16T00:27:34.406741Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.12428","last_updated":"2026-08-12T11:29:49Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-20T06:38:29.970148Z","submitted_at":"2026-08-12T11:29:49Z","title":"MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":19,"verified_exact":5,"verified_fuzzy":14},"total_outbound_references":38},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2608.12428."}