{"as_of":"2026-08-09T00:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:849e7c9cdd24e98b5f5f896dcfcbcff3a775dd4655c8a05f1d7e8befa8cf3e19","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:49:40.214128Z","state":"measured"},{"denominator":47,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":47,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2506.12796/citation-record","integrity":"/paper/2506.12796/integrity","json":"/paper/2506.12796/citation-record.json","paper":"/paper/2506.12796"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:36.790885Z","title":"online\" 'onlinestring :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:36.790885Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:cf6e8fdde86c784d42201460e720827119688f88180ec77e0979de47a6998c28","observation_id":"a5ca25af-4d58-4ab0-b55c-ad5b089de4d9","resolution":{"observed_at":"2026-08-07T00:49:36.790885Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:36.835153Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:36.835153Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:6c6376754ca8022e996bd91eb629e021be852ebd66ec304226380df0fbe8ab45","observation_id":"aeed939e-5029-40d6-b4c7-c1a404dd37a7","resolution":{"observed_at":"2026-08-07T00:49:36.835153Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:43.796624Z","title":null,"venue":null,"work_id":"1826a92a-9f32-48c5-a86c-5d95c2dab11c","year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:36.890571Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:905662a62c331a821a0ad385c7bf9d4f97fc3e159f7a043c5a829c827bd515f3","observation_id":"a67e1444-b14b-47ee-b0e2-0f0e5077a855","resolution":{"observed_at":"2026-08-07T00:49:43.880802Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:43.644755Z","title":null,"venue":null,"work_id":"ed08b738-c8bc-49cd-a32f-d7ec2b83659f","year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:36.956244Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:f84778d0fe679bcaa50dd421b658e6cfb7ba41754be0c07671846849140bee9e","observation_id":"c3ccb70b-9608-48b0-b31a-212c57202e40","resolution":{"observed_at":"2026-08-07T00:49:43.716093Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:43.529794Z","title":null,"venue":null,"work_id":"e5cad882-eeb5-469c-9599-f7a726b3c625","year":2015},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:37.035745Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:b68bdc2cbbdcfd77cd148b4d8cd5d0b845513a0fdecdf37b967c3f1acac2e841","observation_id":"4bf84759-d3a6-461a-8b72-448da92d47f9","resolution":{"observed_at":"2026-08-07T00:49:43.573481Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:37.106677Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:37.106677Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:93ce61297befac1db2991abe3513bc76cddffcbda31d9e61bc84764cf5478a57","observation_id":"442187f5-046c-471a-bf67-805ee5e58b35","resolution":{"observed_at":"2026-08-07T00:49:37.106677Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:37.180151Z","title":null,"venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:37.180151Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:6dedd16c6becd7867f268e73eadcc624ab46e4046f6a48306ac7373cdee004f6","observation_id":"e176a7da-df19-4d5d-aaf4-bb029084aaa5","resolution":{"observed_at":"2026-08-07T00:49:37.180151Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.00234","last_updated":"2024-10-05T11:47:02Z","snapshot_observed_at":"2026-07-06T14:36:25.690733Z","submitted_at":"2022-12-31T15:57:09Z","title":"A Survey on In-context Learning","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.00234","snapshot_observed_at":"2026-08-07T00:49:37.244761Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:37.244761Z"},"links":{"cited_paper":"/paper/2301.00234","citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:e76dfe7d442eca3c60d3c08778c24bc4051e155011cdb0b6e62dfe1b16a6da7a","observation_id":"ae87caeb-6a82-449e-93d7-190b4cf0d32f","resolution":{"observed_at":"2026-08-07T00:49:37.244761Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:43.353643Z","title":null,"venue":null,"work_id":"cec5af83-315f-46be-8837-e41ceba509c7","year":2023},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:37.319251Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:311afc5fd284b050df4059c27e9069f4f627b7673d5b453e9aecb65f672fb688","observation_id":"2968152e-04ce-40d1-a266-02f813b9dcc5","resolution":{"observed_at":"2026-08-07T00:49:43.437642Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:43.235807Z","title":null,"venue":null,"work_id":"42133abf-a5eb-45cc-82e5-ecbd4fed8b94","year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:37.394499Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:b85920b0ca5a6761ddc8524dda1753d0dd34d0d7d02be8dafe9fcd84e921bca8","observation_id":"5febf294-0b70-40ab-9658-7d4b5991c979","resolution":{"observed_at":"2026-08-07T00:49:43.293712Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2412.12276","last_updated":"2025-06-02T12:55:12Z","snapshot_observed_at":"2026-08-06T00:48:12.163739Z","submitted_at":"2024-12-16T19:00:18Z","title":"Emergence