{"as_of":"2026-08-11T05:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d6ad32ef559ea1825fd5a1a905833090466b7244e0ff97c4772b453cc8405424","coverage":[{"denominator":54,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":54,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-11T01:15:07.381414Z","state":"measured"},{"denominator":54,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":54,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2605.07180/citation-record","integrity":"/paper/2605.07180/integrity","json":"/paper/2605.07180/citation-record.json","paper":"/paper/2605.07180"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-05T21:51:27.755715Z","title":"The Thirty-ninth Annual Conference on Neural Information Processing Systems , year=","venue":null,"work_id":"a5d1229f-36c7-479d-bb24-6594659eb068","year":null},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:bcff2e89ad6054a5a78567900bc4058bbd0c3eff93b002abd8512d58f958bc9d","observation_id":"c1620208-5942-4ed4-af01-10994f6007a0","resolution":{"observed_at":"2026-05-14T17:12:30.337972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.11133","last_updated":"2025-02-16T14:00:59Z","snapshot_observed_at":"2026-08-07T18:14:45.344327Z","submitted_at":"2025-02-16T14:00:59Z","title":"MasRouter: Learning to Route LLMs for Multi-Agent Systems","version":1},"cited_work":{"arxiv_id":"2502.11133","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.11133","snapshot_observed_at":"2026-07-10T14:17:10.110073Z","title":"Masrouter: Learning to route llms for multi-agent systems.arXiv preprint arXiv:2502.11133","venue":"cs.LG","work_id":"90519480-2dd6-4046-b59f-741aebc42737","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2502.11133","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:1df20595b3446431bff951ac672b6e0f9f6c1e84390ffbb02f5a7bcfbc02f222","observation_id":"0439b031-9c94-4654-9ed4-3460999fc7a7","resolution":{"observed_at":"2026-05-11T04:35:57.609237Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.05445","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T06:07:41.649239Z","title":"Agentrouter: A knowledge-graph-guided llm router for collaborative multi-agent question answering","venue":null,"work_id":"026ed52b-9e45-4676-bf72-d3314ae6361d","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:06e85971af4cf6467963e9d3e1ef27515523548b0de91b2404f70a585a44ecbe","observation_id":"32fc3d37-a1c9-4937-960e-0c121f89de38","resolution":{"observed_at":"2026-05-11T04:35:57.641425Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.04903","last_updated":"2025-08-12T16:29:05Z","snapshot_observed_at":"2026-08-05T23:47:37.018948Z","submitted_at":"2025-08-06T21:59:34Z","title":"RCR-Router: Efficient Role-Aware Context Routing for Multi-Agent LLM Systems with Structured Memory","version":3},"cited_work":{"arxiv_id":"2508.04903","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.04903","snapshot_observed_at":"2026-06-29T22:14:00.193685Z","title":"arXiv preprint arXiv:2508.04903 , year =","venue":null,"work_id":"6cc41538-3425-4724-b5a6-a155343ef45a","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2508.04903","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:4731c00bbd926027b60cf1dc5c5ab26b683a45bbe0d33c37a8bfd249248f6201","observation_id":"8ff5ee11-c075-41d9-9cdc-2695df288711","resolution":{"observed_at":"2026-05-11T04:35:57.713347Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.21141","last_updated":"2025-09-09T09:54:15Z","snapshot_observed_at":"2026-08-09T22:21:22.305016Z","submitted_at":"2025-08-28T18:18:19Z","title":"Adaptive LLM Routing under Budget Constraints","version":2},"cited_work":{"arxiv_id":"2508.21141","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.21141","snapshot_observed_at":"2026-07-03T23:09:01.795037Z","title":"Pan, H., Tennenholtz, G., Mannor, S., Chi, C.