{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:UXMG2TDBD6XDY3D5FUJVCWCGTA","short_pith_number":"pith:UXMG2TDB","canonical_record":{"source":{"id":"2505.07251","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-12T05:57:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"dc3162818dcb785c2122d1ab29ff866af5ab74ace678af10a57aeb8f92adda10","abstract_canon_sha256":"dd519e740d096d88970d00a6c9be5cbc8ac66fa35851636fef85c2abe50ab48e"},"schema_version":"1.0"},"canonical_sha256":"a5d86d4c611fae3c6c7d2d135158469807c232b92b6f174e048543e9dc5682aa","source":{"kind":"arxiv","id":"2505.07251","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.07251","created_at":"2026-07-05T11:01:44Z"},{"alias_kind":"arxiv_version","alias_value":"2505.07251v1","created_at":"2026-07-05T11:01:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.07251","created_at":"2026-07-05T11:01:44Z"},{"alias_kind":"pith_short_12","alias_value":"UXMG2TDBD6XD","created_at":"2026-07-05T11:01:44Z"},{"alias_kind":"pith_short_16","alias_value":"UXMG2TDBD6XDY3D5","created_at":"2026-07-05T11:01:44Z"},{"alias_kind":"pith_short_8","alias_value":"UXMG2TDB","created_at":"2026-07-05T11:01:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:UXMG2TDBD6XDY3D5FUJVCWCGTA","target":"record","payload":{"canonical_record":{"source":{"id":"2505.07251","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-12T05:57:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"dc3162818dcb785c2122d1ab29ff866af5ab74ace678af10a57aeb8f92adda10","abstract_canon_sha256":"dd519e740d096d88970d00a6c9be5cbc8ac66fa35851636fef85c2abe50ab48e"},"schema_version":"1.0"},"canonical_sha256":"a5d86d4c611fae3c6c7d2d135158469807c232b92b6f174e048543e9dc5682aa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:01:44.995651Z","signature_b64":"J850NIDfCxw1W2DZcx+jdEg8HGD1BzUpYX3X2v5J6UVV6Tb+deh8VABqFbxiSlUrFcWb4FHPqpXAN8Q52mGoAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a5d86d4c611fae3c6c7d2d135158469807c232b92b6f174e048543e9dc5682aa","last_reissued_at":"2026-07-05T11:01:44.995182Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:01:44.995182Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.07251","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:01:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vRieUw6YKshLslXHH8C5cEyaqyScWLNh3kIJ8fbwsSdl3TSxBD2ohmdHWo0bJqHc12H0Kmt91bypKFYe/GcgAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T11:45:43.990073Z"},"content_sha256":"77c4780b1849234623a5a453476b3e2891f88e15c5e07169515ea3f4f9b5a838","schema_version":"1.0","event_id":"sha256:77c4780b1849234623a5a453476b3e2891f88e15c5e07169515ea3f4f9b5a838"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:UXMG2TDBD6XDY3D5FUJVCWCGTA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Incomplete In-context Learning","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Wenqiang Wang, Yangshijie Zhang","submitted_at":"2025-05-12T05:57:39Z","abstract_excerpt":"Large vision language models (LVLMs) achieve remarkable performance through Vision In-context Learning (VICL), a process that depends significantly on demonstrations retrieved from an extensive collection of annotated examples (retrieval database). Existing studies often assume that the retrieval database contains annotated examples for all labels. However, in real-world scenarios, delays in database updates or incomplete data annotation may result in the retrieval database containing labeled samples for only a subset of classes. We refer to this phenomenon as an \\textbf{incomplete retrieval d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.07251","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2505.07251/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:01:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cbpDMNATy5vsv1uJ0qfDqHIVQjPrH0ZvZ7VnNm15J4O1FnJTU1jxTEOFmZoYab76veaKpwfHgXs4YiL2Z/JpCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T11:45:43.991175Z"},"content_sha256":"7eb53819988b5b3becccf1287146af2f6b9bd3d31207f9be35e51156a9388b35","schema_version":"1.0","event_id":"sha256:7eb53819988b5b3becccf1287146af2f6b9bd3d31207f9be35e51156a9388b35"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UXMG2TDBD6XDY3D5FUJVCWCGTA/bundle.json","state_url":"https