{"as_of":"2026-08-09T16:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7a90b337fe38ddabdd3e55a9df321c63face16247259b37d55726c179d718943","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":17,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":17,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":17,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T11:22:28.873531Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-09T11:22:28.873531Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.02743","last_updated":"2025-02-04T22:09:43Z","snapshot_observed_at":"2026-08-09T11:14:34.154309Z","submitted_at":"2025-02-04T22:09:43Z","title":"LLM Bandit: Cost-Efficient LLM Generation via Preference-Conditioned Dynamic Routing","version":1},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-09T11:22:28.873531Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2502.02743"},"observation_digest":"sha256:b1b672e0469ce507258d5ba9cc37f3fb2510caae97cec18c2e9d697e1f650b01","observation_id":"be890cb1-f802-4b56-bfe0-83c21c0d636d","resolution":{"observed_at":"2026-08-09T11:22:28.873531Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-07T23:48:00.934127Z","title":"Tryage: Real-time, intelligent routing of user prompts to large language models, 2023","venue":null,"work_id":null,"year":2023},"citing_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},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T23:48:00.934127Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2502.08773"},"observation_digest":"sha256:71c281d49713364f7ea0c433738bfc14e2ec6b7b94d0c78e6ab308e2033ebfb5","observation_id":"47d14d2c-2a78-43e7-8d8d-f9fba466f5ff","resolution":{"observed_at":"2026-08-07T23:48:00.934127Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-07T19:40:07.745899Z","title":"N., & Thomson, M","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.10051","last_updated":"2025-02-17T15:30:22Z","snapshot_observed_at":"2026-08-08T15:22:06.356585Z","submitted_at":"2025-02-14T10:00:20Z","title":"ORI: O Routing Intelligence","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T19:40:07.745899Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2502.10051"},"observation_digest":"sha256:32486ba8f6ca866f5bb41103bc33c5762e20727cbc8206f837b25e1e373730d3","observation_id":"27168892-f13b-41cc-9baa-4c8bb3748042","resolution":{"observed_at":"2026-08-07T19:40:07.745899Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":"2308.11601","doi":"10.48550/arxiv.2308.11601","metadata_source":"arxiv_reference","pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Tryage: Real-time, intelligent routing of user prompts to large language models","venue":"arXiv (Cornell University)","work_id":"d61d85d1-4e36-4324-b818-9dc089197236","year":2023},"citing_paper":{"arxiv_id":"2505.12601","last_updated":"2026-05-14T18:08:42Z","snapshot_observed_at":"2026-08-02T11:09:30.375825Z","submitted_at":"2025-05-19T01:33:41Z","title":"Rethinking Predictive Modeling for LLM Routing: When Simple kNN Beats Complex Learned Routers","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-22T15:13:28.927880Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2505.12601"},"observation_digest":"sha256:bac0e3ba19d701875571c7c14cf3cb895a276cabe538d7e892714b5e4aaf8766","observation_id":"92723ff5-24c1-4d7f-9488-67bbbdd78adf","resolution":{"observed_at":"2026-05-22T15:14:57.463753Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-07T12:00:10.497442Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01048","last_updated":"2025-06-21T03:39:58Z","snapshot_observed_at":"2026-08-09T00:38:43.055341Z","submitted_at":"2025-06-01T15:14:58Z","title":"IRT-Router: Effective and Interpretable Multi-LLM Routing via Item Response Theory","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T12:00:10.497442Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2506.01048"},"observation_digest":"sha256:356e3cff6a8ec611d8240dbe27df235c84ad6590b04e25ac6e84766d49ee6874","observation_id":"451460e1-f884-4ab0-bcd1-70e4028ada05","resolution":{"observed_at":"2026-08-07T12:00:10.497442Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-07T05:56:56.924187Z","title":"Tryage: Real-time, intelligent rout- ing of user prompts to large language model,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.06579","last_updated":"2025-06-06T23:13:08Z","snapshot_observed_at":"2026-08-07T05:51:34.237166Z","submitted_at":"2025-06-06T23:13:08Z","title":"Towards Efficient Multi-LLM Inference: Characterization and Analysis of LLM Routing and Hierarchical Techniques","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T05:56:56.924187Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2506.06579"},"observation_digest":"sha256:9bc785e9c207eaa036a3227e735b86cda7a3aaee7e009110aaf109313aa10ec1","observation_id":"5b153ab8-f3a6-4034-be29-cb7af28c0ff2","resolution":{"observed_at":"2026-08-07T05:56:56.924187Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-06T20:05:18.195594Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.03834","last_updated":"2025-07-04T23:16:02Z","snapshot_observed_at":"2026-08-07T12:54:43.065453Z","submitted_at":"2025-07-04T23:16:02Z","title":"Economic