{"as_of":"2026-08-07T19:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:564885ae776c14c315d4affae891ac9bc7c839774d8b7bd2378e1c87002b0f55","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":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:44:34.527611Z","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":1,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2406.17681","last_updated":"2024-06-26T15:21:49Z","snapshot_observed_at":"2026-07-06T18:36:51.761148Z","submitted_at":"2024-06-25T16:13:53Z","title":"VarBench: Robust Language Model Benchmarking Through Dynamic Variable Perturbation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.17681","snapshot_observed_at":"2026-08-07T14:44:34.527611Z","title":"VarBench: Robust Language Model Benchmarking Through Dynamic Variable Perturbation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.18102","last_updated":"2026-05-30T13:29:55Z","snapshot_observed_at":"2026-08-07T14:33:15.240605Z","submitted_at":"2025-05-23T16:57:34Z","title":"CapBencher: Give Your LLM Benchmark a Built-in Alarm for Test-Set Overfitting","version":7},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T14:44:34.527611Z"},"links":{"cited_paper":"/paper/2406.17681","citing_paper":"/paper/2505.18102"},"observation_digest":"sha256:8e3e66e1d270292630c4e13b750550f2814e2afade94cd396e7883832aa303c1","observation_id":"e3a6b919-8448-4ca2-b844-46c804bc44b4","resolution":{"observed_at":"2026-08-07T14:44:34.527611Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17681","last_updated":"2024-06-26T15:21:49Z","snapshot_observed_at":"2026-07-06T18:36:51.761148Z","submitted_at":"2024-06-25T16:13:53Z","title":"VarBench: Robust Language Model Benchmarking Through Dynamic Variable Perturbation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.17681","snapshot_observed_at":"2026-08-07T00:40:18.482624Z","title":"Varbench: Robust language model benchmarking through dynamic variable perturbation.arXiv preprint arXiv:2406.17681, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12909","last_updated":"2025-06-15T16:57:14Z","snapshot_observed_at":"2026-08-07T13:43:22.813866Z","submitted_at":"2025-06-15T16:57:14Z","title":"SciDA: Scientific Dynamic Assessor of LLMs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T00:40:18.482624Z"},"links":{"cited_paper":"/paper/2406.17681","citing_paper":"/paper/2506.12909"},"observation_digest":"sha256:6bb681de337c55ebd2a41833dbfd220643f8b4f45093a71d61a649936451fdb5","observation_id":"f3eca25f-0978-4c78-996a-cf6f2e0748a7","resolution":{"observed_at":"2026-08-07T00:40:18.482624Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17681","last_updated":"2024-06-26T15:21:49Z","snapshot_observed_at":"2026-07-06T18:36:51.761148Z","submitted_at":"2024-06-25T16:13:53Z","title":"VarBench: Robust Language Model Benchmarking Through Dynamic Variable Perturbation","version":2},"cited_work":{"arxiv_id":"2406.17681","doi":"10.48550/arxiv.2406.17681","metadata_source":"arxiv_reference","pith_arxiv_id":"2406.17681","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Varbench: Robust language model benchmarking through dynamic variable perturbation.ArXiv, abs/2406.17681, 2024b","venue":"arXiv (Cornell University)","work_id":"8dee5ad1-f515-4fba-b6f2-4c19d9af1fb7","year":2024},"citing_paper":{"arxiv_id":"2508.19035","last_updated":"2026-05-06T13:45:16Z","snapshot_observed_at":"2026-08-02T18:03:42.477619Z","submitted_at":"2025-08-26T13:54:17Z","title":"Investigating Advanced Reasoning of Large Language Models via Black-Box Environment Interaction","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-18T21:35:59.043898Z"},"links":{"cited_paper":"/paper/2406.17681","citing_paper":"/paper/2508.19035"},"observation_digest":"sha256:58edc768d0ee12ebdaacbcdc573d5475c55909143b74c64107adecf5d532c7f8","observation_id":"8e6a57ae-b729-439c-ad64-453e059d7b46","resolution":{"observed_at":"2026-05-18T21:36:51.921349Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17681","last_updated":"2024-06-26T15:21:49Z","snapshot_observed_at":"2026-07-06T18:36:51.761148Z","submitted_at":"2024-06-25T16:13:53Z","title":"VarBench: Robust Language Model Benchmarking Through Dynamic Variable Perturbation","version":2},"cited_work":{"arxiv_id":"2406.17681","doi":"10.48550/arxiv.2406.17681","metadata_source":"arxiv_reference","pith_arxiv_id":"2406.17681","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Varbench: Robust language model benchmarking through dynamic variable perturbation.ArXiv, abs/2406.17681, 2024b","venue":"arXiv (Cornell University)","work_id":"8dee5ad1-f515-4fba-b6f2-4c19d9af1fb7","year":2024},"citing_paper":{"arxiv_id":"2605.17829","last_updated":"2026-05-18T04:03:18Z","snapshot_observed_at":"2026-08-05T06:31:55.615676Z","submitted_at":"2026-05-18T04:03:18Z","title":"Interactive Evaluation Requires a Design Science","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-20T10:55:08.135630Z"},"links":{"cited_paper":"/paper/2406.17681","citing_paper":"/paper/2605.17829"},"observation_digest":"sha256:c08ac02b5234e692bb186f57ea876c898a44f3d2ceb8be6d5b00db1f64e30d2c","observation_id":"75bd40fc-d788-4a65-a650-05bc3d64cba2","resolution":{"observed_at":"2026-05-20T10:58:14.009023Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17681","last_updated":"2024-06-26T15:21:49Z","snapshot_observed_at":"2026-07-06T18:36:51.761148Z","submitted_at":"2024-06-25T16:13:53Z","title":"VarBench: Robust Language Model Benchmarking Through Dynamic Variable Perturbation","version":2},"cited_work":{"arxiv_id":"2406.17681","doi":"10.48550/arxiv.2406.17681","metadata_source":"arxiv_reference","pith_arxiv_id":"2406.17681","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Varbench: Robust language model benchmarking through dynamic variable perturbation.ArXiv, abs/2406.17681, 2024b","venue":"arXiv (Cornell University)","work_id":"8dee5ad1-f515-4fba-b6f2-4c19d9af1fb7","year":2024},"citing_paper":{"arxiv_id":"2605.26133","last_updated":"2026-05-21T10:32:33Z","snapshot_observed_at":"2026-08-07T10:44:40.983544Z","submitted_at":"2026-05-21T10:32:33Z","title":"Pretraining Data Exposure in Large Language Models: A Survey of Membership Inference, Data Contamination, and Security Implications","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-30T17:20:16.735285Z"},"links":{"cited_paper":"/paper/2406.17681","citing_paper":"/paper/2605.26133"},"observation_digest":"sha256:61a966005d5393530953b201a6b5ca3d10847d3bf3ac806c29d1b6bf3f6a137b","observation_id":"1705460c-872b-494b-9257-08bef7e78f9b","resolution":{"observed_at":"2026-06-30T17:24:56.549713Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.17681","last_updated":"2024-06-26T15:21:49Z","snapshot_observed_at":"2026-07-06T18:36:51.761148Z","submitted_at":"2024-06-25T16:13:53Z","title":"VarBench: Robust Language Model Benchmarking Through Dynamic Variable Perturbation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.17681","snapshot_observed_at":"2026-07-30T22:39:33.950950Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.23425","last_updated":"2026-07-26T02:49:56Z","snapshot_observed_at":"2026-08-06T23:37:51.377753Z","submitted_at":"2026-07-26T02:49:56Z","title":"TLA+-Bench: An Execution-Grounded Benchmark and Dataset for Natural-Language to TLA Specification Generation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-30T22:39:33.950950Z"},"links":{"cited_paper":"/paper/2406.17681","citing_paper":"/paper/2607.23425"},"observation_digest":"sha256:322d83ec8872e07d7a5934182de9725e635c226bc44072b889aced6956f51ed5","observation_id":"ffb8bc5c-5013-4dfe-8042-d9db16fc59fd","resolution":{"observed_at":"2026-07-30T22:39:33.950950Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2406.17681/citation-record","integrity":"/paper/2406.17681/integrity","json":"/paper/2406.17681/citation-record.json","paper":"/paper/2406.17681"},"outbound":[],"paper":{"arxiv_id":"2406.17681","last_updated":"2024-06-26T15:21:49Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T18:36:51.761148Z","submitted_at":"2024-06-25T16:13:53Z","title":"VarBench: Robust Language Model Benchmarking Through Dynamic Variable Perturbation"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2406.17681."}