{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:WGSVZPA3XB6XKWSZJFALAJEKHQ","short_pith_number":"pith:WGSVZPA3","canonical_record":{"source":{"id":"2311.16511","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-25T04:05:59Z","cross_cats_sorted":[],"title_canon_sha256":"012c0a9ad55f55740e8d3a9c904a7e6e566f292098561ea1b02e10950ec85926","abstract_canon_sha256":"81469230dfe086e90711b24641ff46875b954313eca4b64856a4979963ea096e"},"schema_version":"1.0"},"canonical_sha256":"b1a55cbc1bb87d755a594940b0248a3c2b72584c50ac8edd0859b8cf16821e14","source":{"kind":"arxiv","id":"2311.16511","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.16511","created_at":"2026-07-05T09:26:22Z"},{"alias_kind":"arxiv_version","alias_value":"2311.16511v2","created_at":"2026-07-05T09:26:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.16511","created_at":"2026-07-05T09:26:22Z"},{"alias_kind":"pith_short_12","alias_value":"WGSVZPA3XB6X","created_at":"2026-07-05T09:26:22Z"},{"alias_kind":"pith_short_16","alias_value":"WGSVZPA3XB6XKWSZ","created_at":"2026-07-05T09:26:22Z"},{"alias_kind":"pith_short_8","alias_value":"WGSVZPA3","created_at":"2026-07-05T09:26:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:WGSVZPA3XB6XKWSZJFALAJEKHQ","target":"record","payload":{"canonical_record":{"source":{"id":"2311.16511","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-25T04:05:59Z","cross_cats_sorted":[],"title_canon_sha256":"012c0a9ad55f55740e8d3a9c904a7e6e566f292098561ea1b02e10950ec85926","abstract_canon_sha256":"81469230dfe086e90711b24641ff46875b954313eca4b64856a4979963ea096e"},"schema_version":"1.0"},"canonical_sha256":"b1a55cbc1bb87d755a594940b0248a3c2b72584c50ac8edd0859b8cf16821e14","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:26:22.959554Z","signature_b64":"Sj1ucyDoLAX0TX5Cul59jj1RV1xcHlng5ZMXWWOQUQUmVhAhBsbhBIARZAYCGLzEvGxo/hb8cD8oTrk12yI6Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b1a55cbc1bb87d755a594940b0248a3c2b72584c50ac8edd0859b8cf16821e14","last_reissued_at":"2026-07-05T09:26:22.959029Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:26:22.959029Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.16511","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":"2026-07-05T09:26:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/vlT+Z4dQ24yVjizPCfQHPYzIlFVW/0e11cBL7E2YoEcAyTHpdJVEo3FbJGR4447LGuzTOomc0XMyiYVAVn4BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T03:03:08.055360Z"},"content_sha256":"e90a04a15007cef3a8f5d3103a56c1daa557db0d362698e940d453d090dbe6ce","schema_version":"1.0","event_id":"sha256:e90a04a15007cef3a8f5d3103a56c1daa557db0d362698e940d453d090dbe6ce"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:WGSVZPA3XB6XKWSZJFALAJEKHQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GPT4Video: A Unified Multimodal Large Language Model for lnstruction-Followed Understanding and Safety-Aware Generation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chenyang Lyu, Deng Cai, Huayang Li, Longyue Wang, Luping Zhou, Minghao Wu, Shuming Shi, Zhanyu Wang, Zhaopeng Tu, Zhen Zhao","submitted_at":"2023-11-25T04:05:59Z","abstract_excerpt":"While the recent advances in Multimodal Large Language Models (MLLMs) constitute a significant leap forward in the field, these models are predominantly confined to the realm of input-side multimodal comprehension, lacking the capacity for multimodal content generation. To fill this gap, we present GPT4Video, a unified multi-model framework that empowers Large Language Models (LLMs) with the capability of both video understanding and generation. Specifically, we develop an instruction-following-based approach integrated with the stable diffusion generative model, which has demonstrated to effe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.16511","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/2311.16511/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":"2026-07-05T09:26:22Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EWwvy5rHSAysuYDp7/Vg+jxxaY2V1J2aFvir3I+P34VXXBiadq43vnIdGXXL1hZjcxyjJDqvW9ElJM5fPyDVAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T03:03:08.056243Z"},"content_sha256":"387ab371e4b6390b0fca5486ce39528425177814c83ecca8ee9c321b89c78f15","schema_version":"1.0","event_id":"sha256:387ab371e4b6390b0fca5486ce39528425177814c83ecca8ee9c321b89c78f15"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WGSVZPA3XB6XKWSZJFALAJEKHQ/bundle.json","state_url":"https