and Effectiveness of Task Vectors in In-Context Learning: An Encoder Decoder Perspective","version":3},"cited_work":{"arxiv_id":"2412.12276","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.12276","snapshot_observed_at":"2026-08-07T00:49:40.740002Z","title":"Emergence and Effectiveness of Task Vectors in In-Context Learning: An Encoder Decoder Perspective","venue":"cs.CL","work_id":"10e08331-e96b-4935-bc4c-bd658c013bd1","year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:37.474320Z"},"links":{"cited_paper":"/paper/2412.12276","citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:359c9a4927a3bb3c71b9cd3efe6637246eafde8c0b84c3c44a28a4e74bf2d241","observation_id":"bfb181bb-915d-4989-8840-f4066b212da2","resolution":{"observed_at":"2026-08-07T00:49:40.766596Z","resolver_source":"local_arxiv","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":"2205.10183","last_updated":"2022-10-05T01:33:07Z","snapshot_observed_at":"2026-07-06T13:12:05.091944Z","submitted_at":"2022-05-20T13:50:07Z","title":"Prototypical Calibration for Few-shot Learning of Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.10183","snapshot_observed_at":"2026-08-07T00:49:37.546662Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:37.546662Z"},"links":{"cited_paper":"/paper/2205.10183","citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:80919d39da0b2a12ca6fd39d979e592857babdaef8f5bbcb4f4a02cf421988da","observation_id":"fb3eb0ae-08a7-4e75-8b4a-65241c535079","resolution":{"observed_at":"2026-08-07T00:49:37.546662Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:43.078218Z","title":null,"venue":null,"work_id":"52a2112f-5634-4f46-a300-02f03736f33d","year":2023},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:37.665988Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:20ced48a06025f27b596e8293d844b3671c3e1996540ec4e74ed8945f9d33360","observation_id":"f1e43a35-07ed-4359-87bc-01a2379f1c03","resolution":{"observed_at":"2026-08-07T00:49:43.156599Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:37.758999Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:37.758999Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:6cc372cb6a98a8e2b731ddad85900dba7fe653ab00a8464b30e68a08e413ba42","observation_id":"030cb61b-3973-4105-9a94-4a84fffe7fec","resolution":{"observed_at":"2026-08-07T00:49:37.758999Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:42.906067Z","title":null,"venue":null,"work_id":"08b5339f-a376-46f6-bbe8-8f4f367306b6","year":2021},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:37.850001Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:8f9c86de9330d41a206e6909cc97cda73eb7443944c332b94a2a1392ac7c9d1b","observation_id":"4ebb92a4-5aec-4b42-8cc2-39f76f141d1c","resolution":{"observed_at":"2026-08-07T00:49:42.977150Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:42.755923Z","title":null,"venue":null,"work_id":"3d4aaa53-3cb4-4e33-9c3c-b3b6c63daca5","year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:37.915757Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:b5682269be9295271bb0eae575142b777d847f8a9c2a7d49578f5ef4cc2f9e33","observation_id":"2e0e8749-0938-45d2-a7e3-ec6d22765f36","resolution":{"observed_at":"2026-08-07T00:49:42.827229Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2110.04541","last_updated":"2022-03-21T17:57:13Z","snapshot_observed_at":"2026-08-04T03:21:19.108004Z","submitted_at":"2021-10-09T11:05:16Z","title":"The Inductive Bias of In-Context Learning: Rethinking Pretraining Example Design","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.04541","snapshot_observed_at":"2026-08-07T00:49:38.000946Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.000946Z"},"links":{"cited_paper":"/paper/2110.04541","citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:150d7357a779993a3d759a127f44c0c140b3e31a2a3b363e557e3c17e7fec966","observation_id":"e203a2f4-1338-48e8-89a3-6829c384fac5","resolution":{"observed_at":"2026-08-07T00:49:38.000946Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:42.604262Z","title":null,"venue":null,"work_id":"77669987-4b23-4242-a370-6863ba715a44","year":2022},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.086205Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:8f087d14a8d4b90f902fc9896695169e247b5a3a363f0331f08692863cd4e7e9","observation_id":"4760b5d9-ba87-4b1a-b3d9-f6e58c022e96","resolution":{"observed_at":"2026-08-07T00:49:42.675053Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:42.459613Z","title":null,"venue":null,"work_id":"b4bbc184-960d-4556-834c-2d0beebc7e7b","year":2023},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.163247Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:ddec85c46526ac401850b5baa2692b9fc0833fd192a9d89b407e4ea8ee63ee1d","observation_id":"b241d6b8-b894-4b28-87e2-225ad114abf8","resolution":{"observed_at":"2026-08-07T00:49:42.511213Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2308.03281","last_updated":"2023-08-07T03:52:59Z","snapshot_observed_at":"2026-08-04T23:10:23.964516Z","submitted_at":"2023-08-07T03:52:59Z","title":"Towards