-W., Brekel- mans, R., Shah, P., and Tewari, A","venue":null,"work_id":"86cd33f5-f0be-4d28-b775-10e356b31e74","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2508.21141","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:a3d5b37ae1592fa54f6c4c8b27c2e7dcf72e67a041e0a90bdb56d07a021682a2","observation_id":"67161235-3b09-43dd-bf49-f3dfb43f213e","resolution":{"observed_at":"2026-05-11T04:35:57.457609Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.19506","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2510.19506 , year=","venue":null,"work_id":"6f4d0d13-9e88-43e5-b310-d7deb9f7ab8c","year":null},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:56e30265fff4023e20bdc5d0d6d52649ba8585f01d0297af2d13eb789d17781d","observation_id":"2a0a40f7-100f-4e0c-8409-11ed68b8365e","resolution":{"observed_at":"2026-05-11T04:35:57.434343Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.22095","last_updated":"2026-04-06T12:52:40Z","snapshot_observed_at":"2026-08-02T15:44:17.473900Z","submitted_at":"2025-05-28T08:17:57Z","title":"Mixture-of-Retrieval Experts for Reasoning-Guided Multimodal Knowledge Exploitation","version":2},"cited_work":{"arxiv_id":"2505.22095","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.22095","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mixture-of-Retrieval Experts for Reasoning-Guided Multimodal Knowledge Exploitation","venue":"cs.CL","work_id":"0a6ba76e-3c32-4729-9d5f-0cc5cf57094e","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2505.22095","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:702a7ef54a4318dcdc31cd363ed7c8c77d51f58fa513d2773b0d215ae2580f73","observation_id":"0f64b902-0d4b-4e32-aaff-696c35fd5d00","resolution":{"observed_at":"2026-05-11T04:35:57.493836Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-07-08T15:05:03.646026Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":"a2bdafeb-48d9-47c6-8520-fad9a5a3c738","year":null},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:d5fb8402fe99c95eaa03c7a396f738e83167ce39e863af1780db1c138864e60c","observation_id":"20dbead4-0591-49bf-b063-b4cee5714b73","resolution":{"observed_at":"2026-05-14T17:12:30.328106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.16291","last_updated":"2023-10-19T16:27:03Z","snapshot_observed_at":"2026-08-07T08:29:46.650400Z","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":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2305.16291","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:acc9b92e227324d8d1d746fb1daa6f7343b5650d349124095415c9404ccf5481","observation_id":"aaa1026a-92f1-4842-bdbb-4ae231b4eff0","resolution":{"observed_at":"2026-05-11T04:35:57.621808Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.07841","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-02T07:46:45.820244Z","title":"Self-improving llm agents at test-time","venue":null,"work_id":"3794e6e3-0a77-4fb9-be42-9f0dd36c9166","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:cdaeb46e2f7f49267944f4a31e3a04209f37265c3439b1c9ad0c5d54d75b3bd9","observation_id":"d803bc9e-71b0-4972-9353-b92a7e4e59b1","resolution":{"observed_at":"2026-05-11T04:35:57.548438Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2510.08558","last_updated":"2026-05-24T21:56:11Z","snapshot_observed_at":"2026-08-04T10:47:54.049813Z","submitted_at":"2025-10-09T17:59:17Z","title":"Agent Learning via Early Experience","version":3},"cited_work":{"arxiv_id":"2510.08558","doi":null,"metadata_source":"pith","pith_arxiv_id":"2510.08558","snapshot_observed_at":"2026-07-04T20:00:07.735443Z","title":"arXiv preprint arXiv:2510.08558 , year=","venue":"cs.AI","work_id":"f0d69349-a2c2-4250-8431-82719c22096f","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2510.08558","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:3f684898f60b4b938eaaa31f479cd89d96790068aa3048110f81907c00960ac3","observation_id":"506667a1-1d5b-42e5-b27c-4c823f3c70ae","resolution":{"observed_at":"2026-05-26T03:04:06.268577Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2510.16079","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:2bde0935e8e3d47011c610801ad58850267870156f69303beb8c6a96ac96d4bf","observation_id":"04d364ee-2ecc-4981-be64-47fd30a6e661","resolution":{"observed_at":"2026-05-11T04:35:57.536202Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.21046","last_updated":"2026-01-16T20:59:08Z","snapshot_observed_at":"2026-08-01T06:32:44.461162Z","submitted_at":"2025-07-28T17:59:05Z","title":"A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence","version":4},"cited_work":{"arxiv_id":"2507.21046","doi":"10.48550/arxiv.2507.21046","metadata_source":"pith","pith_arxiv_id":"2507.21046","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence","venue":"cs.AI","work_id":"f5de9511-98bf-411c-9eba-e8b7a914ec18","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2507.21046","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:cbd0ad50837a19612e8d0877eb165d060859c1d65eda4fb5d9c9f3b055c88564","observation_id":"2f0e22a2-a23d-483a-8b50-63b816784ea7","resolution":{"observed_at":"2026-05-14T22:23:15.948876Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-01T10:08:10.122082+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-01T10:08:10.122082+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-07-10T22:47:37.666062Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":"1265447d-0324-4d07-abba-34fa29d172da","year":null},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:5cf48a330424527b627c354436c7e28f1cf1c349c7ff110a6b39319715bb088e","observation_id":"701a186e-ddb8-4127-b6a6-2a01ceb7ddb4","resolution":{"observed_at":"2026-05-14T17:12:30.371743Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-07-06T21:02:58.716193Z","title":"The