{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:MWJEYFE67RDHXNFOSFIZXIYJ2W","short_pith_number":"pith:MWJEYFE6","canonical_record":{"source":{"id":"2605.30248","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-28T17:13:18Z","cross_cats_sorted":[],"title_canon_sha256":"d553243a9636b7cf27bfee3ab0eb4c29b2e7e57ea6658737282e631f527847f4","abstract_canon_sha256":"cc372d7f0f603e98e082ea96fe7d03d6edff18855c370743cd6b87597e5e84c7"},"schema_version":"1.0"},"canonical_sha256":"65924c149efc467bb4ae91519ba309d5b77b490483b5018a19feb2eb24b3571d","source":{"kind":"arxiv","id":"2605.30248","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30248","created_at":"2026-05-29T02:06:13Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30248v1","created_at":"2026-05-29T02:06:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30248","created_at":"2026-05-29T02:06:13Z"},{"alias_kind":"pith_short_12","alias_value":"MWJEYFE67RDH","created_at":"2026-05-29T02:06:13Z"},{"alias_kind":"pith_short_16","alias_value":"MWJEYFE67RDHXNFO","created_at":"2026-05-29T02:06:13Z"},{"alias_kind":"pith_short_8","alias_value":"MWJEYFE6","created_at":"2026-05-29T02:06:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:MWJEYFE67RDHXNFOSFIZXIYJ2W","target":"record","payload":{"canonical_record":{"source":{"id":"2605.30248","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-28T17:13:18Z","cross_cats_sorted":[],"title_canon_sha256":"d553243a9636b7cf27bfee3ab0eb4c29b2e7e57ea6658737282e631f527847f4","abstract_canon_sha256":"cc372d7f0f603e98e082ea96fe7d03d6edff18855c370743cd6b87597e5e84c7"},"schema_version":"1.0"},"canonical_sha256":"65924c149efc467bb4ae91519ba309d5b77b490483b5018a19feb2eb24b3571d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T02:06:13.938497Z","signature_b64":"Jb8ObMXPWeZ/hEhSrYRDE9Inm6k2zMKlK40/gYGmw9i+QJXVZRnxEHmXTZQSQHtFpLc9eQ2g7KaVkVDwkm79Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"65924c149efc467bb4ae91519ba309d5b77b490483b5018a19feb2eb24b3571d","last_reissued_at":"2026-05-29T02:06:13.938066Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T02:06:13.938066Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.30248","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-29T02:06:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/GKsJVUmsecRdxpKjFGfZDY2KIQDFC/076ri/bdzv5kOwV1um0spd2peGUV8xuDhnS5N/46FBkyZbyKQN8lfAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T05:19:47.057555Z"},"content_sha256":"4712dc8daea78c01430033fff37ba34761967199b9f55829f720d1106b535237","schema_version":"1.0","event_id":"sha256:4712dc8daea78c01430033fff37ba34761967199b9f55829f720d1106b535237"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:MWJEYFE67RDHXNFOSFIZXIYJ2W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GenClaw: Code-Driven Agentic Image Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dongzhi Jiang, Jun He, Junyan Ye, Rui Chen, Weijia Li, Xuan Yang, Zilong Huang","submitted_at":"2026-05-28T17:13:18Z","abstract_excerpt":"Image generation models have evolved from text-conditioned pixel synthesis toward multimodal agents endowed with visual comprehension and tool invocation capabilities. Yet, existing agents remain at the mercy of underlying black-box image models. Their workflow is trapped in a repetitive cycle of prompt rewriting for generation refinement, leaving them with no mechanism to directly manipulate the canvas. In essence, the potential of LLMs to serve as a genuine \"brush\" for precise visual construction remains largely untapped. In this paper, we propose GenClaw, a code-driven agentic image generat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30248","kind":"arxiv","version":1},"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/2605.30248/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":"2026-05-29T02:06:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kCbNpFJdVQFc9eJUoppNrdkOAg8WzjJ75iFENAUfbg6a+XW6MTlYOz1so82YAYYEl4CFqyvX5PnpAB7Ze//lBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T05:19:47.058250Z"},"content_sha256":"c2faf588874cef1996a44c62d427c2618d332184bdc473b0d3dd912ac6d8e6cd","schema_version":"1.0","event_id":"sha256:c2faf588874cef1996a44c62d427c2618d332184bdc473b0d3dd912ac6d8e6cd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MWJEYFE67RDHXNFOSFIZXIYJ2W/bundle.json","state_url":"https://pith.science