General Text Embeddings with Multi-stage Contrastive Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.03281","snapshot_observed_at":"2026-08-07T00:49:38.237795Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.237795Z"},"links":{"cited_paper":"/paper/2308.03281","citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:e61ce2b48e829a146590caf1afbc89a247b0dea888098176f5ddb9f36fa34774","observation_id":"c860e59d-614c-419b-979a-6b03d5aa5bd6","resolution":{"observed_at":"2026-08-07T00:49:38.237795Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:38.323200Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.323200Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:fc9ee51dfed20e36794c1685cdf29bc7be692b493abc377d11296862edf07e61","observation_id":"4cccdc65-8d4c-4a93-9c75-2ebdd7823be1","resolution":{"observed_at":"2026-08-07T00:49:38.323200Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:38.391064Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.391064Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:544666ced70daccb7a27999f5f46ee64392994cb6c92600b38dfdc6f3cfb0bb4","observation_id":"611acc23-76a5-470f-918c-bd9e37e92915","resolution":{"observed_at":"2026-08-07T00:49:38.391064Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:38.462012Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.462012Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:41dafe829b69a554715874a0ad7be9c60c347b3fe1d9addbeea7c4f54f64c521","observation_id":"6703978f-3007-4b2b-9f04-6f2dcba660cb","resolution":{"observed_at":"2026-08-07T00:49:38.462012Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.11624","last_updated":"2024-03-23T16:35:45Z","snapshot_observed_at":"2026-08-04T20:49:05.952874Z","submitted_at":"2024-01-21T23:34:42Z","title":"In-context Learning with Retrieved Demonstrations for Language Models: A Survey","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.11624","snapshot_observed_at":"2026-08-07T00:49:38.521648Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.521648Z"},"links":{"cited_paper":"/paper/2401.11624","citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:e2ea5478f20a3523c6375af10b479f3a5fa8c494d226a1de282684f8292efd7a","observation_id":"7c8c4f37-0f8a-4d6c-b47f-2c54a12fa078","resolution":{"observed_at":"2026-08-07T00:49:38.521648Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:42.309818Z","title":null,"venue":null,"work_id":"03ae2442-4b52-41c4-b33b-067d5373770a","year":2022},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.626116Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:250ead8d535827cb01fd38e78fbbeb88d63531af837cf3326ca3d823934c1a42","observation_id":"2f0e438a-7602-4523-ac23-0a36301b1979","resolution":{"observed_at":"2026-08-07T00:49:42.366105Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2401.12087","last_updated":"2024-06-23T13:45:14Z","snapshot_observed_at":"2026-07-06T17:18:52.483885Z","submitted_at":"2024-01-22T16:25:27Z","title":"Revisiting Demonstration Selection Strategies in In-Context Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.12087","snapshot_observed_at":"2026-08-07T00:49:38.691903Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.691903Z"},"links":{"cited_paper":"/paper/2401.12087","citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:a9bbd7f834e153178b9e9bdf54c344a94a4f580a81a27c86ff741a81e9f11424","observation_id":"8746ae8d-4351-4074-adb7-3a74fd4df104","resolution":{"observed_at":"2026-08-07T00:49:38.691903Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:38.767624Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.767624Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:fc167def8159646ce73e025f9d9c537d88ecff4ab29809fe98fc804b4ee9dd23","observation_id":"1f6d2bdb-e0aa-454f-8ba3-a01b9989c08d","resolution":{"observed_at":"2026-08-07T00:49:38.767624Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.09881","last_updated":"2024-12-30T04:27:05Z","snapshot_observed_at":"2026-08-04T17:18:58.384862Z","submitted_at":"2023-10-15T16:40:19Z","title":"In-Context Learning with Iterative Demonstration