{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TLPCO3QQRNNSF6TMTJL7WZFUPO","short_pith_number":"pith:TLPCO3QQ","canonical_record":{"source":{"id":"2402.05935","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-08T18:59:48Z","cross_cats_sorted":["cs.AI","cs.CL","cs.LG"],"title_canon_sha256":"8df2dd1f48d18b1b322c199ebd5af8ce4a845e61977f97c7c2850e12366c621c","abstract_canon_sha256":"c51bdeb8ee03f579b587d46af160212808f882514d178fb73be2e539e22382a2"},"schema_version":"1.0"},"canonical_sha256":"9ade276e108b5b22fa6c9a57fb64b47b8bb42ff19d360f8f2c0e13d150afb16f","source":{"kind":"arxiv","id":"2402.05935","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.05935","created_at":"2026-07-05T10:36:23Z"},{"alias_kind":"arxiv_version","alias_value":"2402.05935v3","created_at":"2026-07-05T10:36:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.05935","created_at":"2026-07-05T10:36:23Z"},{"alias_kind":"pith_short_12","alias_value":"TLPCO3QQRNNS","created_at":"2026-07-05T10:36:23Z"},{"alias_kind":"pith_short_16","alias_value":"TLPCO3QQRNNSF6TM","created_at":"2026-07-05T10:36:23Z"},{"alias_kind":"pith_short_8","alias_value":"TLPCO3QQ","created_at":"2026-07-05T10:36:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TLPCO3QQRNNSF6TMTJL7WZFUPO","target":"record","payload":{"canonical_record":{"source":{"id":"2402.05935","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-08T18:59:48Z","cross_cats_sorted":["cs.AI","cs.CL","cs.LG"],"title_canon_sha256":"8df2dd1f48d18b1b322c199ebd5af8ce4a845e61977f97c7c2850e12366c621c","abstract_canon_sha256":"c51bdeb8ee03f579b587d46af160212808f882514d178fb73be2e539e22382a2"},"schema_version":"1.0"},"canonical_sha256":"9ade276e108b5b22fa6c9a57fb64b47b8bb42ff19d360f8f2c0e13d150afb16f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:36:23.867581Z","signature_b64":"ZW3G1Js0JKjYeWZZjoBQeU5fWbKjS2zVoUNrpK9tLcXW+stx+VuNQdkKJon19BbuaWLpZBNs2ouqZc5PattwDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9ade276e108b5b22fa6c9a57fb64b47b8bb42ff19d360f8f2c0e13d150afb16f","last_reissued_at":"2026-07-05T10:36:23.866576Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:36:23.866576Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.05935","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:36:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KsM+n4JfDmACvDfdEOe25+xYI9jL8s7xAAayV0CU7CxIs/yqdE0XwDGNUHGPFU2ZNzTn9llMXXwasS6wJAJdBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T02:40:22.793102Z"},"content_sha256":"f4577d855e977eab95b8a9735216ef68e354365bb4af8a4e488d087024cfea79","schema_version":"1.0","event_id":"sha256:f4577d855e977eab95b8a9735216ef68e354365bb4af8a4e488d087024cfea79"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TLPCO3QQRNNSF6TMTJL7WZFUPO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.LG"],"primary_cat":"cs.CV","authors_text":"Chao Xu, Conghui He, Dongyang Liu, Hao Shao, Hongsheng Li, Junjun He, Kaipeng Zhang, Longtian Qiu, Pan Lu, Peng Gao, Peng Jin, Renrui Zhang, Shijie Geng, Shitian Zhao, Siyuan Huang, Weifeng Lin, Wenqi Shao, Yu Qiao, Ziyi Lin","submitted_at":"2024-02-08T18:59:48Z","abstract_excerpt":"We propose SPHINX-X, an extensive Multimodality Large Language Model (MLLM) series developed upon SPHINX. To improve the architecture and training efficiency, we modify the SPHINX framework by removing redundant visual encoders, bypassing fully-padded sub-images with skip tokens, and simplifying multi-stage training into a one-stage all-in-one paradigm. To fully unleash the potential of MLLMs, we assemble a comprehensive multi-domain and multimodal dataset covering publicly available resources in language, vision, and vision-language tasks. We further enrich this collection with our curated OC"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.05935","kind":"arxiv","version":3},"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/2402.05935/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":"2026-07-05T10:36:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1/0dpFDtNLncSM6jIRG3in+/GpNmNg0bHNevzDsHV5hCcJWxMjRQmJN4aB8ySoq69nfEHO/gR0nULQWsYhu3CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T02:40:22.793516Z"},"content_sha256":"e5941b37b782589052b62cdeb528e2e2773c46f194d4e90a08c896766f6530f1","schema_version":"1.0","event_id":"sha256:e5941b37b782589052b62cdeb528e2e2773c46f194d4e90a08c896766f6530f1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TLPCO3QQRNNSF6TMTJL7WZFUPO/bundle.json","state_url":"https://pith.science/pith/TLPCO3QQRNNSF6TMTJL7WZFUPO