{"as_of":"2026-08-09T02:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3adb89b739302a9676cc55c5e38bd7a568c9075bab9ea99c3246d9cc67b2e0e7","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":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:57:11.478970Z","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":"2026-07-02T04:06:34.906379Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2109.01247","last_updated":"2022-04-21T16:03:20Z","snapshot_observed_at":"2026-07-06T11:43:54.154781Z","submitted_at":"2021-09-02T23:46:36Z","title":"Do Prompt-Based Models Really Understand the Meaning of their Prompts?","version":2},"cited_work":{"arxiv_id":"2109.01247","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.01247","snapshot_observed_at":"2026-07-02T04:06:34.906379Z","title":"Do prompt-based models really understand the meaning of their prompts? arXiv preprint arXiv:2109.01247","venue":null,"work_id":"e5ccc60b-711d-4f1b-a2fa-2e9b85020453","year":null},"citing_paper":{"arxiv_id":"2110.08207","last_updated":"2022-03-17T17:53:01Z","snapshot_observed_at":"2026-07-06T11:58:21.596920Z","submitted_at":"2021-10-15T17:08:57Z","title":"Multitask Prompted Training Enables Zero-Shot Task Generalization","version":3},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-14T17:59:42.765380Z"},"links":{"cited_paper":"/paper/2109.01247","citing_paper":"/paper/2110.08207"},"observation_digest":"sha256:527aec15330428836ac9ed38d71838f546b01acfd766941591ec517b6eed4f96","observation_id":"d2cbba3d-fe0e-45bf-9f88-23400e86a71f","resolution":{"observed_at":"2026-05-14T17:59:43.239507Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.01247","last_updated":"2022-04-21T16:03:20Z","snapshot_observed_at":"2026-07-06T11:43:54.154781Z","submitted_at":"2021-09-02T23:46:36Z","title":"Do Prompt-Based Models Really Understand the Meaning of their Prompts?","version":2},"cited_work":{"arxiv_id":"2109.01247","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.01247","snapshot_observed_at":"2026-07-02T04:06:34.906379Z","title":"Do prompt-based models really understand the meaning of their prompts? arXiv preprint arXiv:2109.01247","venue":null,"work_id":"e5ccc60b-711d-4f1b-a2fa-2e9b85020453","year":null},"citing_paper":{"arxiv_id":"2210.09261","last_updated":"2022-10-17T17:08:26Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-10-17T17:08:26Z","title":"Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-11T07:15:23.725397Z"},"links":{"cited_paper":"/paper/2109.01247","citing_paper":"/paper/2210.09261"},"observation_digest":"sha256:07988c707df2b9533c61936396173f501f50c7cd5731d8443125fc4fe43a121c","observation_id":"468806fe-57e1-4417-9b95-ec668a8d4753","resolution":{"observed_at":"2026-05-11T07:15:24.008493Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.01247","last_updated":"2022-04-21T16:03:20Z","snapshot_observed_at":"2026-07-06T11:43:54.154781Z","submitted_at":"2021-09-02T23:46:36Z","title":"Do Prompt-Based Models Really Understand the Meaning of their Prompts?","version":2},"cited_work":{"arxiv_id":"2109.01247","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.01247","snapshot_observed_at":"2026-07-02T04:06:34.906379Z","title":"Do prompt-based models really understand the meaning of their prompts? arXiv preprint arXiv:2109.01247","venue":null,"work_id":"e5ccc60b-711d-4f1b-a2fa-2e9b85020453","year":null},"citing_paper":{"arxiv_id":"2211.01910","last_updated":"2023-03-10T17:20:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-11-03T15:43:03Z","title":"Large Language Models Are Human-Level Prompt Engineers","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-24T09:43:26.288866Z"},"links":{"cited_paper":"/paper/2109.01247","citing_paper":"/paper/2211.01910"},"observation_digest":"sha256:f18c14c5e4308765d0e521e798b4ffb784cfae51f56ee2a3db20a1d61ece11e4","observation_id":"7aa1c6e6-e2b1-4ba4-91e8-adfd19d5ce09","resolution":{"observed_at":"2026-05-24T09:43:26.356199Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.01247","last_updated":"2022-04-21T16:03:20Z","snapshot_observed_at":"2026-07-06T11:43:54.154781Z","submitted_at":"2021-09-02T23:46:36Z","title":"Do Prompt-Based Models Really Understand the Meaning of their Prompts?