Selection","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.09881","snapshot_observed_at":"2026-08-07T00:49:38.818636Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.818636Z"},"links":{"cited_paper":"/paper/2310.09881","citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:45d842263cc0108b90e36a4ff62c77810947db9de65ea35c93814d41f365bd51","observation_id":"da544af3-06d5-4e47-8b3f-82b21a1ad16a","resolution":{"observed_at":"2026-08-07T00:49:38.818636Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:38.869198Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.869198Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:74cc6b6ee00afec4abaf8cec49575b53c2e0977d0f4b9b0bdbad4d1778b1bf7a","observation_id":"c471fd26-b26b-4513-bf71-7af7f36d6aad","resolution":{"observed_at":"2026-08-07T00:49:38.869198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:38.933459Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:38.933459Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:1f9fbebb31df73ab464bffc2c28504a1f7b12629f27bb2ee6752f65ffa0df547","observation_id":"ed0a78cd-79ed-469f-af9a-48320a8c5cf0","resolution":{"observed_at":"2026-08-07T00:49:38.933459Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.23099","last_updated":"2024-10-30T15:11:58Z","snapshot_observed_at":"2026-08-08T01:26:47.981076Z","submitted_at":"2024-10-30T15:11:58Z","title":"Comparative Analysis of Demonstration Selection Algorithms for LLM In-Context Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.23099","snapshot_observed_at":"2026-08-07T00:49:39.017932Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.017932Z"},"links":{"cited_paper":"/paper/2410.23099","citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:ae7a6ff6eae08d2c0c9162bdc4930f229daec0142d9c35bce568ffe9a737ea7c","observation_id":"6959d221-584d-4db9-b8ec-16c4c574decf","resolution":{"observed_at":"2026-08-07T00:49:39.017932Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:42.117517Z","title":null,"venue":null,"work_id":"45e7fff0-e346-429a-84d9-85143baa0150","year":2023},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.086957Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:e8f1be9867770f4c6a36e2a74b0a113a8337017de471dfc83cfe7acee4623af9","observation_id":"394e707d-b32e-4d35-ad62-0a41b2f0199a","resolution":{"observed_at":"2026-08-07T00:49:42.197160Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:39.170897Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.170897Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:c231ca491d7c1db9bffa5cd1ee90168f3c4b87106b56cfdd8994fe099918b3ad","observation_id":"35beb8d1-a3b1-48a7-828b-964e03c6af41","resolution":{"observed_at":"2026-08-07T00:49:39.170897Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:41.968675Z","title":null,"venue":null,"work_id":"b7bc383c-b0f2-447b-917e-5ce46b17ee58","year":2023},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.257125Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:54a792060243bcfac7aa9af64d4361c8ad2f388c91399479342a75102b552f3c","observation_id":"5a5c9df5-4aa0-4130-8ddc-2d9fe53f6ede","resolution":{"observed_at":"2026-08-07T00:49:42.035207Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":"8306.2023","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:40.447374Z","title":"Theocharopoulos, Panagiotis Anagnostou, Anastasia Tsoukala, Spiros V","venue":null,"work_id":"d89a9614-e25c-40e3-a1ac-41b131fe736f","year":2023},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.335167Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:9e34cd6df487d38e742310701babacfcdb24853b44a15218dbde0a6bc1a9401a","observation_id":"d1c92669-83bc-445b-b6f0-9e37f86a3dff","resolution":{"observed_at":"2026-08-07T00:49:40.599676Z","resolver_source":"raw_fallback","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:41.825872Z","title":null,"venue":null,"work_id":"1581b094-2711-49d2-9764-61be374be742","year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.396249Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:79d1c7a393d222dc5ca0ed017f79c0a355367c2f5d7e98c9f25043aa7b650145","observation_id":"7061074c-78e5-4562-adba-ef15696888e2","resolution":{"observed_at":"2026-08-07T00:49:41.884206Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:41.685199Z","title":null,"venue":null,"work_id":"45dc30e3-a26d-4d3a-8ba0-b9f75ae1a9bd","year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.460332Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:c696b2dcea62afe86cb9745fc7c5870aab4bd6befc181d9a03a8222c427c001e","observation_id":"cfb03948-ffbe-49de-9cac-03441c32e3f0","resolution":{"observed_at":"2026-08-07T00:49:41.739618Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:39.537198Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.537198Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:af71d79e951873d656ed3aa3a396c8a13aa2c603b894a57c22cf4c0a2bb31670","observation_id":"99c54f67-4cb6-4dd6-bc87-8b28c5c98bb7","resolution":{"observed_at":"2026-08-07T00:49:39.537198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:39.619697Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.619697Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:ee51ba4bcf69d21c60286b71b75272d80786e84bd48dfbfec6f9c084d49ef000","observation_id":"1b8abda2-2ceb-4799-9174-7dd3566b50a4","resolution":{"observed_at":"2026-08-07T00:49:39.619697Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:41.499583Z","title":null,"venue":null,"work_id":"95b46856-f1e3-41aa-ab3b-86e758460727","year":2023},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.680947Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:f050e2a73f6cbcce00fa752c790302000128df05ce29a9a7a3fb2e0ca5b5e17c","observation_id":"8eaf9a5b-8f87-4b7b-9f66-8571559c680d","resolution":{"observed_at":"2026-08-07T00:49:41.583301Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:41.344658Z","title":null,"venue":null,"work_id":"81451610-e8db-4e68-bafd-dd7caedf51cb","year":2021},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.774212Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:b950eb56883400739977e2d31999a03862ac7501aa3a7920676a72f816222633","observation_id":"fc29e0f4-71c8-41e3-a7ee-fb9870b49bb9","resolution":{"observed_at":"2026-08-07T00:49:41.416834Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-07T00:49:39.848568Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.848568Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:8e9c2ae875e1f686d5b8f51d794f7276eccabad33035ff10c39c70c4aa332147","observation_id":"275604ae-98ed-42d6-be8c-01f8a6e78ca0","resolution":{"observed_at":"2026-08-07T00:49:39.848568Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:41.204057Z","title":null,"venue":null,"work_id":"f99179dc-bd2c-41f4-ac9b-cfcaf14963d8","year":2022},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:39.930390Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:bfcd71918b859dd193c2497a1025e7a3d1832b2fc5b3f507a2e5518a91935f15","observation_id":"48a98cf5-7777-4e10-87b2-d762aae5e46f","resolution":{"observed_at":"2026-08-07T00:49:41.272105Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:41.058899Z","title":null,"venue":null,"work_id":"be9a12c2-f84c-43f8-9342-c93760eda14d","year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:40.008174Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:4855ec09b551ef94aa00f5bf68eb1a93b86a9a97050ac7c0be1f3954b085e8bc","observation_id":"8ade06c0-bf19-42b7-bcd7-21c24e88d576","resolution":{"observed_at":"2026-08-07T00:49:41.120409Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:40.071031Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:40.071031Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:09dae2cfdea9c78f85c1ed54a08bfc7ce1612418cf8f1310c90858d9a9e69070","observation_id":"6dfe4dca-40a3-470b-8742-228f85f260c7","resolution":{"observed_at":"2026-08-07T00:49:40.071031Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.17249","last_updated":"2024-12-01T01:36:50Z","snapshot_observed_at":"2026-07-06T16:25:29.858870Z","submitted_at":"2023-09-29T13:55:45Z","title":"Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.17249","snapshot_observed_at":"2026-08-07T00:49:40.146988Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:40.146988Z"},"links":{"cited_paper":"/paper/2309.17249","citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:fa18da56a53849109d7beeb83b8ecb4e4b3f86de3cb087682693a958d5141916","observation_id":"dd0a2572-3b13-4d5e-b6f6-63bb63c60d06","resolution":{"observed_at":"2026-08-07T00:49:40.146988Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:49:40.884962Z","title":null,"venue":null,"work_id":"bad42437-4df3-4660-9137-7f760334499e","year":2024},"citing_paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-07T00:49:40.214128Z"},"links":{"citing_paper":"/paper/2506.12796"},"observation_digest":"sha256:402bc374fcffc1bfdf5c497099b11d7e6d01e4ea010a8a9a50f6925e6ce7c93b","observation_id":"2fd562fe-c42d-488f-ab7f-994f2ace1fa1","resolution":{"observed_at":"2026-08-07T00:49:40.949586Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}}],"paper":{"arxiv_id":"2506.12796","last_updated":"2025-06-17T07:46:17Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T00:39:48.995457Z","submitted_at":"2025-06-15T10:04:42Z","title":"Surprise Calibration for Better In-Context Learning"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":45,"verified_exact":2,"verified_fuzzy":0},"total_outbound_references":47},"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 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2506.12796."}