{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OCMIMK4N7JFGPZXJLKW3ALVWPW","short_pith_number":"pith:OCMIMK4N","canonical_record":{"source":{"id":"2405.09798","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-16T04:02:43Z","cross_cats_sorted":["cs.AI","cs.CL","cs.CV"],"title_canon_sha256":"f020cbdf4b1ef9391883ce00ea0a39d430ac5640863657f007e73e49507a7096","abstract_canon_sha256":"30d2778c54b4e6c64947ff93d51314475c5fb63b9ffa0dde4145f82405875885"},"schema_version":"1.0"},"canonical_sha256":"7098862b8dfa4a67e6e95aadb02eb67da2c348b9a47b2a263cabb4365dcaffe4","source":{"kind":"arxiv","id":"2405.09798","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.09798","created_at":"2026-07-05T09:16:15Z"},{"alias_kind":"arxiv_version","alias_value":"2405.09798v2","created_at":"2026-07-05T09:16:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.09798","created_at":"2026-07-05T09:16:15Z"},{"alias_kind":"pith_short_12","alias_value":"OCMIMK4N7JFG","created_at":"2026-07-05T09:16:15Z"},{"alias_kind":"pith_short_16","alias_value":"OCMIMK4N7JFGPZXJ","created_at":"2026-07-05T09:16:15Z"},{"alias_kind":"pith_short_8","alias_value":"OCMIMK4N","created_at":"2026-07-05T09:16:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OCMIMK4N7JFGPZXJLKW3ALVWPW","target":"record","payload":{"canonical_record":{"source":{"id":"2405.09798","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-16T04:02:43Z","cross_cats_sorted":["cs.AI","cs.CL","cs.CV"],"title_canon_sha256":"f020cbdf4b1ef9391883ce00ea0a39d430ac5640863657f007e73e49507a7096","abstract_canon_sha256":"30d2778c54b4e6c64947ff93d51314475c5fb63b9ffa0dde4145f82405875885"},"schema_version":"1.0"},"canonical_sha256":"7098862b8dfa4a67e6e95aadb02eb67da2c348b9a47b2a263cabb4365dcaffe4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:16:15.143134Z","signature_b64":"TDizdriMKJXKlZr50LXf+0Dq3bVCDcNt7C5hXQkx+UvCGyvIQTVsZFOKj9+FP+oO7RdnTOGRcESZDn697rgMCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7098862b8dfa4a67e6e95aadb02eb67da2c348b9a47b2a263cabb4365dcaffe4","last_reissued_at":"2026-07-05T09:16:15.142685Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:16:15.142685Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.09798","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:16:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tLgg5L+I4imIrnKRxK/eOs0+irMtK9g0dRTViAm9vmXvIjJFLcAsXCo9gf24fZhkxRSKa74+ClFvzgUqMYXPAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T12:27:07.987002Z"},"content_sha256":"08d78695a775d3af068362bbe5cdd706e51fdcdf4bc92bac9922153de576bd59","schema_version":"1.0","event_id":"sha256:08d78695a775d3af068362bbe5cdd706e51fdcdf4bc92bac9922153de576bd59"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OCMIMK4N7JFGPZXJLKW3ALVWPW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Many-Shot In-Context Learning in Multimodal Foundation Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.CV"],"primary_cat":"cs.LG","authors_text":"Andrew Y. Ng, Jeremy Irvin, Ji Hun Wang, Jonathan H. Chen, Muhammad Ahmed Chaudhry, Yixing Jiang","submitted_at":"2024-05-16T04:02:43Z","abstract_excerpt":"Large language models are effective at few-shot in-context learning (ICL). Recent advancements in multimodal foundation models have enabled unprecedentedly long context windows, presenting an opportunity to explore their capability to perform ICL with many more demonstrating examples. In this work, we evaluate the performance of multimodal foundation models scaling from few-shot to many-shot ICL. We benchmark GPT-4o and Gemini 1.5 Pro across 14 datasets spanning multiple domains (natural imagery, medical imagery, remote sensing, and molecular imagery) and tasks (image classification, visual QA"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.09798","kind":"arxiv","version":2},"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/2405.09798/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":"2026-07-05T09:16:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JDnUtINp35HUn0vwMhWdaEQKAPw8T819Ttdnp1xZBR1RTe5FRxyh84Wa3ud9yie6CyuGXpjEUTNPfM50NEJgBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T12:27:07.988054Z"},"content_sha256":"72323721041914e26d03c1f733d217ccf81bc57429acdf4c64065fca032fc670","schema_version":"1.0","event_id":"sha256:72323721041914e26d03c1f733d217ccf81bc57429acdf4c64065fca032fc670"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OCMIMK4N7JFGPZXJLKW3ALVWPW/bundle.json","state_url":"https://pith.science/pith