{"as_of":"2026-08-05T12:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9348b27446c9847a47d28a7d609ec8e4dfb5a20db8e02162d45c2111cf9fd333","coverage":[{"denominator":69,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":69,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-11T11:50:26.030339Z","state":"measured"},{"denominator":69,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":69,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+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/2605.21463/citation-record","integrity":"/paper/2605.21463/integrity","json":"/paper/2605.21463/citation-record.json","paper":"/paper/2605.21463"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.04697","last_updated":"2025-10-03T01:55:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-06T18:43:29Z","title":"L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2503.04697","doi":"10.48550/arxiv.2503.04697","metadata_source":"pith","pith_arxiv_id":"2503.04697","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning","venue":"cs.CL","work_id":"ad7236fb-3752-48a9-b782-a384899c45a0","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2503.04697","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:864b0800aa40f1be4848ba9cf810b469a762745fc68f52f112ff607f308f3fa3","observation_id":"312bb44a-2a3e-4037-8b2b-3602306f0a2f","resolution":{"observed_at":"2026-05-21T04:29:34.591072Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.11511","last_updated":"2023-10-17T18:18:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-17T18:18:32Z","title":"Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection","version":1},"cited_work":{"arxiv_id":"2310.11511","doi":"10.48550/arxiv.2310.11511","metadata_source":"pith","pith_arxiv_id":"2310.11511","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection","venue":"cs.CL","work_id":"7316de4a-d07d-41de-88ee-509f9b52e462","year":2023},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2310.11511","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:86db7b08a9d90cefe80236d0cc564c9f980941b16bd0e67853640ba386fbe291","observation_id":"cc1801bd-ad24-4362-80db-05facfbb7a65","resolution":{"observed_at":"2026-05-21T04:29:34.534193Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2511.06449","doi":"10.48550/arxiv.2511.06449","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Flex: Continuous agent evolution via forward learning from experience","venue":"ArXiv.org","work_id":"20c70353-cdc5-4bb5-806a-59181ff4fbdf","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:5cfcb7b91e1d9804dc228836caa20ca81ca97d6d682f96cda6f7671bb51c6a06","observation_id":"1b474ce2-bcc6-4061-95ae-4f47d49713ea","resolution":{"observed_at":"2026-05-21T04:29:34.594070Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2508.09874","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Memory decoder: A pretrained, plug-and-play memory for large language models","venue":null,"work_id":"7161188c-2b7f-45d1-95b5-a9c0dc745f54","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:cdca2aefaf282da562ab3475722728cea6c42fdf84024048a0238111f601bd46","observation_id":"fb66120c-9f44-4228-85e9-5786d2b47748","resolution":{"observed_at":"2026-05-21T04:29:34.486873Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.07372","last_updated":"2026-07-12T07:41:31Z","snapshot_observed_at":"2026-08-03T11:11:06.036270Z","submitted_at":"2026-01-12T09:54:49Z","title":"Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models","version":2},"cited_work":{"arxiv_id":"2601.07372","doi":"10.48550/arxiv.2601.07372","metadata_source":"pith","pith_arxiv_id":"2601.07372","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models","venue":"cs.CL","work_id":"942d7453-d7f7-4ad9-8180-e04bd226f6e5","year":2026},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2601.07372","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:c6638c1a14b1c564b3626f5a768a29a444aa3ec13db8847f07e7e1320ded9e18","observation_id":"86108285-99c7-4b9d-9248-cae1b1d44b70","resolution":{"observed_at":"2026-05-21T04:29:34.555281Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Adapting language models to compress contexts","venue":null,"work_id":"4838cc1a-0ea0-450e-95e7-657baf2e5174","year":2023},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:a397c921a355bd88b258127e8250dc50856d50b09788ff323aef5bd08c7e63b2","observation_id":"7b3af8db-c674-4aa7-91c9-b3ea1a97e2c2","resolution":{"observed_at":"2026-05-21T09:54:58.626358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2023.emnlp-main.232","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"doi: 10.18653/v1/2023.emnlp-main.232","venue":null,"work_id":"966a76d3-d6e7-47b5-bb59-10fe95a34b1a","year":2023},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:5a8e63aa4cf38bfa94601e685e55aec947edfe669ccb553832ce210caf108b39","observation_id":"8dce04ad-5e8f-4610-8096-1cdf1fcbb3c4","resolution":{"observed_at":"2026-05-21T04:29:34.098063Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-02T00:08:08.874208+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-02T00:08:08.874208+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.19413","last_updated":"2025-04-28T01:46:35Z","snapshot_observed_at":"2026-08-02T07:32:11.339534Z","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":"2504.19413","doi":"10.48550/arxiv.2504.19413","metadata_source":"pith","pith_arxiv_id":"2504.19413","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory","venue":"cs.CL","work_id":"a5aed26c-a248-48b6-a59e-f7693fcb180a","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2504.19413","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:e4ad8ed64fe52464664f3bac586a1b12b750565f8cebf614837e876a350a010c","observation_id":"551a2523-d7a2-40bb-99a1-4852e44eed21","resolution":{"observed_at":"2026-05-21T04:29:34.588107Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.11349","last_updated":"2022-07-15T07:15:31Z","snapshot_observed_at":"2026-08-03T15:47:56.044506Z","submitted_at":"2022-05-31T08:43:07Z","title":"Prompt Injection: Parameterization of Fixed Inputs","version":2},"cited_work":{"arxiv_id":"2206.11349","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2206.11349","snapshot_observed_at":"2026-07-01T12:05:43.667075Z","title":"Prompt injection: Parameterization of fixed inputs.arXiv preprint