://pith.science/pith/UXMG2TDBD6XDY3D5FUJVCWCGTA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UXMG2TDBD6XDY3D5FUJVCWCGTA/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-16T11:45:43Z","links":{"resolver":"https://pith.science/pith/UXMG2TDBD6XDY3D5FUJVCWCGTA","bundle":"https://pith.science/pith/UXMG2TDBD6XDY3D5FUJVCWCGTA/bundle.json","state":"https://pith.science/pith/UXMG2TDBD6XDY3D5FUJVCWCGTA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UXMG2TDBD6XDY3D5FUJVCWCGTA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:UXMG2TDBD6XDY3D5FUJVCWCGTA","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"dd519e740d096d88970d00a6c9be5cbc8ac66fa35851636fef85c2abe50ab48e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-12T05:57:39Z","title_canon_sha256":"dc3162818dcb785c2122d1ab29ff866af5ab74ace678af10a57aeb8f92adda10"},"schema_version":"1.0","source":{"id":"2505.07251","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.07251","created_at":"2026-07-05T11:01:44Z"},{"alias_kind":"arxiv_version","alias_value":"2505.07251v1","created_at":"2026-07-05T11:01:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.07251","created_at":"2026-07-05T11:01:44Z"},{"alias_kind":"pith_short_12","alias_value":"UXMG2TDBD6XD","created_at":"2026-07-05T11:01:44Z"},{"alias_kind":"pith_short_16","alias_value":"UXMG2TDBD6XDY3D5","created_at":"2026-07-05T11:01:44Z"},{"alias_kind":"pith_short_8","alias_value":"UXMG2TDB","created_at":"2026-07-05T11:01:44Z"}],"graph_snapshots":[{"event_id":"sha256:7eb53819988b5b3becccf1287146af2f6b9bd3d31207f9be35e51156a9388b35","target":"graph","created_at":"2026-07-05T11:01:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2505.07251/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large vision language models (LVLMs) achieve remarkable performance through Vision In-context Learning (VICL), a process that depends significantly on demonstrations retrieved from an extensive collection of annotated examples (retrieval database). Existing studies often assume that the retrieval database contains annotated examples for all labels. However, in real-world scenarios, delays in database updates or incomplete data annotation may result in the retrieval database containing labeled samples for only a subset of classes. We refer to this phenomenon as an \\textbf{incomplete retrieval d","authors_text":"Wenqiang Wang, Yangshijie Zhang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-12T05:57:39Z","title":"Incomplete In-context Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.07251","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:77c4780b1849234623a5a453476b3e2891f88e15c5e07169515ea3f4f9b5a838","target":"record","created_at":"2026-07-05T11:01:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"dd519e740d096d88970d00a6c9be5cbc8ac66fa35851636fef85c2abe50ab48e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-12T05:57:39Z","title_canon_sha256":"dc3162818dcb785c2122d1ab29ff866af5ab74ace678af10a57aeb8f92adda10"},"schema_version":"1.0","source":{"id":"2505.07251","kind":"arxiv","version":1}},"canonical_sha256":"a5d86d4c611fae3c6c7d2d135158469807c232b92b6f174e048543e9dc5682aa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a5d86d4c611fae3c6c7d2d135158469807c232b92b6f174e048543e9dc5682aa","first_computed_at":"2026-07-05T11:01:44.995182Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:01:44.995182Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"J850NIDfCxw1W2DZcx+jdEg8HGD1BzUpYX3X2v5J6UVV6Tb+deh8VABqFbxiSlUrFcWb4FHPqpXAN8Q52mGoAg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:01:44.995651Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.07251","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:77c4780b1849234623a5a453476b3e2891f88e15c5e07169515ea3f4f9b5a838","sha256:7eb53819988b5b3becccf1287146af2f6b9bd3d31207f9be35e51156a9388b35"],"state_sha256":"60e47305552b96ce4dec5866c0b87ab650cae12ec2a0e23447df36496b0ecb99"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"upUfePvh7Qqip6s2ePw8kIWSMXJrd9GwCPnuaF2LKMyz6yLLfJEgUpwCWKy0OaUmZhlmNwGqMuU+5VjoWpB6AA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T11:45:43.998550Z","bundle_sha256":"8f03c616100d68947eb193601220c8b2d851e62d283fd61ffbba250adcd6fe84"}}