{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:WEW6ZIVGDCGHTJQE7KO5NTFMMB","short_pith_number":"pith:WEW6ZIVG","canonical_record":{"source":{"id":"2503.12303","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-16T00:25:13Z","cross_cats_sorted":[],"title_canon_sha256":"0600d2f97b5713f921bb6a71188593b20fbfc78241498c8d702f62b145b68130","abstract_canon_sha256":"4123a5a5d24082d8686d6ea064065fc9fa33fe4550efa91a33605432dbb98b23"},"schema_version":"1.0"},"canonical_sha256":"b12deca2a6188c79a604fa9dd6ccac606bca2d6bbf10dd5ac6b42f2c0d9ffb4c","source":{"kind":"arxiv","id":"2503.12303","version":6},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.12303","created_at":"2026-07-05T11:21:44Z"},{"alias_kind":"arxiv_version","alias_value":"2503.12303v6","created_at":"2026-07-05T11:21:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.12303","created_at":"2026-07-05T11:21:44Z"},{"alias_kind":"pith_short_12","alias_value":"WEW6ZIVGDCGH","created_at":"2026-07-05T11:21:44Z"},{"alias_kind":"pith_short_16","alias_value":"WEW6ZIVGDCGHTJQE","created_at":"2026-07-05T11:21:44Z"},{"alias_kind":"pith_short_8","alias_value":"WEW6ZIVG","created_at":"2026-07-05T11:21:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:WEW6ZIVGDCGHTJQE7KO5NTFMMB","target":"record","payload":{"canonical_record":{"source":{"id":"2503.12303","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-16T00:25:13Z","cross_cats_sorted":[],"title_canon_sha256":"0600d2f97b5713f921bb6a71188593b20fbfc78241498c8d702f62b145b68130","abstract_canon_sha256":"4123a5a5d24082d8686d6ea064065fc9fa33fe4550efa91a33605432dbb98b23"},"schema_version":"1.0"},"canonical_sha256":"b12deca2a6188c79a604fa9dd6ccac606bca2d6bbf10dd5ac6b42f2c0d9ffb4c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:21:44.240404Z","signature_b64":"nNxD2ohV8PbDEZkrt8n2ZGhN3rr+A8PD0hcPAeJogWfRDGtbeoGHU+m2iLwHtzFLyZRuxLsG4cSyibvrPlxTDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b12deca2a6188c79a604fa9dd6ccac606bca2d6bbf10dd5ac6b42f2c0d9ffb4c","last_reissued_at":"2026-07-05T11:21:44.239789Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:21:44.239789Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.12303","source_version":6,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:21:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vk8VHAOJH4+6WuNO4wQq5HoZyPmtjY2qZEDLy7sPeZNaXyH5jx2U7xWJFyQa6tmJXmaVrayLzZnpQLHhNbrwBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T15:48:21.214239Z"},"content_sha256":"436e0782ec40e78a2c9edf26b9f1afee8905a5f7ed109b33f22c0587b1d56327","schema_version":"1.0","event_id":"sha256:436e0782ec40e78a2c9edf26b9f1afee8905a5f7ed109b33f22c0587b1d56327"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:WEW6ZIVGDCGHTJQE7KO5NTFMMB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Will Pre-Training Ever End? A First Step Toward Next-Generation Foundation MLLMs via Self-Improving Systematic Cognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chengyue Wu, Chi Chen, Da Peng, Helen Meng, Jen-tse Huang, Maosong Sun, Wei Ke, Xiaoying Zhang, Yipeng Zhang, Zonghao Guo","submitted_at":"2025-03-16T00:25:13Z","abstract_excerpt":"Recent progress in (multimodal) large language models ((M)LLMs) has shifted focus from pre-training to inference-time computation and post-training optimization, largely due to concerns over the availability of high-quality human data. However, these strategies alone are insufficient to drive substantial model improvements. We argue that effective model advancement requires strong synergy among pre-training, inference-time computation, and post-training optimization. In this paper, we introduce Self-Improving cognition (SIcog), a self-learning framework for constructing next-generation foundat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.12303","kind":"arxiv","version":6},"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/2503.12303/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":"2026-07-05T11:21:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oLB7qrw5K2Z7HwLgpKiiLf2ktYtbmGnuE85YWw9e7h08hSUg5/i/5e5iaMNLDhfLIHpDY0+2r8tGuSYkydeeDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T15:48:21.214744Z"},"content_sha256":"76fbd779b6285ac7cd7aa5f706d350cf20fa5dfdad7cfdce090811a52720d244","schema_version":"1.0","event_id":"sha256:76fbd779b6285ac7cd7aa5f706d350cf20fa5dfdad7cfdce090811a52720d244"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WEW6ZIVGDCGHTJQE7KO5NTFMMB/bundle.json","state_url":"https://