eleventh international conference on learning representations , year=","venue":null,"work_id":"d0870e7f-a33a-4020-8109-459b41853021","year":null},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:5310bbbe028e363562bb735ce84cab212e29ef77511af55e61649801ec0ff825","observation_id":"a455795d-a9d5-434e-9ab2-0358095031d7","resolution":{"observed_at":"2026-05-14T17:12:30.362433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.10625","last_updated":"2023-04-16T22:08:08Z","snapshot_observed_at":"2026-08-06T09:00:42.886249Z","submitted_at":"2022-05-21T15:34:53Z","title":"Least-to-Most Prompting Enables Complex Reasoning in Large Language Models","version":3},"cited_work":{"arxiv_id":"2205.10625","doi":"10.48550/arxiv.2205.10625","metadata_source":"pith","pith_arxiv_id":"2205.10625","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Least-to-Most Prompting Enables Complex Reasoning in Large Language Models","venue":"cs.AI","work_id":"7e58c111-4666-4996-b5ad-1c8efd433083","year":2022},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2205.10625","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:e6169ca88b5f1dbbb6252b86e2d9e3635dfdd3bbdf5df8dc6a0a5ccd4b28ac5d","observation_id":"5e091af2-e50e-475f-907a-b28692797a5b","resolution":{"observed_at":"2026-05-11T08:44:37.129111Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-07-06T01:31:44.141506Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":"f3923cef-fa32-49c8-8280-9c6bb5d18d27","year":null},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:cc6f5c8fd3bc8d378064f909002383fac5e75776da34f12607aae25b6379baf6","observation_id":"7645a7df-ad8f-4909-90a1-935488320833","resolution":{"observed_at":"2026-05-14T17:12:30.357612Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-07-07T12:33:46.029737Z","title":"Proceedings of the 2025 ACM Conference on International Computing Education Research V","venue":null,"work_id":"37b1e4d6-718e-4eda-96fd-2d7415030bc5","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:90af062b498db2c2f758e40854d9d2b4052b3f318e3d5b4bba96c3fcb8fd220f","observation_id":"badb2fed-2e72-407f-b593-ca49c71d65e0","resolution":{"observed_at":"2026-05-14T17:12:30.385738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2510.12061","last_updated":"2026-05-04T04:44:23Z","snapshot_observed_at":"2026-07-06T22:32:37.311210Z","submitted_at":"2025-10-14T01:59:02Z","title":"Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response","version":2},"cited_work":{"arxiv_id":"2510.12061","doi":null,"metadata_source":"pith","pith_arxiv_id":"2510.12061","snapshot_observed_at":"2026-07-03T17:48:45.552042Z","title":"Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response","venue":"cs.AI","work_id":"bd4f9149-650f-41a4-8c59-0b3ee45c4b65","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2510.12061","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:33ef396c410904a9da4d6994b2bd6d39e875f0711ee02dd5432cbc396032ab8f","observation_id":"94353a3c-ed9e-449b-8a3d-b6a423901def","resolution":{"observed_at":"2026-05-11T04:35:57.600634Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-07-06T02:21:49.356376Z","title":"The Twelfth International Conference on Learning Representations , year=","venue":null,"work_id":"5de70941-c7c2-4d29-9679-775f7dd66603","year":null},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:aed779fbb4e4641595730ea43474ec8231635546942761684f61cc0cc4fa09ef","observation_id":"7483cd9e-cccd-43e4-bd34-64e9223ee598","resolution":{"observed_at":"2026-05-14T17:12:30.412594Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-07-09T14:06:16.682435Z","title":"Proceedings of the International Conference on Learning Representations (ICLR) , year=","venue":null,"work_id":"9fc03996-1ca4-4c37-9b48-66c12a36bb17","year":null},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:53162c0f636481557c6a6b3028a7276e51bbc446ced8e5ac8b34a33f74c4edc0","observation_id":"6e5cbbd9-67aa-48b3-8fa2-f4f2cdc2d739","resolution":{"observed_at":"2026-05-14T17:12:30.380751Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.16153","last_updated":"2025-08-25T13:32:12Z","snapshot_observed_at":"2026-08-06T23:53:22.457977Z","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":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2508.16153","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:88fb478fb45a690ff1053541962fef4d8a65cce190a0ae047ac6351fe7130877","observation_id":"e5b25611-39bd-4e7b-a3ef-0f73850e5bd7","resolution":{"observed_at":"2026-05-11T04:35:57.682196Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.23885","last_updated":"2025-06-11T01:42:53Z","snapshot_observed_at":"2026-08-07T22:31:50.319614Z","submitted_at":"2025-05-29T17:51:58Z","title":"OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation","version":2},"cited_work":{"arxiv_id":"2505.23885","doi":"10.48550/arxiv.2505.23885","metadata_source":"arxiv_reference","pith_arxiv_id":"2505.23885","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2505.23885 , year=","venue":"ArXiv.org","work_id":"f267e37d-ab4f-4288-8cfe-389d3a6da414","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2505.23885","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:1da8f0c9b384e5e3f6b6b3291f164ba708cd60a361dd25616c006f7560b4c4a4","observation_id":"c6ad22fa-6416-4151-967c-fe5f73f0421c","resolution":{"observed_at":"2026-05-11T04:35:57.423223Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.21557","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Co-sight: Enhancing llm-based agents via conflict-aware meta-verification and trustworthy reasoning with structured facts","venue":null,"work_id":"b716be15-4016-420c-885e-7d581ce16dbd","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:b829711d28b50e52036cce024c9efdea04548078cb8494419283190870327fda","observation_id":"b38cf815-ab42-4359-babf-0362e4ad07c2","resolution":{"observed_at":"2026-05-11T04:35:57.739769Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.20286","last_updated":"2025-05-26T17:58:53Z","snapshot_observed_at":"2026-08-07T15:21:20.945396Z","submitted_at":"2025-05-26T17:58:53Z","title":"Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution","version":1},"cited_work":{"arxiv_id":"2505.20286","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.20286","snapshot_observed_at":"2026-07-09T14:26:20.364079Z","title":"Alita: Generalist agent enabling scalable agentic reasoning with minimal predefinition and maximal self-evolution","venue":"cs.AI","work_id":"8c50a731-e2ce-41b5-a21a-7a4dcb1dacc5","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2505.20286","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:08cb7c41315f8c7c92127f1115dcc40d348735b5202bbe59fa76e6dad57ab372","observation_id":"cf7899c0-f167-4065-a8fa-36efb0d0f709","resolution":{"observed_at":"2026-05-11T04:35:57.587562Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.23601","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T08:39:42.719138Z","title":"arXiv preprint arXiv:2510.23601 , year=","venue":null,"work_id":"bbc74607-5725-48bb-a855-e21950480570","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:564f9fc996f23e1987ef6de43bf4d70da400d615d3e36bad6733c8a324aaa6a0","observation_id":"77d36efd-1ec7-44c3-bdac-9f9014100fcc","resolution":{"observed_at":"2026-05-11T04:35:57.395354Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"7ad79796-2d09-4b9a-858c-dcf9737721b7","year":null},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:84a2035b8f39aac0300132b7652b4de97d62ce4c2909a39de743b55c48a3f9ba","observation_id":"5a16178a-8353-4846-b522-4e3861852156","resolution":{"observed_at":"2026-05-14T17:12:30.367094Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-07-07T22:54:10.794872Z","title":"2024 , url=","venue":null,"work_id":"8cb9b778-76a8-412b-b182-96eb9462c821","year":2024},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:591a67d177a34a7c028e6f784617461cd300e57acf11ceedade1d899a1f6ef27","observation_id":"7e24e9a1-614a-48c4-8058-ffd5752446ea","resolution":{"observed_at":"2026-05-14T17:12:30.347904Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"Nature Methods , pages=","venue":null,"work_id":"5244c485-95a9-4144-800d-eb7929e01363","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:d07f5f3a6946759d807e65796ca99da1bb10f46696288bcb07066c05bbd7c083","observation_id":"4e6e1ef8-d1cd-4fbe-b51f-75a80caede87","resolution":{"observed_at":"2026-05-14T17:12:30.342381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"Nature