/OCMIMK4N7JFGPZXJLKW3ALVWPW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OCMIMK4N7JFGPZXJLKW3ALVWPW/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":"2026-08-06T12:27:07Z","links":{"resolver":"https://pith.science/pith/OCMIMK4N7JFGPZXJLKW3ALVWPW","bundle":"https://pith.science/pith/OCMIMK4N7JFGPZXJLKW3ALVWPW/bundle.json","state":"https://pith.science/pith/OCMIMK4N7JFGPZXJLKW3ALVWPW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OCMIMK4N7JFGPZXJLKW3ALVWPW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OCMIMK4N7JFGPZXJLKW3ALVWPW","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":"30d2778c54b4e6c64947ff93d51314475c5fb63b9ffa0dde4145f82405875885","cross_cats_sorted":["cs.AI","cs.CL","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-16T04:02:43Z","title_canon_sha256":"f020cbdf4b1ef9391883ce00ea0a39d430ac5640863657f007e73e49507a7096"},"schema_version":"1.0","source":{"id":"2405.09798","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.09798","created_at":"2026-07-05T09:16:15Z"},{"alias_kind":"arxiv_version","alias_value":"2405.09798v2","created_at":"2026-07-05T09:16:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.09798","created_at":"2026-07-05T09:16:15Z"},{"alias_kind":"pith_short_12","alias_value":"OCMIMK4N7JFG","created_at":"2026-07-05T09:16:15Z"},{"alias_kind":"pith_short_16","alias_value":"OCMIMK4N7JFGPZXJ","created_at":"2026-07-05T09:16:15Z"},{"alias_kind":"pith_short_8","alias_value":"OCMIMK4N","created_at":"2026-07-05T09:16:15Z"}],"graph_snapshots":[{"event_id":"sha256:72323721041914e26d03c1f733d217ccf81bc57429acdf4c64065fca032fc670","target":"graph","created_at":"2026-07-05T09:16:15Z","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/2405.09798/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models are effective at few-shot in-context learning (ICL). Recent advancements in multimodal foundation models have enabled unprecedentedly long context windows, presenting an opportunity to explore their capability to perform ICL with many more demonstrating examples. In this work, we evaluate the performance of multimodal foundation models scaling from few-shot to many-shot ICL. We benchmark GPT-4o and Gemini 1.5 Pro across 14 datasets spanning multiple domains (natural imagery, medical imagery, remote sensing, and molecular imagery) and tasks (image classification, visual QA","authors_text":"Andrew Y. Ng, Jeremy Irvin, Ji Hun Wang, Jonathan H. Chen, Muhammad Ahmed Chaudhry, Yixing Jiang","cross_cats":["cs.AI","cs.CL","cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-16T04:02:43Z","title":"Many-Shot In-Context Learning in Multimodal Foundation Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.09798","kind":"arxiv","version":2},"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":"sha256:08d78695a775d3af068362bbe5cdd706e51fdcdf4bc92bac9922153de576bd59","target":"record","created_at":"2026-07-05T09:16:15Z","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":"30d2778c54b4e6c64947ff93d51314475c5fb63b9ffa0dde4145f82405875885","cross_cats_sorted":["cs.AI","cs.CL","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-05-16T04:02:43Z","title_canon_sha256":"f020cbdf4b1ef9391883ce00ea0a39d430ac5640863657f007e73e49507a7096"},"schema_version":"1.0","source":{"id":"2405.09798","kind":"arxiv","version":2}},"canonical_sha256":"7098862b8dfa4a67e6e95aadb02eb67da2c348b9a47b2a263cabb4365dcaffe4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7098862b8dfa4a67e6e95aadb02eb67da2c348b9a47b2a263cabb4365dcaffe4","first_computed_at":"2026-07-05T09:16:15.142685Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:16:15.142685Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TDizdriMKJXKlZr50LXf+0Dq3bVCDcNt7C5hXQkx+UvCGyvIQTVsZFOKj9+FP+oO7RdnTOGRcESZDn697rgMCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:16:15.143134Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.09798","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:08d78695a775d3af068362bbe5cdd706e51fdcdf4bc92bac9922153de576bd59","sha256:72323721041914e26d03c1f733d217ccf81bc57429acdf4c64065fca032fc670"],"state_sha256":"de62707f4c39015f1b6501ad7037003e6b545a5782a2e6d713b2b3817b1d9dc2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yJBdlAXtGsecGue7IWbxnbNfNsAYn74EUCtPdBhoEE9ytAQ/AH5NLufZDWzkofn37qIMIkPHKPPGQiT4UWFxAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T12:27:07.993887Z","bundle_sha256":"6f253e080dbae917ca5da8fa13b6163bcca52de8f20105686be628d6565da5fc"}}