arXiv:2206.11349","venue":null,"work_id":"e8886c3c-6bdf-43af-a2c8-f2b78d9c58f8","year":null},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2206.11349","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:2b7ccb87783eacdebf6175c6e2fba6c030505ec434c8d127016185fab680423a","observation_id":"f62cf1e8-5a06-4e7a-9619-d28433996987","resolution":{"observed_at":"2026-05-21T04:29:34.573397Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.16941","last_updated":"2025-11-14T22:00:03Z","snapshot_observed_at":"2026-07-06T22:30:21.881075Z","submitted_at":"2025-09-21T06:28:17Z","title":"SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?","version":2},"cited_work":{"arxiv_id":"2509.16941","doi":"10.48550/arxiv.2509.16941","metadata_source":"pith","pith_arxiv_id":"2509.16941","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SWE-Bench Pro: Can AI Agents Solve Long-Horizon Software Engineering Tasks?","venue":"cs.SE","work_id":"a561c78a-4b02-4053-a92a-bc5c7c5f6b9b","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2509.16941","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:27f5f7fbe7c03b64baabb11296b16b48abdc2cf0170c84dcd9feb0eba966951a","observation_id":"90a487ad-326a-4460-8376-7407687d6d3c","resolution":{"observed_at":"2026-05-21T04:29:34.576114Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-11T01:50:48.977196+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T01:50:48.977196+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.03359","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Meki: Memory-based expert knowledge injection for efficient llm scaling.arXiv preprint arXiv:2602.03359","venue":null,"work_id":"8021849e-c4ac-42fd-bc6e-b47c9bda4477","year":2026},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:46001a3fdfc4308227fe01b5111f437258084b32dba9745a1f3a697a6f437d12","observation_id":"80861e38-08da-4247-96de-144b74898936","resolution":{"observed_at":"2026-05-21T04:29:34.579167Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2022.acl-long.203","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"doi: 10.18653/v1/2022.acl-long.203","venue":"Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)","work_id":"2c3d5a22-9c3f-45d0-83e1-57baf149ad24","year":2022},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:06aaeddd0f8eb7cae7b3cc504dfef850ea01699789028b25e2eb4e71deae1c71","observation_id":"1cb0b698-2aef-4a47-87b1-7bd284865f63","resolution":{"observed_at":"2026-05-21T04:29:34.089199Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.09559","last_updated":"2024-08-18T17:59:49Z","snapshot_observed_at":"2026-07-06T19:02:11.267510Z","submitted_at":"2024-08-18T17:59:49Z","title":"HiAgent: Hierarchical Working Memory Management for Solving Long-Horizon Agent Tasks with Large Language Model","version":1},"cited_work":{"arxiv_id":"2408.09559","doi":"10.48550/arxiv.2408.09559","metadata_source":"arxiv_reference","pith_arxiv_id":"2408.09559","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Hiagent: Hierarchical working memory management for solving long-horizon agent tasks with large language model","venue":"arXiv (Cornell University)","work_id":"bf5ea8ae-3cb8-49b6-b19b-4a49bbc341e4","year":2024},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2408.09559","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:9aeb7e42c19bf4f81c1c2ebed754bd5fdb84c85ee765b14a0740e5ca6f549b0f","observation_id":"3d79cb01-8b9d-4679-a986-b6cae214b91a","resolution":{"observed_at":"2026-05-21T04:29:34.581992Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2512.13564","last_updated":"2026-01-13T09:33:57Z","snapshot_observed_at":"2026-07-30T04:57:05.391864Z","submitted_at":"2025-12-15T17:22:34Z","title":"Memory in the Age of AI Agents","version":2},"cited_work":{"arxiv_id":"2512.13564","doi":"10.48550/arxiv.2512.13564","metadata_source":"pith","pith_arxiv_id":"2512.13564","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Memory in the Age of AI Agents","venue":"cs.CL","work_id":"1ff75a14-302e-4906-aa86-1f96fbcf12ff","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2512.13564","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:de3c1802eda6a47fc0a1d05f2ba3f9813ef3bdbc13ffe6e1d9fee19e1e39ea15","observation_id":"4feb0c13-c39c-412b-8ab4-eb9e0f80a080","resolution":{"observed_at":"2026-05-21T04:29:34.584663Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.06052","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T10:17:57.832911Z","title":"Rethinking memory mechanisms of foundation agents in the second half","venue":null,"work_id":"639480bb-7fee-4f7e-ac4f-23006d622bd4","year":2026},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:be6c68ba33631384d5e1dc7a070ce53adf7cd98df8fcd48be3c718fb77fc63b2","observation_id":"61aa8d7b-8061-40c9-9176-82d2bebc37c1","resolution":{"observed_at":"2026-05-21T04:29:34.602240Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21276","last_updated":"2024-10-25T17:43:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-10-25T17:43:01Z","title":"GPT-4o System Card","version":1},"cited_work":{"arxiv_id":"2410.21276","doi":"10.1177/15248380231178756","metadata_source":"pith","pith_arxiv_id":"2410.21276","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"GPT-4o System Card","venue":"cs.CL","work_id":"f37bf1c7-4964-4e56-9762-d20da8d9009f","year":2024},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2410.21276","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:203bc348ce2b0fe74f6b3b1d001a0595db0c5287d9a2d619331c83d13bd613d5","observation_id":"464deb64-b592-4ae2-b214-3f102c2fcd34","resolution":{"observed_at":"2026-05-21T04:29:34.596549Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.00398","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Memoryllm: Plug-n-play interpretable feed-forward memory for transformers.arXiv preprint arXiv:2602.00398","venue":null,"work_id":"c09acecb-e7e2-400c-911b-747978ca539a","year":2026},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:b3f0d9385fd2ce53c6b084222562749968e87e3098e6add6ec3b4d613af5967f","observation_id":"83196639-1158-4658-9c55-b46582603ccf","resolution":{"observed_at":"2026-05-21T04:29:34.564089Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Adaptive-RAG: Learning to adapt retrieval-augmented large language models through question