{"as_of":"2026-08-14T09:02:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c00d383dd34cea51df8ed07a7fe49eb0a6527dfa55bbc9d18c4115e95e0948dd","coverage":[{"denominator":15,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T00:18:54.165282Z","state":"measured"},{"denominator":15,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":15,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2608.08239/citation-record","integrity":"/paper/2608.08239/integrity","json":"/paper/2608.08239/citation-record.json","paper":"/paper/2608.08239"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2605.07112","last_updated":"2026-05-08T01:41:31Z","snapshot_observed_at":"2026-07-06T23:19:30.387067Z","submitted_at":"2026-05-08T01:41:31Z","title":"Switchcraft: AI Model Router for Agentic Tool Calling","version":1},"cited_work":{"arxiv_id":"2605.07112","doi":null,"metadata_source":"pith","pith_arxiv_id":"2605.07112","snapshot_observed_at":"2026-08-12T00:18:54.668561Z","title":"Switchcraft: AI Model Router for Agentic Tool Calling","venue":"cs.AI","work_id":"4320b736-dce9-4d16-ba11-78e64e6db026","year":2026},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.095105Z"},"links":{"cited_paper":"/paper/2605.07112","citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:5c6804f83365fca25c33543f09a72680513e483f7113a80012e6c49e01dce5d9","observation_id":"d36c36fa-dbd6-42eb-8e77-ef705d33ba8e","resolution":{"observed_at":"2026-08-12T00:18:54.674282Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.12031","last_updated":"2024-03-28T17:56:28Z","snapshot_observed_at":"2026-08-09T22:21:33.340392Z","submitted_at":"2024-03-18T17:59:04Z","title":"RouterBench: A Benchmark for Multi-LLM Routing System","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.12031","snapshot_observed_at":"2026-08-12T00:18:54.111313Z","title":"Routerbench: A benchmark for multi- llm routing systems.arXiv preprint arXiv:2403.12031,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.111313Z"},"links":{"cited_paper":"/paper/2403.12031","citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:e3d090cafc990200b8652f5387ef633383d3c3c3d2a5fd7b62f8aadf05fbd070","observation_id":"e5690e71-0c1a-4b56-83af-97dd95198134","resolution":{"observed_at":"2026-08-12T00:18:54.111313Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.10657","last_updated":"2025-05-20T14:59:21Z","snapshot_observed_at":"2026-08-13T09:25:43.676027Z","submitted_at":"2025-03-08T04:07:07Z","title":"RouterEval: A Comprehensive Benchmark for Routing LLMs to Explore Model-level Scaling Up in LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.10657","snapshot_observed_at":"2026-08-12T00:18:54.116775Z","title":"Routereval: A comprehensive benchmark for routing llms to explore model-level scaling up in llms.arXiv preprint arXiv:2503.10657,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.116775Z"},"links":{"cited_paper":"/paper/2503.10657","citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:db004f8c5c9d1de03d8e0ba607b4346d2a40efb92ebc47557b6510156cd3234d","observation_id":"acd73c12-76f2-472b-96cb-804c6265671b","resolution":{"observed_at":"2026-08-12T00:18:54.116775Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.08773","last_updated":"2025-07-22T15:27:33Z","snapshot_observed_at":"2026-08-14T02:29:31.486179Z","submitted_at":"2025-02-12T20:30:28Z","title":"Universal Model Routing for Efficient LLM Inference","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.08773","snapshot_observed_at":"2026-08-12T00:18:54.121405Z","title":"Universal model routing for efficient llm inference.arXiv preprint arXiv:2502.08773,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.121405Z"},"links":{"cited_paper":"/paper/2502.08773","citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:42f89547a147951fbfe147b8a6af43af58b7d58bb38d80a99bf7a7fbc26da752","observation_id":"e8f3a029-e178-4d69-88eb-09b24bd3b99e","resolution":{"observed_at":"2026-08-12T00:18:54.121405Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T00:18:54.135081Z","title":"Routerarena: An open platform for comprehensive comparison of llm routers.arXiv preprint