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.01247","snapshot_observed_at":"2026-08-07T04:57:25.739518Z","title":"Do prompt-based models really understand the meaning of their prompts?","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09331","last_updated":"2025-06-17T23:22:53Z","snapshot_observed_at":"2026-08-08T14:40:23.191843Z","submitted_at":"2025-06-11T02:12:34Z","title":"Multi-Agent Language Models: Advancing Cooperation, Coordination, and Adaptation","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T04:57:25.739518Z"},"links":{"cited_paper":"/paper/2109.01247","citing_paper":"/paper/2506.09331"},"observation_digest":"sha256:b97c64afa32a328f8e3c9b11a1e3d7f744d0553fa3131ff12f67f2b947c5056b","observation_id":"8600aa5f-320b-4fa3-ba64-f06bd0e88f33","resolution":{"observed_at":"2026-08-07T04:57:25.739518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.01247","last_updated":"2022-04-21T16:03:20Z","snapshot_observed_at":"2026-07-06T11:43:54.154781Z","submitted_at":"2021-09-02T23:46:36Z","title":"Do Prompt-Based Models Really Understand the Meaning of their Prompts?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.01247","snapshot_observed_at":"2026-08-06T14:26:03.588558Z","title":"\\ Pavlick, E","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.06503","last_updated":"2025-07-25T15:56:25Z","snapshot_observed_at":"2026-08-07T10:30:17.548016Z","submitted_at":"2025-07-25T15:56:25Z","title":"Understanding Human Limits in Pattern Recognition: A Computational Model of Sequential Reasoning in Rock, Paper, Scissors","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-06T14:26:03.588558Z"},"links":{"cited_paper":"/paper/2109.01247","citing_paper":"/paper/2508.06503"},"observation_digest":"sha256:9fd7fe296d1cec8c8f1f55535fda592cafc39c3372064169650756b245ea7da7","observation_id":"1a7c2b15-4db1-4b08-9be8-3474bebd8358","resolution":{"observed_at":"2026-08-06T14:26:03.588558Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.01247","last_updated":"2022-04-21T16:03:20Z","snapshot_observed_at":"2026-07-06T11:43:54.154781Z","submitted_at":"2021-09-02T23:46:36Z","title":"Do Prompt-Based Models Really Understand the Meaning of their Prompts?","version":2},"cited_work":{"arxiv_id":"2109.01247","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.01247","snapshot_observed_at":"2026-07-02T04:06:34.906379Z","title":"Do prompt-based models really understand the meaning of their prompts? arXiv preprint arXiv:2109.01247","venue":null,"work_id":"e5ccc60b-711d-4f1b-a2fa-2e9b85020453","year":null},"citing_paper":{"arxiv_id":"2606.04273","last_updated":"2026-06-02T22:58:19Z","snapshot_observed_at":"2026-07-06T23:44:23.633099Z","submitted_at":"2026-06-02T22:58:19Z","title":"Characterizing initial human-AI proof formalization workflows","version":1},"reference_index":214,"source":"arxiv_source","source_observed_at":"2026-06-28T09:29:50.282874Z"},"links":{"cited_paper":"/paper/2109.01247","citing_paper":"/paper/2606.04273"},"observation_digest":"sha256:366c69186886adb34070eb392b8bd5b427c284381e19e5721363afd1f3aef59f","observation_id":"47bd2fa6-47b3-415e-92c1-edc5ac339907","resolution":{"observed_at":"2026-07-02T04:06:34.908012Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.01247","last_updated":"2022-04-21T16:03:20Z","snapshot_observed_at":"2026-07-06T11:43:54.154781Z","submitted_at":"2021-09-02T23:46:36Z","title":"Do Prompt-Based Models Really Understand the Meaning of their Prompts?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.01247","snapshot_observed_at":"2026-08-07T13:57:11.478970Z","title":"Do prompt-based models really understand the meaning of their prompts?","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.06154","last_updated":"2026-08-06T15:21:42Z","snapshot_observed_at":"2026-08-09T02:13:11.059684Z","submitted_at":"2026-08-06T15:21:42Z","title":"Visual Grounding in Zero-Shot Vision-Language Control","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T13:57:11.478970Z"},"links":{"cited_paper":"/paper/2109.01247","citing_paper":"/paper/2608.06154"},"observation_digest":"sha256:d49954ddba3a3f085a79c5cd4f0afa9243a6dfd39539c0ac8e4481fb0f039ec8","observation_id":"db19dba4-69c2-4470-8fa9-744f8721c355","resolution":{"observed_at":"2026-08-07T13:57:11.478970Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2109.01247/citation-record","integrity":"/paper/2109.01247/integrity","json":"/paper/2109.01247/citation-record.json","paper":"/paper/2109.01247"},"outbound":[],"paper":{"arxiv_id":"2109.01247","last_updated":"2022-04-21T16:03:20Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T11:43:54.154781Z","submitted_at":"2021-09-02T23:46:36Z","title":"Do Prompt-Based Models Really Understand the Meaning of their Prompts?"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2109.01247."}