Evaluation of LLMs","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-06T20:05:18.195594Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2507.03834"},"observation_digest":"sha256:33939e0ca2c4541a0035dd9404bbe1cd69b7f95d01a13ab9e0b12df9487f64ca","observation_id":"eb594062-b4d0-4da4-b203-791ef45a2bda","resolution":{"observed_at":"2026-08-06T20:05:18.195594Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":"2308.11601","doi":"10.48550/arxiv.2308.11601","metadata_source":"arxiv_reference","pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Tryage: Real-time, intelligent routing of user prompts to large language models","venue":"arXiv (Cornell University)","work_id":"d61d85d1-4e36-4324-b818-9dc089197236","year":2023},"citing_paper":{"arxiv_id":"2509.24814","last_updated":"2026-05-07T06:47:05Z","snapshot_observed_at":"2026-07-30T12:36:06.124222Z","submitted_at":"2025-09-29T14:02:27Z","title":"A Greedy PDE Router for Blending Neural Operators and Classical Methods","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-18T12:32:13.577474Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2509.24814"},"observation_digest":"sha256:f44f78ad211f73c45f9105f2f988ccfa1032d628de64385550ae60bf59b10f6e","observation_id":"5af22fe2-439c-44a9-9b7a-c37e3d449453","resolution":{"observed_at":"2026-05-18T12:32:36.199507Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":"2308.11601","doi":"10.48550/arxiv.2308.11601","metadata_source":"arxiv_reference","pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Tryage: Real-time, intelligent routing of user prompts to large language models","venue":"arXiv (Cornell University)","work_id":"d61d85d1-4e36-4324-b818-9dc089197236","year":2023},"citing_paper":{"arxiv_id":"2605.17110","last_updated":"2026-06-01T07:26:00Z","snapshot_observed_at":"2026-07-06T23:28:12.114488Z","submitted_at":"2026-05-16T18:30:37Z","title":"Capturing LLM Capabilities via Evidence-Calibrated Query Clustering","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-20T15:04:32.774530Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2605.17110"},"observation_digest":"sha256:f05773d779c058304d3269db396a3c72b8c5fd5c62daf915ee10f3c22fadec08","observation_id":"bc3c2ffb-ec9e-4a2f-bff3-cb3af70fc085","resolution":{"observed_at":"2026-05-20T15:08:25.112308Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":"2308.11601","doi":"10.48550/arxiv.2308.11601","metadata_source":"arxiv_reference","pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Tryage: Real-time, intelligent routing of user prompts to large language models","venue":"arXiv (Cornell University)","work_id":"d61d85d1-4e36-4324-b818-9dc089197236","year":2023},"citing_paper":{"arxiv_id":"2605.17110","last_updated":"2026-06-01T07:26:00Z","snapshot_observed_at":"2026-07-06T23:28:12.114488Z","submitted_at":"2026-05-16T18:30:37Z","title":"Capturing LLM Capabilities via Evidence-Calibrated Query Clustering","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-30T18:59:45.877785Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2605.17110"},"observation_digest":"sha256:509bdedbcd42b519a39c942f0c129f5c5580445111267372d675e4174a66968d","observation_id":"e9bc57d9-2ff3-437e-bcff-0c2e7cd2bac8","resolution":{"observed_at":"2026-06-30T19:05:00.984836Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":"2308.11601","doi":"10.48550/arxiv.2308.11601","metadata_source":"arxiv_reference","pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Tryage: Real-time, intelligent routing of user prompts to large language models","venue":"arXiv (Cornell University)","work_id":"d61d85d1-4e36-4324-b818-9dc089197236","year":2023},"citing_paper":{"arxiv_id":"2605.17288","last_updated":"2026-05-17T06:59:43Z","snapshot_observed_at":"2026-08-02T11:50:03.814042Z","submitted_at":"2026-05-17T06:59:43Z","title":"When Efficiency Backfires: Cascading LLMs Trigger Cascade Failure under Adversarial Attack","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-19T23:58:53.524203Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2605.17288"},"observation_digest":"sha256:527aaa9a7218837d514449ff7c83b42616bfae92195e069a1f4ee142be38e8b7","observation_id":"9bdfa1dc-7fb5-424b-9628-f636332fcc67","resolution":{"observed_at":"2026-05-20T00:02:53.702571Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":"2308.11601","doi":"10.48550/arxiv.2308.11601","metadata_source":"arxiv_reference","pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Tryage: Real-time, intelligent routing of user prompts to large language models","venue":"arXiv (Cornell University)","work_id":"d61d85d1-4e36-4324-b818-9dc089197236","year":2023},"citing_paper":{"arxiv_id":"2606.04883","last_updated":"2026-06-23T10:56:57Z","snapshot_observed_at":"2026-08-05T15:37:01.185480Z","submitted_at":"2026-06-03T13:46:20Z","title":"Optimizing the Cost-Quality Tradeoff of Agentic Theorem Provers in