arXiv:2510.00202,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.135081Z"},"links":{"citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:05061e5d5cebf75729e064eeeb9cc53215a4771b3f2d2645dd6277cf2436a406","observation_id":"90abd128-3dec-4217-9494-d7aa174c556d","resolution":{"observed_at":"2026-08-12T00:18:54.135081Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T00:18:54.139092Z","title":"Odar: Principled adaptive routing for llm reasoning via active inference","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.139092Z"},"links":{"citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:eaeb21f194b6029f41be91b254120885f9e4968238c126f2cc4b412a65b898c1","observation_id":"9c2ced0c-2fde-4a61-b8ec-754313d4dd25","resolution":{"observed_at":"2026-08-12T00:18:54.139092Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.18665","last_updated":"2025-02-23T08:50:33Z","snapshot_observed_at":"2026-07-30T15:06:18.011623Z","submitted_at":"2024-06-26T18:10:22Z","title":"RouteLLM: Learning to Route LLMs with Preference Data","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.18665","snapshot_observed_at":"2026-08-12T00:18:54.143606Z","title":"Gonzalez, M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.143606Z"},"links":{"cited_paper":"/paper/2406.18665","citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:b77d2b22688687b4461c300d199cf2e3540ce7bd4bf5c1002db0f65e97420d21","observation_id":"b5cfd66b-ea8c-41a7-9d32-a05164ad4746","resolution":{"observed_at":"2026-08-12T00:18:54.143606Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.19435","last_updated":"2025-05-26T02:53:17Z","snapshot_observed_at":"2026-08-14T03:12:01.680185Z","submitted_at":"2025-05-26T02:53:17Z","title":"Route to Reason: Adaptive Routing for LLM and Reasoning Strategy Selection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.19435","snapshot_observed_at":"2026-08-12T00:18:54.149064Z","title":"Route to reason: Adaptive routing for llm and reasoning strategy selection.arXiv preprint arXiv:2505.19435,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.149064Z"},"links":{"cited_paper":"/paper/2505.19435","citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:e6d05a9fa2ae245a2b273649ac2f9776c71b2a1c80700de46cc6f92df6261e7e","observation_id":"5b8145ba-adce-4712-9048-a90929237e80","resolution":{"observed_at":"2026-08-12T00:18:54.149064Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.09388","last_updated":"2025-05-14T13:41:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-14T13:41:34Z","title":"Qwen3 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.09388","snapshot_observed_at":"2026-08-12T00:18:54.159441Z","title":"Qwen3 technical report.arXiv preprint arXiv:2505.09388,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.159441Z"},"links":{"cited_paper":"/paper/2505.09388","citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:fcf2860ed587c5c029f7fc8a902a7eb5470911526234eb71eb2a0243938286e4","observation_id":"13092041-523f-4119-9c43-b263d655017b","resolution":{"observed_at":"2026-08-12T00:18:54.159441Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.18859","last_updated":"2026-05-22T02:55:33Z","snapshot_observed_at":"2026-08-02T11:54:59.984785Z","submitted_at":"2026-05-14T08:58:59Z","title":"TwinRouterBench: Fast Static and Live Dynamic Evaluation for Realistic Agentic LLM Routing","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.18859","snapshot_observed_at":"2026-08-12T00:18:54.165282Z","title":"Twinrouterbench: Fast static and live dynamic evaluation for realistic agentic llm routing.arXiv preprint arXiv:2605.18859,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.165282Z"},"links":{"cited_paper":"/paper/2605.18859","citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:bcabd97c3b9c5e95ed7994b3ced6248148f3d6858c7a66ed74bf45b711e6a631","observation_id":"80955fb7-5ad3-486f-902c-838badcf76d9","resolution":{"observed_at":"2026-08-12T00:18:54.165282Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.27151","last_updated":"2026-04-29T19:59:36Z","snapshot_observed_at":"2026-08-11T13:33:53.477733Z","submitted_at":"2026-04-29T19:59:36Z","title":"Step-level Optimization for Efficient Computer-use Agents","version":1},"cited_work":{"arxiv_id":"2604.27151","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.27151","snapshot_observed_at":"2026-08-12T00:18:54.233418Z","title":"Step-level