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TLPCO3QQRNNSF6TMTJL7WZFUPO/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":"2026-07-07T02:40:22Z","links":{"resolver":"https://pith.science/pith/TLPCO3QQRNNSF6TMTJL7WZFUPO","bundle":"https://pith.science/pith/TLPCO3QQRNNSF6TMTJL7WZFUPO/bundle.json","state":"https://pith.science/pith/TLPCO3QQRNNSF6TMTJL7WZFUPO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TLPCO3QQRNNSF6TMTJL7WZFUPO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TLPCO3QQRNNSF6TMTJL7WZFUPO","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":"c51bdeb8ee03f579b587d46af160212808f882514d178fb73be2e539e22382a2","cross_cats_sorted":["cs.AI","cs.CL","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-08T18:59:48Z","title_canon_sha256":"8df2dd1f48d18b1b322c199ebd5af8ce4a845e61977f97c7c2850e12366c621c"},"schema_version":"1.0","source":{"id":"2402.05935","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.05935","created_at":"2026-07-05T10:36:23Z"},{"alias_kind":"arxiv_version","alias_value":"2402.05935v3","created_at":"2026-07-05T10:36:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.05935","created_at":"2026-07-05T10:36:23Z"},{"alias_kind":"pith_short_12","alias_value":"TLPCO3QQRNNS","created_at":"2026-07-05T10:36:23Z"},{"alias_kind":"pith_short_16","alias_value":"TLPCO3QQRNNSF6TM","created_at":"2026-07-05T10:36:23Z"},{"alias_kind":"pith_short_8","alias_value":"TLPCO3QQ","created_at":"2026-07-05T10:36:23Z"}],"graph_snapshots":[{"event_id":"sha256:e5941b37b782589052b62cdeb528e2e2773c46f194d4e90a08c896766f6530f1","target":"graph","created_at":"2026-07-05T10:36:23Z","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/2402.05935/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose SPHINX-X, an extensive Multimodality Large Language Model (MLLM) series developed upon SPHINX. To improve the architecture and training efficiency, we modify the SPHINX framework by removing redundant visual encoders, bypassing fully-padded sub-images with skip tokens, and simplifying multi-stage training into a one-stage all-in-one paradigm. To fully unleash the potential of MLLMs, we assemble a comprehensive multi-domain and multimodal dataset covering publicly available resources in language, vision, and vision-language tasks. We further enrich this collection with our curated OC","authors_text":"Chao Xu, Conghui He, Dongyang Liu, Hao Shao, Hongsheng Li, Junjun He, Kaipeng Zhang, Longtian Qiu, Pan Lu, Peng Gao, Peng Jin, Renrui Zhang, Shijie Geng, Shitian Zhao, Siyuan Huang, Weifeng Lin, Wenqi Shao, Yu Qiao, Ziyi Lin","cross_cats":["cs.AI","cs.CL","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-08T18:59:48Z","title":"SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.05935","kind":"arxiv","version":3},"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:f4577d855e977eab95b8a9735216ef68e354365bb4af8a4e488d087024cfea79","target":"record","created_at":"2026-07-05T10:36:23Z","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":"c51bdeb8ee03f579b587d46af160212808f882514d178fb73be2e539e22382a2","cross_cats_sorted":["cs.AI","cs.CL","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-02-08T18:59:48Z","title_canon_sha256":"8df2dd1f48d18b1b322c199ebd5af8ce4a845e61977f97c7c2850e12366c621c"},"schema_version":"1.0","source":{"id":"2402.05935","kind":"arxiv","version":3}},"canonical_sha256":"9ade276e108b5b22fa6c9a57fb64b47b8bb42ff19d360f8f2c0e13d150afb16f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9ade276e108b5b22fa6c9a57fb64b47b8bb42ff19d360f8f2c0e13d150afb16f","first_computed_at":"2026-07-05T10:36:23.866576Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:36:23.866576Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZW3G1Js0JKjYeWZZjoBQeU5fWbKjS2zVoUNrpK9tLcXW+stx+VuNQdkKJon19BbuaWLpZBNs2ouqZc5PattwDg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:36:23.867581Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.05935","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f4577d855e977eab95b8a9735216ef68e354365bb4af8a4e488d087024cfea79","sha256:e5941b37b782589052b62cdeb528e2e2773c46f194d4e90a08c896766f6530f1"],"state_sha256":"a2fa6c94fe9ded1ac67fae6dd39bcfcf11ca3ef3636b395317e5224345291eb3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bYSLz8LqZObKnAV9sy4j4Nujr+vUUkD76/+z6KC5Od4iEdSiUrFNb6z2GZ4/2M45w7iLTJRuIQEyqHaQf55cAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T02:40:22.795996Z","bundle_sha256":"99cd84af5dd60b4900fb5fdc182148cb5cb59e331afd04532d267ca81c0c38b4"}}