Lean","version":3},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-06-28T06:01:44.894830Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2606.04883"},"observation_digest":"sha256:37fef64247a5d76b454c4aea933f8aa50ff0c1565503c28868d5798b75bf23be","observation_id":"5d280dea-e41f-46e0-bcd9-bfca149d88c4","resolution":{"observed_at":"2026-06-28T06:11:42.484207Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":"2308.11601","doi":"10.48550/arxiv.2308.11601","metadata_source":"arxiv_reference","pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Tryage: Real-time, intelligent routing of user prompts to large language models","venue":"arXiv (Cornell University)","work_id":"d61d85d1-4e36-4324-b818-9dc089197236","year":2023},"citing_paper":{"arxiv_id":"2606.06924","last_updated":"2026-06-05T05:42:00Z","snapshot_observed_at":"2026-08-06T11:49:12.989321Z","submitted_at":"2026-06-05T05:42:00Z","title":"From Sampled Outcomes to Capability Distributions: Rethinking Supervision for LLM Routing","version":1},"reference_index":125,"source":"arxiv_source","source_observed_at":"2026-06-27T22:54:28.452796Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2606.06924"},"observation_digest":"sha256:b7438bea54272f71f3bde92f07811d1f389d1afeecb7985779e518baf08bbaa1","observation_id":"53c0b3ae-5eb4-42c5-b4a6-9694e1b7ec4f","resolution":{"observed_at":"2026-07-02T16:17:08.764825Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":"2308.11601","doi":"10.48550/arxiv.2308.11601","metadata_source":"arxiv_reference","pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Tryage: Real-time, intelligent routing of user prompts to large language models","venue":"arXiv (Cornell University)","work_id":"d61d85d1-4e36-4324-b818-9dc089197236","year":2023},"citing_paper":{"arxiv_id":"2606.07392","last_updated":"2026-06-05T15:29:17Z","snapshot_observed_at":"2026-07-06T23:47:00.425715Z","submitted_at":"2026-06-05T15:29:17Z","title":"Online Pandora's Box for Contextual LLM Cascading","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-06-27T21:59:43.429931Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2606.07392"},"observation_digest":"sha256:820e48dfc2157806ea44845ddd6821de6ba399c83673a3a42065f6bce0daa381","observation_id":"bd2dd4cc-4d43-40d0-8eef-58602cad7701","resolution":{"observed_at":"2026-07-02T17:37:14.290160Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":"2308.11601","doi":"10.48550/arxiv.2308.11601","metadata_source":"arxiv_reference","pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Tryage: Real-time, intelligent routing of user prompts to large language models","venue":"arXiv (Cornell University)","work_id":"d61d85d1-4e36-4324-b818-9dc089197236","year":2023},"citing_paper":{"arxiv_id":"2607.00053","last_updated":"2026-06-30T01:46:26Z","snapshot_observed_at":"2026-07-07T00:05:41.920778Z","submitted_at":"2026-06-30T01:46:26Z","title":"SWE-Router: Routing in Multi-turn Agentic Software Engineering Tasks","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-07-02T18:19:43.146102Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2607.00053"},"observation_digest":"sha256:f0bc5d2bca9f4f0a1e4d42d8fca3f344aea86eff6994dbf09cf332f66b8b0bbf","observation_id":"a19e310d-d168-4359-b7de-f0f6e2b43612","resolution":{"observed_at":"2026-07-02T18:37:16.490544Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-02T12:49:14.576579Z","title":"N.; Thomson, M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22561","last_updated":"2026-05-29T03:13:24Z","snapshot_observed_at":"2026-08-09T05:09:03.523364Z","submitted_at":"2026-05-29T03:13:24Z","title":"Codifying the Judge: Scalable Evaluation via Program Distillation","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-02T12:49:14.576579Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2607.22561"},"observation_digest":"sha256:df19b9c80dd1bd0714e882a0270ce1f45bb6cd8fdb64e2384c9e03613beeddd7","observation_id":"02d9e9dc-bb67-449c-9c5d-15c508457a90","resolution":{"observed_at":"2026-08-02T12:49:14.576579Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.11601","snapshot_observed_at":"2026-08-04T07:49:39.973177Z","title":"arXiv preprint arXiv:2308.11601 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02415","last_updated":"2026-08-03T15:53:49Z","snapshot_observed_at":"2026-08-08T15:56:39.139618Z","submitted_at":"2026-08-03T15:53:49Z","title":"Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes","version":1},"reference_index":98,"source":"arxiv_source","source_observed_at":"2026-08-04T07:49:39.973177Z"},"links":{"cited_paper":"/paper/2308.11601","citing_paper":"/paper/2608.02415"},"observation_digest":"sha256:8845640938847d79b15c68d75168c4a6229984f348baa052e50233ad725cb5af","observation_id":"824ff4c3-7096-4b79-9906-799ef205cf63","resolution":{"observed_at":"2026-08-04T07:49:39.973177Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2308.11601/citation-record","integrity":"/paper/2308.11601/integrity","json":"/paper/2308.11601/citation-record.json","paper":"/paper/2308.11601"},"outbound":[],"paper":{"arxiv_id":"2308.11601","last_updated":"2023-08-23T17:34:17Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T16:09:09.018523Z","submitted_at":"2023-08-22T17:48:24Z","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2308.11601."}