{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:NYQZZD2HHPT5DWVWEWJ26FJPY2","short_pith_number":"pith:NYQZZD2H","canonical_record":{"source":{"id":"2411.02796","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-05T04:10:59Z","cross_cats_sorted":["cs.AI","cs.CV","q-bio.GN"],"title_canon_sha256":"a5ac77f440aa8a3036d541a7306a4efa5f3d18b99cc26aecc36190c89af19765","abstract_canon_sha256":"992385dc532e7137d898e63aeb8341927bc15966d61796097632878f1409fc6b"},"schema_version":"1.0"},"canonical_sha256":"6e219c8f473be7d1dab62593af152fc6a8b15f900bba1c9603172a7b4efdcd7a","source":{"kind":"arxiv","id":"2411.02796","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.02796","created_at":"2026-07-05T10:36:31Z"},{"alias_kind":"arxiv_version","alias_value":"2411.02796v2","created_at":"2026-07-05T10:36:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.02796","created_at":"2026-07-05T10:36:31Z"},{"alias_kind":"pith_short_12","alias_value":"NYQZZD2HHPT5","created_at":"2026-07-05T10:36:31Z"},{"alias_kind":"pith_short_16","alias_value":"NYQZZD2HHPT5DWVW","created_at":"2026-07-05T10:36:31Z"},{"alias_kind":"pith_short_8","alias_value":"NYQZZD2H","created_at":"2026-07-05T10:36:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:NYQZZD2HHPT5DWVWEWJ26FJPY2","target":"record","payload":{"canonical_record":{"source":{"id":"2411.02796","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-05T04:10:59Z","cross_cats_sorted":["cs.AI","cs.CV","q-bio.GN"],"title_canon_sha256":"a5ac77f440aa8a3036d541a7306a4efa5f3d18b99cc26aecc36190c89af19765","abstract_canon_sha256":"992385dc532e7137d898e63aeb8341927bc15966d61796097632878f1409fc6b"},"schema_version":"1.0"},"canonical_sha256":"6e219c8f473be7d1dab62593af152fc6a8b15f900bba1c9603172a7b4efdcd7a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:36:31.037856Z","signature_b64":"5Zz+Hp/xhKkuMsUB35IfAtmPluwstGwH4fPdYjnqtCxvRu2oLxrui95zkgxBslgdDL027Jes19cdmN4aWa9mCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6e219c8f473be7d1dab62593af152fc6a8b15f900bba1c9603172a7b4efdcd7a","last_reissued_at":"2026-07-05T10:36:31.037249Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:36:31.037249Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.02796","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":"2026-07-05T10:36:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ctO2B19CaM0pccaG0wjKfQwovUaB238Yyi1jU3jdp0RRCOT0CR1pig63GL+MKLJ+TGn+nUwIl+nx/y76I02dBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T00:03:57.304908Z"},"content_sha256":"772ca00c1f0d4330d1264c3c701b857ff905079456fe4d9135cf5308f16049bd","schema_version":"1.0","event_id":"sha256:772ca00c1f0d4330d1264c3c701b857ff905079456fe4d9135cf5308f16049bd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:NYQZZD2HHPT5DWVWEWJ26FJPY2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Specialized Foundation Models Struggle to Beat Supervised Baselines","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV","q-bio.GN"],"primary_cat":"cs.LG","authors_text":"Alexander Shen, Ameet Talwalkar, Junhong Shen, Mikhail Khodak, Ritvik Gupta, Wenduo Cheng, Zongzhe Xu","submitted_at":"2024-11-05T04:10:59Z","abstract_excerpt":"Following its success for vision and text, the \"foundation model\" (FM) paradigm -- pretraining large models on massive data, then fine-tuning on target tasks -- has rapidly expanded to domains in the sciences, engineering, healthcare, and beyond. Has this achieved what the original FMs accomplished, i.e. the supplanting of traditional supervised learning in their domains? To answer we look at three modalities -- genomics, satellite imaging, and time series -- with multiple recent FMs and compare them to a standard supervised learning workflow: model development, hyperparameter tuning, and trai"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.02796","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/2411.02796/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":"2026-07-05T10:36:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sEnYhuEInrYJor9a4xNzbdJ17pQqjJ1mAluhPlstj8KyUpHpQVwEGNiTBfCJYwXro+SIDoL36ejM4GNmYoA2DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T00:03:57.305456Z"},"content_sha256":"92a88005718ad0290cdaaf124e5e2645569b2ba4a5ee8760182710fefc84ccd1","schema_version":"1.0","event_id":"sha256:92a88005718ad0290cdaaf124e5e2645569b2ba4a5ee8760182710fefc84ccd1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NYQZZD2HHPT5DWVWEWJ26FJPY2/bundle.json","state_url":"https://pith.science/pith/NYQZZD2HHPT5DWVWEWJ26FJPY2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NYQZZD2HHPT5DWVWEWJ26FJPY2/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":"2026-08-05T00:03:57Z","links":{"resolver":"https://pith.science/pith/NYQZZD2HHPT5DWVWEWJ26FJPY2","bundle":"https://pith.science/pith/NYQZZD2HHPT5DWVWEWJ26FJPY2/bundle.json","state":"https://pith.science/pith/NYQZZD2HHPT5DWVWEWJ26FJPY2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NYQZZD2HHPT5DWVWEWJ26FJPY2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NYQZZD2HHPT5DWVWEWJ26FJPY2","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":"992385dc532e7137d898e63aeb8341927bc15966d61796097632878f1409fc6b","cross_cats_sorted":["cs.AI","cs.CV","q-bio.GN"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-05T04:10:59Z","title_canon_sha256":"a5ac77f440aa8a3036d541a7306a4efa5f3d18b99cc26aecc36190c89af19765"},"schema_version":"1.0","source":{"id":"2411.02796","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.02796","created_at":"2026-07-05T10:36:31Z"},{"alias_kind":"arxiv_version","alias_value":"2411.02796v2","created_at":"2026-07-05T10:36:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.02796","created_at":"2026-07-05T10:36:31Z"},{"alias_kind":"pith_short_12","alias_value":"NYQZZD2HHPT5","created_at":"2026-07-05T10:36:31Z"},{"alias_kind":"pith_short_16","alias_value":"NYQZZD2HHPT5DWVW","created_at":"2026-07-05T10:36:31Z"},{"alias_kind":"pith_short_8","alias_value":"NYQZZD2H","created_at":"2026-07-05T10:36:31Z"}],"graph_snapshots":[{"event_id":"sha256:92a88005718ad0290cdaaf124e5e2645569b2ba4a5ee8760182710fefc84ccd1","target":"graph","created_at":"2026-07-05T10:36:31Z","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/2411.02796/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Following its success for vision and text, the \"foundation model\" (FM) paradigm -- pretraining large models on massive data, then fine-tuning on target tasks -- has rapidly expanded to domains in the sciences, engineering, healthcare, and beyond. Has this achieved what the original FMs accomplished, i.e. the supplanting of traditional supervised learning in their domains? To answer we look at three modalities -- genomics, satellite imaging, and time series -- with multiple recent FMs and compare them to a standard supervised learning workflow: model development, hyperparameter tuning, and trai","authors_text":"Alexander Shen, Ameet Talwalkar, Junhong Shen, Mikhail Khodak, Ritvik Gupta, Wenduo Cheng, Zongzhe Xu","cross_cats":["cs.AI","cs.CV","q-bio.GN"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-05T04:10:59Z","title":"Specialized Foundation Models Struggle to Beat Supervised Baselines"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.02796","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":"sha256:772ca00c1f0d4330d1264c3c701b857ff905079456fe4d9135cf5308f16049bd","target":"record","created_at":"2026-07-05T10:36:31Z","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":"992385dc532e7137d898e63aeb8341927bc15966d61796097632878f1409fc6b","cross_cats_sorted":["cs.AI","cs.CV","q-bio.GN"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-05T04:10:59Z","title_canon_sha256":"a5ac77f440aa8a3036d541a7306a4efa5f3d18b99cc26aecc36190c89af19765"},"schema_version":"1.0","source":{"id":"2411.02796","kind":"arxiv","version":2}},"canonical_sha256":"6e219c8f473be7d1dab62593af152fc6a8b15f900bba1c9603172a7b4efdcd7a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6e219c8f473be7d1dab62593af152fc6a8b15f900bba1c9603172a7b4efdcd7a","first_computed_at":"2026-07-05T10:36:31.037249Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:36:31.037249Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5Zz+Hp/xhKkuMsUB35IfAtmPluwstGwH4fPdYjnqtCxvRu2oLxrui95zkgxBslgdDL027Jes19cdmN4aWa9mCw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:36:31.037856Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.02796","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:772ca00c1f0d4330d1264c3c701b857ff905079456fe4d9135cf5308f16049bd","sha256:92a88005718ad0290cdaaf124e5e2645569b2ba4a5ee8760182710fefc84ccd1"],"state_sha256":"d6294fa85c8c9cbfe9436a3009d59ef519d1fc6c563b686939dfae368d0620cc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j2zySArtV6VJWmh3m80NbeybexOLPe0efb1y7iU2L4o5Ql6/he4k5+jUxOZdFThHNz7NMzxk/6dn6pHDU5SPCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T00:03:57.309168Z","bundle_sha256":"c36b1c84d256a9a32859a78000461cdeed74c90f40d2829e38594360d93bc8b7"}}