/pith/MWJEYFE67RDHXNFOSFIZXIYJ2W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MWJEYFE67RDHXNFOSFIZXIYJ2W/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":"2026-05-30T05:19:47Z","links":{"resolver":"https://pith.science/pith/MWJEYFE67RDHXNFOSFIZXIYJ2W","bundle":"https://pith.science/pith/MWJEYFE67RDHXNFOSFIZXIYJ2W/bundle.json","state":"https://pith.science/pith/MWJEYFE67RDHXNFOSFIZXIYJ2W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MWJEYFE67RDHXNFOSFIZXIYJ2W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:MWJEYFE67RDHXNFOSFIZXIYJ2W","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":"cc372d7f0f603e98e082ea96fe7d03d6edff18855c370743cd6b87597e5e84c7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-28T17:13:18Z","title_canon_sha256":"d553243a9636b7cf27bfee3ab0eb4c29b2e7e57ea6658737282e631f527847f4"},"schema_version":"1.0","source":{"id":"2605.30248","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30248","created_at":"2026-05-29T02:06:13Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30248v1","created_at":"2026-05-29T02:06:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30248","created_at":"2026-05-29T02:06:13Z"},{"alias_kind":"pith_short_12","alias_value":"MWJEYFE67RDH","created_at":"2026-05-29T02:06:13Z"},{"alias_kind":"pith_short_16","alias_value":"MWJEYFE67RDHXNFO","created_at":"2026-05-29T02:06:13Z"},{"alias_kind":"pith_short_8","alias_value":"MWJEYFE6","created_at":"2026-05-29T02:06:13Z"}],"graph_snapshots":[{"event_id":"sha256:c2faf588874cef1996a44c62d427c2618d332184bdc473b0d3dd912ac6d8e6cd","target":"graph","created_at":"2026-05-29T02:06:13Z","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/2605.30248/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Image generation models have evolved from text-conditioned pixel synthesis toward multimodal agents endowed with visual comprehension and tool invocation capabilities. Yet, existing agents remain at the mercy of underlying black-box image models. Their workflow is trapped in a repetitive cycle of prompt rewriting for generation refinement, leaving them with no mechanism to directly manipulate the canvas. In essence, the potential of LLMs to serve as a genuine \"brush\" for precise visual construction remains largely untapped. In this paper, we propose GenClaw, a code-driven agentic image generat","authors_text":"Dongzhi Jiang, Jun He, Junyan Ye, Rui Chen, Weijia Li, Xuan Yang, Zilong Huang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-28T17:13:18Z","title":"GenClaw: Code-Driven Agentic Image Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30248","kind":"arxiv","version":1},"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":"sha256:4712dc8daea78c01430033fff37ba34761967199b9f55829f720d1106b535237","target":"record","created_at":"2026-05-29T02:06:13Z","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":"cc372d7f0f603e98e082ea96fe7d03d6edff18855c370743cd6b87597e5e84c7","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-28T17:13:18Z","title_canon_sha256":"d553243a9636b7cf27bfee3ab0eb4c29b2e7e57ea6658737282e631f527847f4"},"schema_version":"1.0","source":{"id":"2605.30248","kind":"arxiv","version":1}},"canonical_sha256":"65924c149efc467bb4ae91519ba309d5b77b490483b5018a19feb2eb24b3571d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"65924c149efc467bb4ae91519ba309d5b77b490483b5018a19feb2eb24b3571d","first_computed_at":"2026-05-29T02:06:13.938066Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T02:06:13.938066Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Jb8ObMXPWeZ/hEhSrYRDE9Inm6k2zMKlK40/gYGmw9i+QJXVZRnxEHmXTZQSQHtFpLc9eQ2g7KaVkVDwkm79Aw==","signature_status":"signed_v1","signed_at":"2026-05-29T02:06:13.938497Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.30248","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4712dc8daea78c01430033fff37ba34761967199b9f55829f720d1106b535237","sha256:c2faf588874cef1996a44c62d427c2618d332184bdc473b0d3dd912ac6d8e6cd"],"state_sha256":"9a61a7c4b71994e4b5b06264c73325bdb2d3df359d6f2cef0b94fc87d4166b2a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g4ZmgoEDrBUOQS1MQf3xHD6Vu6U/ye8LMlM3kQgvsi+baN9j1Uqhd/WVbMCqIp/lUI6TR5higp3hG+2mHz61Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T05:19:47.061203Z","bundle_sha256":"1a73bec72a3c0467e31f28e3c8cf072a48caf70418d64e05950a4bce21e0d598"}}