{"as_of":"2026-08-10T08:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:77aef6fc3dceb9085d7974710c7aa04b54f73168c980dfa06455e1c6664c0692","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":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:27:14.817392Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-02T19:57:19.013998Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2306.03030","last_updated":"2023-10-23T02:55:08Z","snapshot_observed_at":"2026-07-06T15:38:46.970127Z","submitted_at":"2023-06-05T16:48:41Z","title":"Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.03030","snapshot_observed_at":"2026-08-07T11:27:14.817392Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.02561","last_updated":"2025-06-03T07:47:30Z","snapshot_observed_at":"2026-08-08T01:27:01.613503Z","submitted_at":"2025-06-03T07:47:30Z","title":"Pruning General Large Language Models into Customized Expert Models","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T11:27:14.817392Z"},"links":{"cited_paper":"/paper/2306.03030","citing_paper":"/paper/2506.02561"},"observation_digest":"sha256:e08306a56d219fbd8595f157927708f3370537338c57a1ddc4f8e2d3033b78cf","observation_id":"b040dc8a-ab98-4fea-91b5-2692441fa5bc","resolution":{"observed_at":"2026-08-07T11:27:14.817392Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.03030","last_updated":"2023-10-23T02:55:08Z","snapshot_observed_at":"2026-07-06T15:38:46.970127Z","submitted_at":"2023-06-05T16:48:41Z","title":"Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.03030","snapshot_observed_at":"2026-08-07T00:59:43.421977Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.12379","last_updated":"2025-06-14T07:21:11Z","snapshot_observed_at":"2026-08-07T23:12:16.942292Z","submitted_at":"2025-06-14T07:21:11Z","title":"Training-free LLM Merging for Multi-task Learning","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T00:59:43.421977Z"},"links":{"cited_paper":"/paper/2306.03030","citing_paper":"/paper/2506.12379"},"observation_digest":"sha256:e7a2af4d50da906b8ad7ee0954f817b38b1e257426aa430369009d9b77385d8c","observation_id":"af74d540-bebd-48dc-b5e1-7345a0cdcffa","resolution":{"observed_at":"2026-08-07T00:59:43.421977Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.03030","last_updated":"2023-10-23T02:55:08Z","snapshot_observed_at":"2026-07-06T15:38:46.970127Z","submitted_at":"2023-06-05T16:48:41Z","title":"Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.03030","snapshot_observed_at":"2026-08-03T05:30:50.689747Z","title":"Liu, J., Zhou, P., Hua, Y ., Chong, D., Tian, Z., Liu, A., Wang, H., You, C., Guo, Z., Zhu, L., et al","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2602.02229","last_updated":"2026-06-10T12:21:44Z","snapshot_observed_at":"2026-08-08T07:43:48.063917Z","submitted_at":"2026-02-02T15:32:14Z","title":"Prediction-Powered Risk Monitoring of Deployed Models for Detecting Harmful Distribution Shifts","version":2},"reference_index":3130,"source":"pdf_text","source_observed_at":"2026-08-03T05:30:50.689747Z"},"links":{"cited_paper":"/paper/2306.03030","citing_paper":"/paper/2602.02229"},"observation_digest":"sha256:a0692b8130e0258b456c1f7c0af83105e18b5ea119ffb9ddeb50294ec8e107a5","observation_id":"d7748025-a35f-4884-a999-4929bb2584cc","resolution":{"observed_at":"2026-08-03T05:30:50.689747Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.03030","last_updated":"2023-10-23T02:55:08Z","snapshot_observed_at":"2026-07-06T15:38:46.970127Z","submitted_at":"2023-06-05T16:48:41Z","title":"Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset","version":3},"cited_work":{"arxiv_id":"2306.03030","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2306.03030","snapshot_observed_at":"2026-07-02T19:57:19.013998Z","title":"Benchmarking large language models on CMExam: A comprehensive chinese medical exam dataset,","venue":null,"work_id":"d452a7cf-1e25-49e4-a91e-24b332b0ef48","year":2023},"citing_paper":{"arxiv_id":"2605.08094","last_updated":"2026-04-09T18:00:47Z","snapshot_observed_at":"2026-08-02T05:04:09.143025Z","submitted_at":"2026-04-09T18:00:47Z","title":"MedThink: Enhancing Diagnostic Accuracy in Small Models via Teacher-Guided Reasoning Correction","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-12T01:22:15.608348Z"},"links":{"cited_paper":"/paper/2306.03030","citing_paper":"/paper/2605.08094"},"observation_digest":"sha256:1c100b531ee623624e7572b669d116adbf8df0221317155b8e369ddf38329eac","observation_id":"70a5d587-e9a0-426c-ab6a-dba39405ed1e","resolution":{"observed_at":"2026-05-12T08:01:31.866559Z","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":"2306.03030","last_updated":"2023-10-23T02:55:08Z","snapshot_observed_at":"2026-07-06T15:38:46.970127Z","submitted_at":"2023-06-05T16:48:41Z","title":"Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset","version":3},"cited_work":{"arxiv_id":"2306.03030","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2306.03030","snapshot_observed_at":"2026-07-02T19:57:19.013998Z","title":"Benchmarking