pith.science/pith/WEW6ZIVGDCGHTJQE7KO5NTFMMB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WEW6ZIVGDCGHTJQE7KO5NTFMMB/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":"2026-08-08T15:48:21Z","links":{"resolver":"https://pith.science/pith/WEW6ZIVGDCGHTJQE7KO5NTFMMB","bundle":"https://pith.science/pith/WEW6ZIVGDCGHTJQE7KO5NTFMMB/bundle.json","state":"https://pith.science/pith/WEW6ZIVGDCGHTJQE7KO5NTFMMB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WEW6ZIVGDCGHTJQE7KO5NTFMMB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WEW6ZIVGDCGHTJQE7KO5NTFMMB","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":"4123a5a5d24082d8686d6ea064065fc9fa33fe4550efa91a33605432dbb98b23","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-16T00:25:13Z","title_canon_sha256":"0600d2f97b5713f921bb6a71188593b20fbfc78241498c8d702f62b145b68130"},"schema_version":"1.0","source":{"id":"2503.12303","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.12303","created_at":"2026-07-05T11:21:44Z"},{"alias_kind":"arxiv_version","alias_value":"2503.12303v6","created_at":"2026-07-05T11:21:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.12303","created_at":"2026-07-05T11:21:44Z"},{"alias_kind":"pith_short_12","alias_value":"WEW6ZIVGDCGH","created_at":"2026-07-05T11:21:44Z"},{"alias_kind":"pith_short_16","alias_value":"WEW6ZIVGDCGHTJQE","created_at":"2026-07-05T11:21:44Z"},{"alias_kind":"pith_short_8","alias_value":"WEW6ZIVG","created_at":"2026-07-05T11:21:44Z"}],"graph_snapshots":[{"event_id":"sha256:76fbd779b6285ac7cd7aa5f706d350cf20fa5dfdad7cfdce090811a52720d244","target":"graph","created_at":"2026-07-05T11:21:44Z","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/2503.12303/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent progress in (multimodal) large language models ((M)LLMs) has shifted focus from pre-training to inference-time computation and post-training optimization, largely due to concerns over the availability of high-quality human data. However, these strategies alone are insufficient to drive substantial model improvements. We argue that effective model advancement requires strong synergy among pre-training, inference-time computation, and post-training optimization. In this paper, we introduce Self-Improving cognition (SIcog), a self-learning framework for constructing next-generation foundat","authors_text":"Chengyue Wu, Chi Chen, Da Peng, Helen Meng, Jen-tse Huang, Maosong Sun, Wei Ke, Xiaoying Zhang, Yipeng Zhang, Zonghao Guo","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-16T00:25:13Z","title":"Will Pre-Training Ever End? A First Step Toward Next-Generation Foundation MLLMs via Self-Improving Systematic Cognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.12303","kind":"arxiv","version":6},"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":"sha256:436e0782ec40e78a2c9edf26b9f1afee8905a5f7ed109b33f22c0587b1d56327","target":"record","created_at":"2026-07-05T11:21:44Z","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":"4123a5a5d24082d8686d6ea064065fc9fa33fe4550efa91a33605432dbb98b23","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-03-16T00:25:13Z","title_canon_sha256":"0600d2f97b5713f921bb6a71188593b20fbfc78241498c8d702f62b145b68130"},"schema_version":"1.0","source":{"id":"2503.12303","kind":"arxiv","version":6}},"canonical_sha256":"b12deca2a6188c79a604fa9dd6ccac606bca2d6bbf10dd5ac6b42f2c0d9ffb4c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b12deca2a6188c79a604fa9dd6ccac606bca2d6bbf10dd5ac6b42f2c0d9ffb4c","first_computed_at":"2026-07-05T11:21:44.239789Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:21:44.239789Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nNxD2ohV8PbDEZkrt8n2ZGhN3rr+A8PD0hcPAeJogWfRDGtbeoGHU+m2iLwHtzFLyZRuxLsG4cSyibvrPlxTDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:21:44.240404Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.12303","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:436e0782ec40e78a2c9edf26b9f1afee8905a5f7ed109b33f22c0587b1d56327","sha256:76fbd779b6285ac7cd7aa5f706d350cf20fa5dfdad7cfdce090811a52720d244"],"state_sha256":"a74292f45e0203b13cf335d6bff25a700f01694983816fdd18b47c6bd27a95f8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h3dnVu6h3JMFlykn+tFc2cARSYu0IKBdLttSCt5IHvazLmA+mnk2XdKf5AYhxqbRBaNKgaXjAEpb7J9tvZQDCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T15:48:21.219579Z","bundle_sha256":"7ab3a7a64188016ef4612bd6a91ba912e6b3b47f36841da09a3fb3710f29c1fc"}}