Computational Science , pages=","venue":null,"work_id":"7c791238-3819-4715-a7ce-8664f024237d","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:777c1ce5b79dc1a404979ce732da7847a4d9cd06602fbcc06a3c45dc174bfa4f","observation_id":"70ef9493-a5a9-436a-99c6-39b266669c97","resolution":{"observed_at":"2026-05-14T17:12:30.390135Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"3194cbba-878a-4772-a1bf-80395f51dc87","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:8d9089e5dda7e71673e670330cae8ae88e5b8e380788d6b7f49f66690ba76f4d","observation_id":"c6bb9656-62fa-4fc3-8202-419ba3efec1d","resolution":{"observed_at":"2026-05-14T17:12:30.316046Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.20246","last_updated":"2025-06-19T15:42:45Z","snapshot_observed_at":"2026-08-09T21:27:49.188739Z","submitted_at":"2025-05-26T17:22:20Z","title":"On Path to Multimodal Historical Reasoning: HistBench and HistAgent","version":3},"cited_work":{"arxiv_id":"2505.20246","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.20246","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2505.20246 , year=","venue":null,"work_id":"d65dda60-b945-4980-8d05-7eedc9ecb779","year":null},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2505.20246","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:d69a4ea931840a9cdcca1afdeb8ff723b46ae2354c9f6b471550752606139197","observation_id":"ef343a86-5934-47df-9083-f81aaa8f9e99","resolution":{"observed_at":"2026-05-11T04:35:57.472272Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2025 , note =","venue":null,"work_id":"e26e9f37-3d5d-4965-abdf-c31fb9754659","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:f3ac92387aa1e6cc6eb584bd76e292f60d480ba979b987ae518502a9b94276b9","observation_id":"e58897a4-1483-48d2-88ac-ede9192217f5","resolution":{"observed_at":"2026-05-14T17:12:30.397745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.08773","last_updated":"2025-07-22T15:27:33Z","snapshot_observed_at":"2026-08-08T01:13:01.972942Z","submitted_at":"2025-02-12T20:30:28Z","title":"Universal Model Routing for Efficient LLM Inference","version":2},"cited_work":{"arxiv_id":"2502.08773","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.08773","snapshot_observed_at":"2026-07-08T15:35:07.230646Z","title":"Levente Kocsis and Csaba Szepesvári","venue":"cs.CL","work_id":"7498cd4e-1061-4c66-972d-258bcf0c6913","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2502.08773","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:4c635e30c51ad9f5c6a3251e7d967ccf9592e94cdc3b7328ca4ce7652a7cec6b","observation_id":"7fb040f1-05ed-42b3-be12-6594f6f8061e","resolution":{"observed_at":"2026-05-11T04:35:57.517116Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.15789","last_updated":"2023-09-27T17:08:40Z","snapshot_observed_at":"2026-08-06T08:57:12.331150Z","submitted_at":"2023-09-27T17:08:40Z","title":"Large Language Model Routing with Benchmark Datasets","version":1},"cited_work":{"arxiv_id":"2309.15789","doi":null,"metadata_source":"pith","pith_arxiv_id":"2309.15789","snapshot_observed_at":"2026-07-11T02:27:47.646520Z","title":"Large language model routing with benchmark datasets","venue":"cs.CL","work_id":"56d9bd9c-33d3-4d15-80bf-a522f51610b7","year":2023},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2309.15789","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:0fc2b4c84b6ef0f741ac536c063d868e26e0bfa96e97e822535a73e6752a7acb","observation_id":"df4ea24e-22cd-4406-aaf6-2e59531e8a9a","resolution":{"observed_at":"2026-05-11T04:35:57.726716Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.22716","last_updated":"2025-06-28T01:52:50Z","snapshot_observed_at":"2026-08-10T21:18:17.869089Z","submitted_at":"2025-06-28T01:52:50Z","title":"BEST-Route: Adaptive LLM Routing with Test-Time Optimal Compute","version":1},"cited_work":{"arxiv_id":"2506.22716","doi":"10.48550/arxiv.2506.22716","metadata_source":"arxiv_reference","pith_arxiv_id":"2506.22716","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2506.22716 , year=","venue":"ArXiv.org","work_id":"3b9abf2d-f47b-4a37-aef4-36823462365b","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2506.22716","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:7b9e7d94198bd6c243d7cefc8aa45959cbe73bb0ed05823c38db310e48abd951","observation_id":"9b338d22-0e31-42f9-a942-f67d0b5cab59","resolution":{"observed_at":"2026-05-11T04:35:57.654049Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2024.naacl-long.109","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models","venue":null,"work_id":"4085765a-6b1c-4ae0-8480-8050fbbd2e4a","year":2024},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:e0392d0e6a9498c57fb5618322cb2b89308ddaf311fdee3a050f08edbde1f17e","observation_id":"dc6b61eb-a722-4752-80f0-fc552d8fd7c0","resolution":{"observed_at":"2026-05-11T01:15:50.850285Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2025 , month =","venue":null,"work_id":"53574742-e43c-42c1-a1e4-17789ab202d7","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:5d1b9cc9bded81489a63fa9f24b5c923ac9a089193adae25cf9e1fa5e1975420","observation_id":"4fcf753f-622e-47b3-855e-ef35b50a1fcb","resolution":{"observed_at":"2026-05-14T17:12:30.402119Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2025 , month = dec, url =","venue":null,"work_id":"bf0073c0-9d10-4c61-9f7f-f3e25340e5ed","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:7d5ed2d2e983f98856525d125c2a85015e8a94b26f40f9766d3445948f0f981a","observation_id":"4d88752f-eae6-4015-8095-fc6775118148","resolution":{"observed_at":"2026-05-14T17:12:30.313088Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"8f15fd49-4bef-45be-83f3-d1b917f20d2e","year":null},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:c4740300515b78c78a70084a340c6852a3f4231d418ff9de5a8f69b33a69808f","observation_id":"c49c6c70-ec5f-47aa-af1a-28b65c3d17a4","resolution":{"observed_at":"2026-05-14T17:12:30.407083Z","resolver_source":"raw_fallback","status":"parse_uncertain"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2025 , month = dec, howpublished =","venue":null,"work_id":"506c1256-aee4-4dfb-b4f6-5b4778980533","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:a193a423122a54ea1f855d8b6d4f9e2ce55ed1c816c2d5b1645d1833b149bae0","observation_id":"8976848f-a9ad-4acb-a9bd-586f77de5872","resolution":{"observed_at":"2026-05-14T17:12:30.352557Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.06261","last_updated":"2025-12-19T14:25:46Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-07T17:36:04Z","title":"Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities","version":6},"cited_work":{"arxiv_id":"2507.06261","doi":"10.48550/arxiv.2503.19","metadata_source":"pith","pith_arxiv_id":"2507.06261","snapshot_observed_at":"2026-07-11T03:17:51.364436Z","title":"Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities","venue":"cs.CL","work_id":"008df105-2fdd-45d8-857a-8e35868aecb6","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2507.06261","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:c8a5b7a1da53e9d7416cd72f5859f6d7bd4960a2b5cbb4fe6fe14c78af4800a1","observation_id":"f55aabae-618c-4cb4-bd06-45b047ca3e49","resolution":{"observed_at":"2026-05-11T04:35:57.505232Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2025 , month = may, url =","venue":null,"work_id":"90094143-6afa-4f85-b7b5-ab5d9d874363","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:de8955d05cf88332c352ff272c84c37d34a742cf8701006425e0017e7431a854","observation_id":"32301a6a-98f8-4b01-bc4e-fa2f279d46e7","resolution":{"observed_at":"2026-05-14T17:12:30.375968Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2025 , month = sep, howpublished =","venue":null,"work_id":"406189e8-c4b0-417d-818c-6966cb6617b0","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:d5bdaec3f272acaee93def972070855b3a3ed8ca8ec6ae270dc0ddd4371a4680","observation_id":"bffec02f-8d1e-4e62-819b-e373dcf12bae","resolution":{"observed_at":"2026-05-14T17:12:30.319301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2025 , howpublished =","venue":null,"work_id":"2b763c94-b77b-4e08-9143-32b6ea0685d8","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:0885ea8145c09d63d82416277aa7735d55f71eee6a27b72a26f8b1a5ada7e278","observation_id":"ff2630f5-1b22-4db9-9895-4527f04e5900","resolution":{"observed_at":"2026-05-14T17:12:30.332994Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"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":"2505.09388","doi":"10.1016/j.aiopen.2022.12","metadata_source":"pith","pith_arxiv_id":"2505.09388","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Qwen3 Technical