complexity","venue":null,"work_id":"32a8d86b-231d-4e85-84ac-74a5ba2bca9b","year":2024},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:d0d95a81940df0833591cbf6528e3417b8948fa09437f5f6b0719eaa40f89d16","observation_id":"c8566de8-bce5-4fd9-8960-1be04e99ab26","resolution":{"observed_at":"2026-05-21T09:54:58.631427Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2024.naacl-long.389","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T02:37:45.989677Z","title":"doi: 10.18653/v1/2024.naacl-long.389","venue":"Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)","work_id":"ea53249c-12d1-4769-8970-91c1761bd133","year":2024},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:fd2627b92bae0ae71be7fb4f24843be87e1719f5534e3a576f269a1f6339f0ee","observation_id":"088047a6-e6db-456b-a8b2-2abec9c9ac9d","resolution":{"observed_at":"2026-05-21T04:29:34.079001Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-11T09:48:58.449544+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T09:48:58.449544+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2023.emnlp-main.495","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T02:37:46.031027Z","title":"doi: 10.18653/v1/2023.emnlp-main.495","venue":"Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing","work_id":"a8d62c13-5705-4432-a83f-351c14d24e32","year":2023},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:eb713d2bfd8bf8909130fd3da9ea05c347e4641f5c9dec48f478841be9b40b07","observation_id":"7d4dd658-c04a-47fa-b6fc-fe84ded2004f","resolution":{"observed_at":"2026-05-21T04:29:34.095247Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-11T09:48:58.218514+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T09:48:58.218514+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.21776","last_updated":"2025-10-13T12:40:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-30T16:25:25Z","title":"WebThinker: Empowering Large Reasoning Models with Deep Research Capability","version":2},"cited_work":{"arxiv_id":"2504.21776","doi":"10.48550/arxiv.2504.21776","metadata_source":"pith","pith_arxiv_id":"2504.21776","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"WebThinker: Empowering Large Reasoning Models with Deep Research Capability","venue":"cs.CL","work_id":"7e319d34-eb88-4ea9-8c0d-b66320599f98","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2504.21776","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:315dfd15fb0ac8e86b460e710c6f92eaf831606e026fa8366d248d7dc2614114","observation_id":"7fcc1b10-983c-46c7-b0a4-7b0695cc202f","resolution":{"observed_at":"2026-05-21T04:29:34.560918Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2602.02556","last_updated":"2026-04-24T18:39:50Z","snapshot_observed_at":"2026-07-06T22:44:09.804048Z","submitted_at":"2026-01-30T13:15:13Z","title":"Beyond Experience Retrieval: Learning to Generate Utility-Optimized Structured Experience for Frozen LLMs","version":2},"cited_work":{"arxiv_id":"2602.02556","doi":null,"metadata_source":"pith","pith_arxiv_id":"2602.02556","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Beyond Experience Retrieval: Learning to Generate Utility-Optimized Structured Experience for Frozen LLMs","venue":"cs.LG","work_id":"295adfbd-5414-45cb-9a65-3fb529020a58","year":2026},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2602.02556","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:ab2912c1144b7bf633eaa2137d70240a5a4e5d4cb9bb200d193f5378a2cac064","observation_id":"25c2de34-8ec8-4c81-a801-306139923872","resolution":{"observed_at":"2026-05-21T04:29:34.599342Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12388","last_updated":"2024-10-17T04:09:09Z","snapshot_observed_at":"2026-07-06T19:34:27.813248Z","submitted_at":"2024-10-16T09:13:23Z","title":"Prompt Compression for Large Language Models: A Survey","version":2},"cited_work":{"arxiv_id":"2410.12388","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.12388","snapshot_observed_at":"2026-07-10T01:36:43.999133Z","title":"Prompt compression for large language models: A survey","venue":"cs.CL","work_id":"6d49b9ce-0ee1-45e1-87e9-91bdae8d7ba1","year":2024},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2410.12388","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:d6230cb55621aaff93202e232ebd296fa7b09ce0cf3aad42de1e2a3fcc173520","observation_id":"9048ecd7-f98f-4a57-8267-382e2e46f0bf","resolution":{"observed_at":"2026-05-21T04:29:34.605265Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.09110","last_updated":"2023-10-01T21:44:23Z","snapshot_observed_at":"2026-08-01T19:14:56.803459Z","submitted_at":"2022-11-16T18:51:34Z","title":"Holistic Evaluation of Language Models","version":2},"cited_work":{"arxiv_id":"2211.09110","doi":"10.1007/bf01194075","metadata_source":"pith","pith_arxiv_id":"2211.09110","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Holistic Evaluation of Language Models","venue":"cs.CL","work_id":"cc02a01e-7218-47dc-8e66-3333e7e4adec","year":2022},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2211.09110","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:f410e9c17ca29526fec4ffa4183b827fef4927dd527d702d65eb60702c51a1d8","observation_id":"e13af09a-84e1-4136-b79d-e9a1ed397257","resolution":{"observed_at":"2026-05-21T04:29:34.608038Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.01990","last_updated":"2025-08-02T12:44:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-31T18:00:29Z","title":"Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems","version":2},"cited_work":{"arxiv_id":"2504.01990","doi":"10.48550/arxiv.2504.01990","metadata_source":"pith","pith_arxiv_id":"2504.01990","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems","venue":"cs.AI","work_id":"984dfe5e-1c5c-4b65-920e-15121a85ee7e","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2504.01990","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:3f480062d4a9628ed5b6768c5ad9f3d5f3b7dc3a7eb8793640482c7725de3e55","observation_id":"d0aa3807-d60a-4138-8c32-9465eff92dee","resolution":{"observed_at":"2026-05-21T04:29:34.611162Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.06292","last_updated":"2024-09-01T00:41:18Z","snapshot_observed_at":"2026-07-06T18:59:43.564435Z","submitted_at":"2024-08-12T16:58:11Z","title":"The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery","version":3},"cited_work":{"arxiv_id":"2408.06292","doi":"10.48550/arxiv.2408.06292","metadata_source":"pith","pith_arxiv_id":"2408.06292","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery","venue":"cs.AI","work_id":"56b6b58d-e73a-4317-896e-36ac5f84e957","year":2024},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2408.06292","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:c5dae97b5518f13d56e24436854897e0c7a2ec37c47b238ac0c2e47c53644398","observation_id":"edca8bb1-366b-4c90-ae5c-1326a7d8a4e7","resolution":{"observed_at":"2026-05-21T04:29:34.558100Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:20.611352+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:20.611352+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.04373","doi":"10.48550/arxiv.2510.04373","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Just-in-time