Optimization for Efficient Computer-use Agents","venue":"cs.AI","work_id":"018f5709-b3f6-4d22-916d-66a4128fdcb1","year":2026},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.154484Z"},"links":{"cited_paper":"/paper/2604.27151","citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:d595baa9df2f9ff4ee2aa9bfa59b0cbf8fa60b0c89daa6105e4cca8e72817902","observation_id":"025e749e-fa89-470a-84e5-2907cecea79d","resolution":{"observed_at":"2026-08-12T00:18:54.240259Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2606.18774","last_updated":"2026-06-19T09:33:33Z","snapshot_observed_at":"2026-08-14T02:19:39.374269Z","submitted_at":"2026-06-17T07:35:10Z","title":"RouteJudge: An Open Platform for Reproducible and Preference-Aware LLM Routing","version":2},"cited_work":{"arxiv_id":"2606.18774","doi":null,"metadata_source":"pith","pith_arxiv_id":"2606.18774","snapshot_observed_at":"2026-08-12T00:18:54.568925Z","title":"RouteJudge: An Open Platform for Reproducible and Preference-Aware LLM Routing","venue":"cs.LG","work_id":"90e00641-7e7f-412c-895c-688a2804d2db","year":2026},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.126620Z"},"links":{"cited_paper":"/paper/2606.18774","citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:4055154e4db2529901541c8de6e851982a937d468bae27387eda63459fadb644","observation_id":"042ff5c3-d06e-4ba3-928b-45ff557256b5","resolution":{"observed_at":"2026-08-12T00:18:54.573778Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.05176","last_updated":"2023-05-09T05:11:02Z","snapshot_observed_at":"2026-08-10T11:59:11.481480Z","submitted_at":"2023-05-09T05:11:02Z","title":"FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.05176","snapshot_observed_at":"2026-08-12T00:18:54.106043Z","title":"Frugalgpt: How to use large language models while reducing cost and improving performance.arXiv preprint arXiv:2305.05176,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.106043Z"},"links":{"cited_paper":"/paper/2305.05176","citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:9e22dd0e541cd54acd70bec5e670fe8c75c512e2fb06d35bb38ec04850bf25b5","observation_id":"bd504762-ced5-400c-9089-1abeb2024d29","resolution":{"observed_at":"2026-08-12T00:18:54.106043Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T00:18:54.685488Z","title":"Session-aware agentic routing: Continuity- aware model selection for long-horizon llm agents","venue":null,"work_id":"c0f6ac3c-fde4-4e23-9e65-b2597ab53a33","year":2026},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.131034Z"},"links":{"citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:b373a7e7ecf19d4d3467b6db3d871a0b044e59d09a4076a8d92d9e67527adc81","observation_id":"c823f036-d0cf-4726-b02c-791109e2997b","resolution":{"observed_at":"2026-08-12T00:18:54.690524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.12963","last_updated":"2025-01-19T15:59:56Z","snapshot_observed_at":"2026-08-13T05:45:09.919925Z","submitted_at":"2023-10-19T17:57:39Z","title":"AutoMix: Automatically Mixing Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.12963","snapshot_observed_at":"2026-08-12T00:18:54.100605Z","title":"Automix: Automatically mixing language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World","version":1},"reference_index":2026,"source":"pdf_text","source_observed_at":"2026-08-12T00:18:54.100605Z"},"links":{"cited_paper":"/paper/2310.12963","citing_paper":"/paper/2608.08239"},"observation_digest":"sha256:6f6953d4db00d1de80e0af208bb5931d48e8975c5acb8cf8fa0ac7dbf53d0997","observation_id":"4c00d2ec-c5f4-474b-b92c-311bbc0ed06e","resolution":{"observed_at":"2026-08-12T00:18:54.100605Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.08239","last_updated":"2026-08-08T17:07:11Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T03:23:31.907906Z","submitted_at":"2026-08-08T17:07:11Z","title":"The Replay Gap: Static Evaluation of Model Switching in LLM Agents Scores the Wrong World"},"reference_resolution":{"displayed":15,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":3,"verified_fuzzy":1},"total_outbound_references":15},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2608.08239."}