Report","venue":"cs.CL","work_id":"25a4e30c-1232-48e7-9925-02fa12ba7c9e","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2505.09388","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:08e20025ebea8e2c9e93ec87112803defc4adf5376a6ac8c20932aace43e4004","observation_id":"089e3355-2934-4d86-85cc-a341199410df","resolution":{"observed_at":"2026-05-11T04:35:57.524807Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2025 , month = jul, howpublished =","venue":null,"work_id":"2386db85-11eb-4186-9779-300db5485053","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:0296c329d8ed9c8315bb9c2287a057677de669d1428b31c81bedfef54b031579","observation_id":"0200fa49-470b-4303-9566-cb8f31697b8c","resolution":{"observed_at":"2026-05-14T17:12:30.394040Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2512.02556","last_updated":"2025-12-02T09:25:14Z","snapshot_observed_at":"2026-07-31T23:49:25.878472Z","submitted_at":"2025-12-02T09:25:14Z","title":"DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models","version":1},"cited_work":{"arxiv_id":"2512.02556","doi":"10.18653/v1/d18-1512","metadata_source":"pith","pith_arxiv_id":"2512.02556","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models","venue":"cs.CL","work_id":"07c85cc5-4086-4abc-823b-6d0f4ff784d0","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2512.02556","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:bb9cc462917e0ad96f068780a2d5dc52244173d1324b461580b17ededf63e4af","observation_id":"bb0ff3f7-5cfb-4489-86f4-40b393f368fc","resolution":{"observed_at":"2026-05-11T04:35:57.670174Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2025 , month = nov, url =","venue":null,"work_id":"d71a0e31-fcb2-443c-86ec-adff7f103a49","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:0bb7d26af9794d7a0bd0d89956a9255fbcd0ec965b8ff9bf9aec5356a6193a8b","observation_id":"7a12eef5-cff1-4648-9074-f176487171ec","resolution":{"observed_at":"2026-05-14T17:12:30.417198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2410.21276","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:4232a58afbbe2780671d580882fa7621edaee2f1150b0b1be58ae9631cc919b9","observation_id":"cb6b505f-6053-4dbe-bb06-d49d1cbcafbc","resolution":{"observed_at":"2026-05-11T04:35:57.662121Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"author =","venue":null,"work_id":"e8bf0b9c-803b-4ba8-acfa-87d5cd109cac","year":null},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:1bb4cac56ac26319f7344ffa6a3f845275cf2e2356841c5e4d3151d751c2464c","observation_id":"c8a33d23-5cc0-499d-8650-ae19a56efd6c","resolution":{"observed_at":"2026-05-14T17:12:30.323404Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2501.14249","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:985f84919a27d067500c6b3053b343d49e3d8308e0684edc57be03728f346e9f","observation_id":"8f30cfd5-972a-491c-acfd-5c3507a7704e","resolution":{"observed_at":"2026-05-11T04:35:57.568032Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.07974","last_updated":"2024-06-06T17:41:21Z","snapshot_observed_at":"2026-08-10T03:07:35.408836Z","submitted_at":"2024-03-12T17:58:04Z","title":"LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code","version":2},"cited_work":{"arxiv_id":"2403.07974","doi":"10.1109/icsme52107.2021.00025","metadata_source":"pith","pith_arxiv_id":"2403.07974","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code","venue":"cs.SE","work_id":"ea9e51ce-1e75-4182-92d8-4d25f70d2ee4","year":2024},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2403.07974","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:8a86c72ea2e2600b4482f5fbeb147e0404dc227807b4c3823a6d0633c3777d83","observation_id":"d23cacd4-fe6d-43f6-99ca-8681783460b4","resolution":{"observed_at":"2026-05-11T04:35:57.410386Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":"2506.14728","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-07-04T13:39:50.583619Z","title":"Agentdistill: Training-free agent distillation with gener- alizable mcp boxes","venue":null,"work_id":"cdbcddc9-75ef-44de-8735-629463effa85","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:3c3d28fee5ae18e276b0283e2684c13a99e7cf6f9009c3590aa41b24d2fa7233","observation_id":"ff2e6df0-3fdf-4514-b7d1-39f8e5d60074","resolution":{"observed_at":"2026-05-11T04:35:57.749352Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience"},"reference_resolution":{"displayed":54,"state_counts":{"malformed_identifier":0,"metadata_mismatch":20,"parse_uncertain":1,"unresolved":2,"verified_exact":10,"verified_fuzzy":21},"total_outbound_references":54},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2605.07180."}