://pith.science/pith/WGSVZPA3XB6XKWSZJFALAJEKHQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WGSVZPA3XB6XKWSZJFALAJEKHQ/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":"2026-08-09T03:03:08Z","links":{"resolver":"https://pith.science/pith/WGSVZPA3XB6XKWSZJFALAJEKHQ","bundle":"https://pith.science/pith/WGSVZPA3XB6XKWSZJFALAJEKHQ/bundle.json","state":"https://pith.science/pith/WGSVZPA3XB6XKWSZJFALAJEKHQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WGSVZPA3XB6XKWSZJFALAJEKHQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:WGSVZPA3XB6XKWSZJFALAJEKHQ","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":"81469230dfe086e90711b24641ff46875b954313eca4b64856a4979963ea096e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-25T04:05:59Z","title_canon_sha256":"012c0a9ad55f55740e8d3a9c904a7e6e566f292098561ea1b02e10950ec85926"},"schema_version":"1.0","source":{"id":"2311.16511","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.16511","created_at":"2026-07-05T09:26:22Z"},{"alias_kind":"arxiv_version","alias_value":"2311.16511v2","created_at":"2026-07-05T09:26:22Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.16511","created_at":"2026-07-05T09:26:22Z"},{"alias_kind":"pith_short_12","alias_value":"WGSVZPA3XB6X","created_at":"2026-07-05T09:26:22Z"},{"alias_kind":"pith_short_16","alias_value":"WGSVZPA3XB6XKWSZ","created_at":"2026-07-05T09:26:22Z"},{"alias_kind":"pith_short_8","alias_value":"WGSVZPA3","created_at":"2026-07-05T09:26:22Z"}],"graph_snapshots":[{"event_id":"sha256:387ab371e4b6390b0fca5486ce39528425177814c83ecca8ee9c321b89c78f15","target":"graph","created_at":"2026-07-05T09:26:22Z","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/2311.16511/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"While the recent advances in Multimodal Large Language Models (MLLMs) constitute a significant leap forward in the field, these models are predominantly confined to the realm of input-side multimodal comprehension, lacking the capacity for multimodal content generation. To fill this gap, we present GPT4Video, a unified multi-model framework that empowers Large Language Models (LLMs) with the capability of both video understanding and generation. Specifically, we develop an instruction-following-based approach integrated with the stable diffusion generative model, which has demonstrated to effe","authors_text":"Chenyang Lyu, Deng Cai, Huayang Li, Longyue Wang, Luping Zhou, Minghao Wu, Shuming Shi, Zhanyu Wang, Zhaopeng Tu, Zhen Zhao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-25T04:05:59Z","title":"GPT4Video: A Unified Multimodal Large Language Model for lnstruction-Followed Understanding and Safety-Aware Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.16511","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:e90a04a15007cef3a8f5d3103a56c1daa557db0d362698e940d453d090dbe6ce","target":"record","created_at":"2026-07-05T09:26:22Z","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":"81469230dfe086e90711b24641ff46875b954313eca4b64856a4979963ea096e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-25T04:05:59Z","title_canon_sha256":"012c0a9ad55f55740e8d3a9c904a7e6e566f292098561ea1b02e10950ec85926"},"schema_version":"1.0","source":{"id":"2311.16511","kind":"arxiv","version":2}},"canonical_sha256":"b1a55cbc1bb87d755a594940b0248a3c2b72584c50ac8edd0859b8cf16821e14","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b1a55cbc1bb87d755a594940b0248a3c2b72584c50ac8edd0859b8cf16821e14","first_computed_at":"2026-07-05T09:26:22.959029Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:26:22.959029Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Sj1ucyDoLAX0TX5Cul59jj1RV1xcHlng5ZMXWWOQUQUmVhAhBsbhBIARZAYCGLzEvGxo/hb8cD8oTrk12yI6Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T09:26:22.959554Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.16511","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e90a04a15007cef3a8f5d3103a56c1daa557db0d362698e940d453d090dbe6ce","sha256:387ab371e4b6390b0fca5486ce39528425177814c83ecca8ee9c321b89c78f15"],"state_sha256":"9090dddfba69e5c38371b74fe36bb892096fe2e5e7ebb6bf605e6e82388ace3b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oQuSfxCT8bSdVhKpGHxvqOiZfbMfhmU8rXo7Bi6US46K5cWL6GCkrldorURViW65r+nSe4Qi+2ydf+SbBacfDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T03:03:08.061148Z","bundle_sha256":"95caac3460f699a431b2b4d599e8c45ea841062dd74f70dff9b2b52b4fadfdd0"}}