large language models on CMExam: A comprehensive chinese medical exam dataset,","venue":null,"work_id":"d452a7cf-1e25-49e4-a91e-24b332b0ef48","year":2023},"citing_paper":{"arxiv_id":"2606.31432","last_updated":"2026-07-02T08:43:43Z","snapshot_observed_at":"2026-07-07T00:05:07.912609Z","submitted_at":"2026-06-30T09:59:05Z","title":"Clinically Structured Rank-Gated LoRA for Cross-Benchmark Medical Question Answering","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-01T05:53:55.141657Z"},"links":{"cited_paper":"/paper/2306.03030","citing_paper":"/paper/2606.31432"},"observation_digest":"sha256:b2d7fc3cd0df80cb56b8fb9146b1d38c81951bac651fd1c6c3c4707354362a2e","observation_id":"00dbe29a-eb37-4939-9d97-dd3f72da20c3","resolution":{"observed_at":"2026-07-01T10:05:41.004721Z","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":"2306.03030","last_updated":"2023-10-23T02:55:08Z","snapshot_observed_at":"2026-07-06T15:38:46.970127Z","submitted_at":"2023-06-05T16:48:41Z","title":"Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset","version":3},"cited_work":{"arxiv_id":"2306.03030","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2306.03030","snapshot_observed_at":"2026-07-02T19:57:19.013998Z","title":"Benchmarking large language models on CMExam: A comprehensive chinese medical exam dataset,","venue":null,"work_id":"d452a7cf-1e25-49e4-a91e-24b332b0ef48","year":2023},"citing_paper":{"arxiv_id":"2606.31432","last_updated":"2026-07-02T08:43:43Z","snapshot_observed_at":"2026-07-07T00:05:07.912609Z","submitted_at":"2026-06-30T09:59:05Z","title":"Clinically Structured Rank-Gated LoRA for Cross-Benchmark Medical Question Answering","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-02T19:53:25.252752Z"},"links":{"cited_paper":"/paper/2306.03030","citing_paper":"/paper/2606.31432"},"observation_digest":"sha256:badc9be8f1b4c48a97b3d49c90c6a9bcfda099e3a6c170095ff0534e7e43b7f9","observation_id":"30a8fc90-3bbf-4b88-ae92-65ed477bc119","resolution":{"observed_at":"2026-07-02T19:57:19.015860Z","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":"2306.03030","last_updated":"2023-10-23T02:55:08Z","snapshot_observed_at":"2026-07-06T15:38:46.970127Z","submitted_at":"2023-06-05T16:48:41Z","title":"Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.03030","snapshot_observed_at":"2026-07-13T05:07:42.040673Z","title":"Benchmarking large language models on CMExam – a comprehensive chinese medical exam dataset","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.09142","last_updated":"2026-07-16T10:17:24Z","snapshot_observed_at":"2026-08-06T22:09:00.592774Z","submitted_at":"2026-07-10T06:52:05Z","title":"MedRealMM: A Real-World Multimodal Benchmark for Chinese Online Medical Consultation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-13T05:07:42.040673Z"},"links":{"cited_paper":"/paper/2306.03030","citing_paper":"/paper/2607.09142"},"observation_digest":"sha256:489f93646390dfac03bcb48f9a6a127fc24784a3b950c9af4b65af87fa6cb7fe","observation_id":"661448f3-47e5-4a24-938a-a50081019ed6","resolution":{"observed_at":"2026-07-13T05:07:42.040673Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.03030","last_updated":"2023-10-23T02:55:08Z","snapshot_observed_at":"2026-07-06T15:38:46.970127Z","submitted_at":"2023-06-05T16:48:41Z","title":"Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.03030","snapshot_observed_at":"2026-08-02T07:43:27.681801Z","title":"Benchmarking large language models on CMExam – a comprehensive chinese medical exam dataset","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.09142","last_updated":"2026-07-16T10:17:24Z","snapshot_observed_at":"2026-08-06T22:09:00.592774Z","submitted_at":"2026-07-10T06:52:05Z","title":"MedRealMM: A Real-World Multimodal Benchmark for Chinese Online Medical Consultation","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-02T07:43:27.681801Z"},"links":{"cited_paper":"/paper/2306.03030","citing_paper":"/paper/2607.09142"},"observation_digest":"sha256:2370ef49f0a96c6bf92638fa58607ddeecf779e120e06ba56c1938f7fe4aa304","observation_id":"8294e180-58e9-43c2-a5cb-53108082f788","resolution":{"observed_at":"2026-08-02T07:43:27.681801Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2306.03030/citation-record","integrity":"/paper/2306.03030/integrity","json":"/paper/2306.03030/citation-record.json","paper":"/paper/2306.03030"},"outbound":[],"paper":{"arxiv_id":"2306.03030","last_updated":"2023-10-23T02:55:08Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T15:38:46.970127Z","submitted_at":"2023-06-05T16:48:41Z","title":"Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2306.03030."}