episodic feedback hinter: Leveraging offline knowledge to improve llm agents adaptation.arXiv preprint arXiv:2510.04373","venue":"ArXiv.org","work_id":"f99c8146-6e70-41c6-abdd-7f824c10e9e2","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:2b0ca4caa906c82267dc176194627ff2e8de513ed809064e935a1f394179db51","observation_id":"1c0c1c7a-4733-4eff-b97e-85bff8ef356c","resolution":{"observed_at":"2026-05-21T04:29:34.567587Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"12 Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Gray, et al","venue":null,"work_id":"b64721ff-8924-4df6-878d-e155f24c102f","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:56b10af8808d995bf31f66f30b672bc952c2d272b8ae155432a915e5ad0d9b2e","observation_id":"be697800-a58a-41e2-830c-8f42378c6e02","resolution":{"observed_at":"2026-05-21T09:54:58.639185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2509.25140","last_updated":"2026-03-16T20:49:28Z","snapshot_observed_at":"2026-08-02T12:08:17.149184Z","submitted_at":"2025-09-29T17:51:03Z","title":"ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory","version":2},"cited_work":{"arxiv_id":"2509.25140","doi":"10.48550/arxiv.2509.25140","metadata_source":"pith","pith_arxiv_id":"2509.25140","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ReasoningBank: Scaling Agent Self-Evolving with Reasoning Memory","venue":"cs.AI","work_id":"551218b8-a306-4c1e-8795-6232cc30192b","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2509.25140","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:6942a07e65f81d75cb74ecf786869bde415a811b76739ed6d457d22f8bf2fe10","observation_id":"93c03a89-ce02-4866-8bc5-00b7bd8ce4a9","resolution":{"observed_at":"2026-05-21T04:29:34.477632Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:34.995342+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:34.995342+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08560","last_updated":"2024-02-12T18:59:46Z","snapshot_observed_at":"2026-08-03T06:31:15.541423Z","submitted_at":"2023-10-12T17:51:32Z","title":"MemGPT: Towards LLMs as Operating Systems","version":2},"cited_work":{"arxiv_id":"2310.08560","doi":"10.48550/arxiv.2310.08560","metadata_source":"pith","pith_arxiv_id":"2310.08560","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"MemGPT: Towards LLMs as Operating Systems","venue":"cs.AI","work_id":"2698f5ad-c84c-40ca-b839-0912dae10ba2","year":2023},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2310.08560","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:d1f5e60b5fe78f97053502624db2353c4be5abf7e0a7f5cdde2cdcda376d3cef","observation_id":"a5f980ef-88fa-4e8f-98a4-468aa3d469ff","resolution":{"observed_at":"2026-05-21T04:29:34.549869Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-13T15:49:35.543803+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T15:49:35.543803+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.14249","last_updated":"2026-02-20T04:23:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-24T05:27:46Z","title":"Humanity's Last Exam","version":10},"cited_work":{"arxiv_id":"2501.14249","doi":"10.1038/s41586-025-09962-4","metadata_source":"pith","pith_arxiv_id":"2501.14249","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Humanity's Last Exam","venue":"cs.LG","work_id":"59ea00d4-16a8-45e1-aafc-290a6f91d9f4","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2501.14249","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:83d23e743cc0c7d9f5abe0df9c83bfd853e3fd1401af2285e68f2786774e2082","observation_id":"44febb33-f0d7-4420-ab98-4504b38966b1","resolution":{"observed_at":"2026-05-21T04:29:34.546945Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-03T22:08:32.844211+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-03T22:08:32.844211+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.02337","last_updated":"2025-01-27T11:56:15Z","snapshot_observed_at":"2026-07-06T19:45:00.034364Z","submitted_at":"2024-11-04T17:59:58Z","title":"WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learning","version":3},"cited_work":{"arxiv_id":"2411.02337","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.02337","snapshot_observed_at":"2026-07-04T17:20:00.041093Z","title":"Webrl: Training llm web agents via self-evolving online curriculum reinforcement learning","venue":null,"work_id":"ceab60f7-8cb0-4202-b6d8-973b47e933fc","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2411.02337","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:5f808b1a1f6de024c831ee51e008349474c46b82d5628e3f1494e6134a854035","observation_id":"6e5bcc9a-5671-4435-ad9f-e72c017169f0","resolution":{"observed_at":"2026-05-21T04:29:34.490134Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.05591","last_updated":"2025-04-09T09:09:37Z","snapshot_observed_at":"2026-07-06T19:12:32.037156Z","submitted_at":"2024-09-09T13:20:31Z","title":"MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Retrieval Augmentation","version":3},"cited_work":{"arxiv_id":"2409.05591","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2409.05591","snapshot_observed_at":"2026-07-03T20:08:56.368210Z","title":"arXiv preprint arXiv:2409.05591 (2024)","venue":null,"work_id":"1978623a-00e1-4c49-899e-f65a8cb0c9e3","year":2024},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2409.05591","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:91a8df151ae4d207dfb3d5f30ddca5170e11e7b683bae9e2d872f9fca9ce4a0e","observation_id":"d4fe3471-980b-4f19-a533-dff0997e846b","resolution":{"observed_at":"2026-05-21T04:29:34.483693Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12326","last_updated":"2025-01-21T17:48:10Z","snapshot_observed_at":"2026-07-06T20:23:58.426780Z","submitted_at":"2025-01-21T17:48:10Z","title":"UI-TARS: Pioneering Automated GUI Interaction with Native Agents","version":1},"cited_work":{"arxiv_id":"2501.12326","doi":"10.48550/arxiv.2501.12326","metadata_source":"pith","pith_arxiv_id":"2501.12326","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"UI-TARS: Pioneering Automated GUI Interaction with Native Agents","venue":"cs.AI","work_id":"0bbcf263-a46d-4525-a438-11fce3316568","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2501.12326","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:0cd72b8efdaf334566f88c83a0624fd5eec98abc509b27a74dec9c6b46e95ba0","observation_id":"efcae764-fab3-4767-99e5-197a54133da8","resolution":{"observed_at":"2026-05-21T04:29:34.540197Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-05-19T22:22:19.638951+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-19T22:22:19.638951+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Agent laboratory: Using LLM agents as research assistants","venue":null,"work_id":"7d8534c9-f797-4186-8168-2065b9def22c","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:b69065fe535dc77ba424314421e5bef5aab9baf32e702fa316f1e1e15ddc9309","observation_id":"f51fc5c6-5c23-4e67-a98f-e16d9c9db87a","resolution":{"observed_at":"2026-05-21T09:54:58.621490Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2025.findings-emnlp.320","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Agent laboratory: Using LLM agents as research assistants","venue":null,"work_id":"11e386dd-1235-4d81-ba06-dd0717cd145b","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:fa9ad5529c2678b902a9c7bb900d852132ef18265b8789c0917a6ba97dfab9c5","observation_id":"cd383ede-953f-42a5-8860-191f405a75df","resolution":{"observed_at":"2026-05-21T04:29:34.073694Z","resolver_source":"doi","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03300","last_updated":"2024-04-27T15:25:53Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-05T18:55:32Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","version":3},"cited_work":{"arxiv_id":"2402.03300","doi":"10.1016/0004-3702(73)90011-8","metadata_source":"pith","pith_arxiv_id":"2402.03300","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","venue":"cs.CL","work_id":"c5006563-f3ec-438a-9e35-b7b484f34828","year":2024},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2402.03300","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:af192650e47d69d4677a4e5062a284e3895f5560ed0cbbe8f5dd4a211087a7a4","observation_id":"1a65fa3e-a8c4-4a07-a499-d3f2afe1ca6b","resolution":{"observed_at":"2026-05-21T04:29:34.552589Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.03509","last_updated":"2026-06-22T21:27:19Z","snapshot_observed_at":"2026-08-03T13:00:48.590322Z","submitted_at":"2026-01-07T01:43:25Z","title":"Evolving Programmatic Skill Networks","version":2},"cited_work":{"arxiv_id":"2601.03509","doi":null,"metadata_source":"pith","pith_arxiv_id":"2601.03509","snapshot_observed_at":"2026-07-02T20:57:23.181234Z","title":"Evolving programmatic skill networks.arXiv preprint arXiv:2601.03509","venue":"cs.AI","work_id":"fe31832c-58a9-4e80-9fea-f1929c679b20","year":2026},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2601.03509","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:11878461bcc89f6d02e5a0a6e9762adeffddb3465d6c62f279c8e339904b5961","observation_id":"f41d3e8b-4fd9-4cf8-8727-53b7181d86ee","resolution":{"observed_at":"2026-06-24T01:14:24.490580Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.03768","last_updated":"2021-03-14T22:44:38Z","snapshot_observed_at":"2026-07-06T10:02:33.297722Z","submitted_at":"2020-10-08T05:13:36Z","title":"ALFWorld: Aligning Text and Embodied Environments for Interactive Learning","version":2},"cited_work":{"arxiv_id":"2010.03768","doi":"10.1109/cvpr.2001.990517","metadata_source":"pith","pith_arxiv_id":"2010.03768","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"ALFWorld: Aligning Text and Embodied Environments for Interactive Learning","venue":"cs.CL","work_id":"fa436f46-ec0a-4d2e-a0ff-e697def4a7be","year":2020},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2010.03768","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:1108d4dfd8b2ca5c9adb82a913accc87e45724ef6cbc1b67e31ca3c1279d9cdb","observation_id":"deb1ccc5-0ea0-41e9-a570-485e1174ca45","resolution":{"observed_at":"2026-05-21T04:29:34.537078Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-05-20T11:23:33.289391+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-20T11:23:33.289391+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.02427","last_updated":"2024-03-15T15:44:11Z","snapshot_observed_at":"2026-08-03T00:38:27.580701Z","submitted_at":"2023-09-05T17:56:20Z","title":"Cognitive Architectures for Language Agents","version":3},"cited_work":{"arxiv_id":"2309.02427","doi":"10.1145/3531146.3533088","metadata_source":"pith","pith_arxiv_id":"2309.02427","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Cognitive Architectures for Language Agents","venue":"cs.AI","work_id":"af5e610e-9c97-4573-81ca-fd8532e60568","year":2023},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2309.02427","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:1f26e177eb4e785aad3df9e735222f8a7429167c9e90757f90af48f184d95c69","observation_id":"eba811d7-d915-4360-bc68-5345427a3e79","resolution":{"observed_at":"2026-05-21T04:29:34.525026Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-13T07:49:43.581412+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T07:49:43.581412+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.14387","last_updated":"2024-06-03T17:47:30Z","snapshot_observed_at":"2026-07-06T18:03:51.687441Z","submitted_at":"2024-04-22T17:43:23Z","title":"A Survey on Self-Evolution of Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.14387","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.14387","snapshot_observed_at":"2026-07-04T10:59:47.067283Z","title":"arXiv preprint arXiv:2404.14387 , year=","venue":null,"work_id":"ffd0559d-37d0-4858-8aaa-84dc7e4a3541","year":2024},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2404.14387","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:809496d621e215c3906f6babe73d0b919a6f0d188edd58207d9194779199eb70","observation_id":"61da0936-50ee-4d01-b592-894f02abaabb","resolution":{"observed_at":"2026-05-21T04:29:34.528489Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":"2312.11805","doi":"10.1038/nrn2888","metadata_source":"pith","pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Gemini: A Family of Highly Capable Multimodal Models","venue":"cs.CL","work_id":"83f7c85b-3f11-450f-ac0c-64d9745220b2","year":2023},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:723d6f0bd934fe21c5e1fb6b1cb22fb9074f89c9bfb0776d25928767007c268c","observation_id":"2bd32ea4-a4d8-4e99-9df2-3228ac1eb11a","resolution":{"observed_at":"2026-05-21T04:29:34.522144Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Xing W, Guangyuan Ma, Wanhui Qian, Zijia Lin, and Songlin Hu","venue":null,"work_id":"bae7081f-f828-4c11-a51f-361482037219","year":2023},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:4d7e058ba50b5ea72c319d563d9c7827056c3857dda82f6cc85a3e742110a8ed","observation_id":"7330f1ad-85d0-45e2-b17b-b1d2d1eedfc1","resolution":{"observed_at":"2026-05-21T09:54:58.646997Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16291","last_updated":"2023-10-19T16:27:03Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-25T17:46:38Z","title":"Voyager: An Open-Ended Embodied Agent with Large Language Models","version":2},"cited_work":{"arxiv_id":"2305.16291","doi":"10.18653/v1/2023.emnlp-main.118","metadata_source":"pith","pith_arxiv_id":"2305.16291","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Voyager: An Open-Ended Embodied Agent with Large Language Models","venue":"cs.AI","work_id":"ffe0d207-86cf-4742-a100-e988ac8b9676","year":2023},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-07-11T11:50:26.030339Z"},"links":{"cited_paper":"/paper/2305.16291","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:230144100752eb8a7dd54e591e60b4f80ec22df04dc84e67898372cfc0278b47","observation_id":"727b705d-3a59-461b-8304-397419947130","resolution":{"observed_at":"2026-05-21T04:29:34.076746Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Oscar: Operating system control via state-aware reasoning and re-planning","venue":null,"work_id":"3b2c5606-2202-4e91-b4b8-b4da9afe10ee","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:f8e6c8bf69ae58e5c5fc0387bd4a0210b13d0f5a6d479b140e11b4735ac13652","observation_id":"4079ff31-052a-47d0-8218-161c1bf4516c","resolution":{"observed_at":"2026-05-21T09:54:58.636381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2025.findings-acl.235","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"R3Mem: Bridging memory retention and retrieval via reversible compression","venue":null,"work_id":"37256596-f033-44f7-a880-b85b299210c3","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:0692cb6f01211c010471dd8f4961453d54e5fb54356c6fd81ef2ba996b7c21a7","observation_id":"40fa7d1c-bf01-4078-bdf2-7ca6d7c2c42e","resolution":{"observed_at":"2026-05-21T04:29:34.081895Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2025.emnlp-main.401","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Agent workflow memory","venue":null,"work_id":"41eb3807-be75-414a-8e90-424ade702c77","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:5751f9e2ec9963ebb1fa5c2900fddaea859bd84fac753222b4827ee3a99b90f8","observation_id":"75de96d9-72be-42aa-8a7b-71a813566dcc","resolution":{"observed_at":"2026-05-21T04:29:34.086946Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-11T02:50:24.938453+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T02:50:24.938453+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2510.16079","last_updated":"2026-05-16T02:57:47Z","snapshot_observed_at":"2026-08-05T00:54:36.690304Z","submitted_at":"2025-10-17T12:03:16Z","title":"EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle","version":3},"cited_work":{"arxiv_id":"2510.16079","doi":"10.48550/arxiv.2510.16079","metadata_source":"pith","pith_arxiv_id":"2510.16079","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"EvolveR: Self-Evolving LLM Agents through an Experience-Driven Lifecycle","venue":"cs.CL","work_id":"350af93c-7749-4477-8163-e35d2cac8d96","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-07-11T11:50:26.030339Z"},"links":{"cited_paper":"/paper/2510.16079","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:bd255b99253ecc26000ea03fcdafa06e010b41c9ec670c70666d5619767e36aa","observation_id":"ba136fe7-fcce-4f87-aecc-280051cfae82","resolution":{"observed_at":"2026-05-21T04:29:34.084876Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.05832","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T22:08:58.635086Z","title":"Ui-mem: Self-evolving experience memory for online reinforcement learning in mobile gui agents","venue":null,"work_id":"74d6ec92-8265-49da-b322-30236d8cec10","year":2026},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:04334a6072cebbca1b68041698c7accdf7a9bcc11b8f0ef2f047a0e2d040e0c2","observation_id":"5057d63a-7fc3-480e-aec8-5d5fc5e6ecf3","resolution":{"observed_at":"2026-05-21T04:29:34.513738Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12110","last_updated":"2025-10-08T01:46:37Z","snapshot_observed_at":"2026-08-03T02:27:06.991396Z","submitted_at":"2025-02-17T18:36:14Z","title":"A-MEM: Agentic Memory for LLM Agents","version":11},"cited_work":{"arxiv_id":"2502.12110","doi":"10.48550/arxiv.2502.12110","metadata_source":"pith","pith_arxiv_id":"2502.12110","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A-MEM: Agentic Memory for LLM Agents","venue":"cs.CL","work_id":"3b98feb2-fdb1-479a-bbe4-2c298a4592e2","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2502.12110","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:8e6655ed7d1169da2bbeb5f10c7872e6d248adc77c56f34feea7e4a1d98e66a1","observation_id":"d1a95d4d-8366-4cbc-81da-4eaa7baae434","resolution":{"observed_at":"2026-05-21T04:29:34.516485Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.14287","last_updated":"2026-04-24T09:04:54Z","snapshot_observed_at":"2026-07-06T22:42:19.252543Z","submitted_at":"2026-01-14T04:42:15Z","title":"Chain-of-Memory: Lightweight Memory Construction with Dynamic Evolution for LLM Agents","version":2},"cited_work":{"arxiv_id":"2601.14287","doi":null,"metadata_source":"pith","pith_arxiv_id":"2601.14287","snapshot_observed_at":"2026-07-02T07:36:45.438998Z","title":"Chain-of-Memory: Lightweight Memory Construction with Dynamic Evolution for LLM Agents","venue":"cs.LG","work_id":"4836c44e-bc83-4696-b958-1d6c550bba4c","year":2026},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2601.14287","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:ecffa9618b03315b7218a34f8e2c769d9f0a89c67e98f77ee5c5cd9be4591bfe","observation_id":"2fb5c50b-aa92-43dc-9dc8-7ff6a9cbb893","resolution":{"observed_at":"2026-05-21T04:29:34.510585Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.19828","last_updated":"2026-01-14T14:21:21Z","snapshot_observed_at":"2026-07-06T22:19:28.487854Z","submitted_at":"2025-08-27T12:26:55Z","title":"Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning","version":5},"cited_work":{"arxiv_id":"2508.19828","doi":"10.48550/arxiv.2508.19828","metadata_source":"pith","pith_arxiv_id":"2508.19828","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning","venue":"cs.CL","work_id":"2a070440-2167-4398-be97-c2d4c3ee3541","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2508.19828","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:71cd41e98c4ed214dfb726fa2eda81417287c90af52dc17a1b7f56f35bc3a34d","observation_id":"598af286-bd06-44e3-915c-3c8f2cb1931c","resolution":{"observed_at":"2026-05-21T04:29:34.507653Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-13T15:49:35.802766+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-13T15:49:35.802766+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2601.04463","doi":"10.48550/arxiv.2601.04463","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Beyond static summarization: Proactive memory extraction for llm agents.arXiv preprint arXiv:2601.04463, 2026a","venue":"arXiv (Cornell University)","work_id":"889d7cf3-d566-4af8-91d3-95cfdc032e38","year":2026},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:d280328d54b022f6d7d9e2010f742b675cf55bf54af10f92bfdd4c1136f1aacd","observation_id":"9c55adf1-93d6-4d18-b28e-02e42e73388b","resolution":{"observed_at":"2026-05-21T04:29:34.519452Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Explicit memory learning with expectation maximization","venue":null,"work_id":"4c734401-5cb3-451e-908f-6a1b8f4a1fd8","year":2024},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:de94573ad5b2301e67ad26ecca34b84fbfe7d4c755d91882f6f4c170da8102ab","observation_id":"238ad194-3d5d-4353-8a76-a39d4bfc09b8","resolution":{"observed_at":"2026-05-21T09:54:58.644012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.02259","last_updated":"2026-07-29T12:55:39Z","snapshot_observed_at":"2026-08-01T23:32:07.108143Z","submitted_at":"2025-07-03T03:11:50Z","title":"MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent","version":2},"cited_work":{"arxiv_id":"2507.02259","doi":"10.48550/arxiv.2507.02259","metadata_source":"pith","pith_arxiv_id":"2507.02259","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent","venue":"cs.CL","work_id":"ac66fe72-b869-4874-8a9d-c110b849da0c","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-07-11T11:50:26.030339Z"},"links":{"cited_paper":"/paper/2507.02259","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:c57338af1c1a7815b61ffc20ad9546f3f177042d91b229fe67f8cd02ac91139f","observation_id":"684f54a0-e11f-4830-9bca-afd8e9c0e031","resolution":{"observed_at":"2026-05-21T04:29:34.092106Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.02245","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T20:50:12.357975Z","title":"Exgrpo: Learning to reason from experience.arXiv preprint arXiv:2510.02245","venue":null,"work_id":"792b0eaf-59f4-46a3-a117-ac2ade54fe9b","year":2023},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:70afcde614e25589b715daf6c300575d78b25ed546ac52d0a3b577d5de7129ea","observation_id":"c66a86d1-24f3-4db0-8d45-802e79b7375a","resolution":{"observed_at":"2026-05-21T04:29:34.499041Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2509.24704","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T05:36:01.242136Z","title":"Appagent: Multimodal agents as smartphone users","venue":null,"work_id":"9a080bd6-ce14-4b37-9c10-b026c507a4d7","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:cac2f896d003844bdce4b54d501ace63024fc7b6b113c197cf866314f2c9b6ea","observation_id":"59c1b20a-ff8f-47ac-b15b-4e3b9780ce1e","resolution":{"observed_at":"2026-05-21T04:29:34.501969Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"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":"2404.13501","doi":"10.48550/arxiv.2404.13501","metadata_source":"pith","pith_arxiv_id":"2404.13501","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A Survey on the Memory Mechanism of Large Language Model based Agents","venue":"cs.AI","work_id":"86a3cea2-e600-466a-bf9e-6e737a41ed6a","year":2024},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2404.13501","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:526eb176125b5f6a07412cf3d263a9fc8e30b736dc9ec41909eb22b044e72ef6","observation_id":"e2c553fc-4ebf-4cad-8c9f-2d7b6822a388","resolution":{"observed_at":"2026-05-21T04:29:34.492896Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.11942","last_updated":"2025-05-30T02:28:21Z","snapshot_observed_at":"2026-07-06T21:25:32.619009Z","submitted_at":"2025-05-17T10:09:11Z","title":"LifelongAgentBench: Evaluating LLM Agents as Lifelong Learners","version":3},"cited_work":{"arxiv_id":"2505.11942","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.11942","snapshot_observed_at":"2026-07-04T17:09:59.374964Z","title":"Lifelonga- gentbench: Evaluating llm agents as lifelong learners.arXiv preprint arXiv:2505.11942","venue":null,"work_id":"c834b014-6484-4f50-bc9d-15e598a8890a","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2505.11942","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:b0002baf1e245ba0061f5b120a19f3254372382224c845392ff7bbc0fb669c57","observation_id":"223a33c4-15ec-4e37-a708-32a2b129ae13","resolution":{"observed_at":"2026-05-21T04:29:34.495977Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.08224","last_updated":"2026-04-09T13:19:41Z","snapshot_observed_at":"2026-08-02T22:56:00.067549Z","submitted_at":"2026-04-09T13:19:41Z","title":"Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering","version":1},"cited_work":{"arxiv_id":"2604.08224","doi":"10.48550/arxiv.2604.08224","metadata_source":"pith","pith_arxiv_id":"2604.08224","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering","venue":"cs.SE","work_id":"766ea250-68f3-4ef9-b7fa-b92fd9eba501","year":2026},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2604.08224","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:faf4d88c9d37c7f7ce635c3b73d71fd4a3073ea36ea12de59784b413e83ba61a","observation_id":"dc6ca1a0-d3d2-4653-881f-be170a96d934","resolution":{"observed_at":"2026-05-21T04:29:34.504787Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.16153","last_updated":"2025-08-25T13:32:12Z","snapshot_observed_at":"2026-07-06T22:16:34.442202Z","submitted_at":"2025-08-22T07:25:30Z","title":"Memento: Fine-tuning LLM Agents without Fine-tuning LLMs","version":2},"cited_work":{"arxiv_id":"2508.16153","doi":"10.48550/arxiv.2508.16153","metadata_source":"pith","pith_arxiv_id":"2508.16153","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Memento: Fine-tuning LLM Agents without Fine-tuning LLMs","venue":"cs.LG","work_id":"ed7d69aa-0e41-4f9f-99e1-2dfcbdd515a0","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2508.16153","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:b9f71371af5ec2da9914078dc8a06c5782f2c2cbe957f092049f141b35b43322","observation_id":"a998856b-e58e-45f7-b74c-b801195e126e","resolution":{"observed_at":"2026-05-21T04:29:34.531512Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:34.518715+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:34.518715+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.13854","last_updated":"2024-04-16T15:13:18Z","snapshot_observed_at":"2026-07-06T15:58:31.756298Z","submitted_at":"2023-07-25T22:59:32Z","title":"WebArena: A Realistic Web Environment for Building Autonomous Agents","version":4},"cited_work":{"arxiv_id":"2307.13854","doi":"10.48550/arxiv.2307.13854","metadata_source":"pith","pith_arxiv_id":"2307.13854","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"WebArena: A Realistic Web Environment for Building Autonomous Agents","venue":"cs.AI","work_id":"7058ffd2-a339-4102-89eb-248eeb074652","year":2023},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"cited_paper":"/paper/2307.13854","citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:8ebcce73ef3da3cb792c29f4bb5387dca6c80622cabe71bdc4de03560e534e90","observation_id":"adb9f0e4-f7fd-4388-bf72-368194d0706d","resolution":{"observed_at":"2026-05-21T04:29:34.570483Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-05-20T18:52:18.85917+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-20T18:52:18.85917+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"ba21c353-9763-49e0-8c43-7dbbb13e67e6","year":2024},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:2035da50f5dde6fe0bb2e5fb86ee782ebed3e468011e8f7d612f9ebfaeaaca03","observation_id":"a3452542-cc36-40a8-9e37-71af607a8199","resolution":{"observed_at":"2026-05-21T09:54:58.649378Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"RL training is built on TRL (von Werra et al., 2020), with rollout generation served by vLLM (Kwon et al., 2023).Mem-π is initialized fromQwen2.5-7B-Instruct (Yang et al","venue":null,"work_id":"0dd9373f-983a-4cec-8b77-71fbe886d667","year":2020},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:e06666df1236dc30b154261e4a5b2dd9ac3d600598a85b94d57512e2faa6045b","observation_id":"ef7654e8-6cfa-485b-a624-ec6095300f95","resolution":{"observed_at":"2026-05-21T09:54:58.629211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Optimization uses AdamW with learning rate1×10−6, β1=0.9, β2=0.999, weight decay0, batch size 8tasks per step, and200optimization steps","venue":null,"work_id":"e83c9e9e-35a3-4162-8689-7b1beefeac0b","year":2019},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:c784379c6f5004ebc588cbb86fec6543c1ff1a0113b9b3698e34a4628c80afa9","observation_id":"1c15b008-d7e7-47b0-8b41-0947213c04cf","resolution":{"observed_at":"2026-05-21T09:54:58.624029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Reported numbers are means over three independent seeds","venue":null,"work_id":"5626e7c8-f9eb-4cce-9c27-a33f9d833498","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:253591b19398e9c7e2849dedb76e8a1da81c620a2b66c8800a50ec7c7ce5611f","observation_id":"f5c51be2-8698-44fd-b9ff-1dc70b47814a","resolution":{"observed_at":"2026-05-21T09:54:58.641694Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"What is the top-1 best-selling product in 2022","venue":null,"work_id":"f9287901-d230-402b-8995-ef0fede0f08b","year":2022},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:6967c75c8997d6156675147fb801237ba30fdfcc2fb5037a93e3cb7e5b2b8cfd","observation_id":"58ab5310-63fb-4539-a9d2-dea71a9cc034","resolution":{"observed_at":"2026-05-21T09:54:58.616241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Each entry contains a task query (source_trace_goals in JEF-Hinter (Nekoei et al., 2025)) and the guidance (JEF-Hinter hint) text","venue":null,"work_id":"79d32aed-568e-4796-bc52-bf3cec8e987f","year":2025},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:a6fc8e8bedb7be4abbf4b53296ccb9d15f14d0c7dc3af62e8ccc4e5ac17bd404","observation_id":"4fcdd294-42ba-43f2-8354-66cabe4774f5","resolution":{"observed_at":"2026-05-21T09:54:58.619343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"List the top 3 search terms in my store","venue":null,"work_id":"2e087123-9ecf-4a9a-902d-f7c947a18ef2","year":2023},"citing_paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-21T04:27:25.041652Z"},"links":{"citing_paper":"/paper/2605.21463"},"observation_digest":"sha256:72437df76d8abb6ae84e5f427c874169634f2d6b7b7425b6d34e083a14bad718","observation_id":"9e2f9c0b-9f07-493f-89ba-80c28438bce7","resolution":{"observed_at":"2026-05-21T09:54:58.633632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2605.21463","last_updated":"2026-05-20T17:51:05Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-05-20T17:51:05Z","title":"Mem-$\\pi$: Adaptive Memory through Learning When and What to Generate"},"reference_resolution":{"displayed":69,"state_counts":{"malformed_identifier":0,"metadata_mismatch":5,"parse_uncertain":0,"unresolved":1,"verified_exact":50,"verified_fuzzy":13},"total_outbound_references":69},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2605.21463."}