{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:RLDG62C5NRGN7MIX5G7AI2DRDV","short_pith_number":"pith:RLDG62C5","canonical_record":{"source":{"id":"2305.06152","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-06T03:57:05Z","cross_cats_sorted":["cs.AI","cs.MM"],"title_canon_sha256":"c8c91c61a6cc8122a4406df18df94702149a4535becec61d4083d1754f935ffa","abstract_canon_sha256":"5fe469afb3b83fcaa7f51f981181050ddb64ab435c9090157f91f0a4e0aa77a4"},"schema_version":"1.0"},"canonical_sha256":"8ac66f685d6c4cdfb117e9be0468711d43652b995ccea8dec2906e58a9192e8a","source":{"kind":"arxiv","id":"2305.06152","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.06152","created_at":"2026-07-05T07:23:25Z"},{"alias_kind":"arxiv_version","alias_value":"2305.06152v3","created_at":"2026-07-05T07:23:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.06152","created_at":"2026-07-05T07:23:25Z"},{"alias_kind":"pith_short_12","alias_value":"RLDG62C5NRGN","created_at":"2026-07-05T07:23:25Z"},{"alias_kind":"pith_short_16","alias_value":"RLDG62C5NRGN7MIX","created_at":"2026-07-05T07:23:25Z"},{"alias_kind":"pith_short_8","alias_value":"RLDG62C5","created_at":"2026-07-05T07:23:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:RLDG62C5NRGN7MIX5G7AI2DRDV","target":"record","payload":{"canonical_record":{"source":{"id":"2305.06152","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-06T03:57:05Z","cross_cats_sorted":["cs.AI","cs.MM"],"title_canon_sha256":"c8c91c61a6cc8122a4406df18df94702149a4535becec61d4083d1754f935ffa","abstract_canon_sha256":"5fe469afb3b83fcaa7f51f981181050ddb64ab435c9090157f91f0a4e0aa77a4"},"schema_version":"1.0"},"canonical_sha256":"8ac66f685d6c4cdfb117e9be0468711d43652b995ccea8dec2906e58a9192e8a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:23:25.768543Z","signature_b64":"zsXoLCjAihAell6YE2g5dPdsewFiBq3tlMDh7OnyhAWNkgrjscro6bAa6UdRrE1xGRTbwsoJPppoBfPq28AmAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8ac66f685d6c4cdfb117e9be0468711d43652b995ccea8dec2906e58a9192e8a","last_reissued_at":"2026-07-05T07:23:25.768069Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:23:25.768069Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.06152","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":"2026-07-05T07:23:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dXiJmRWClPVHK0RfiNjfoaM6e7nqNoVdWr+lDznI5SEFOVNRRt8akcjyXh4OD2FY60ElBjetdgOf4cbN+B9aAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T09:29:52.208796Z"},"content_sha256":"b15d42365aafc74e12e047e2764569432f64f1e800cc0d2eb49bd9ea1fcffb96","schema_version":"1.0","event_id":"sha256:b15d42365aafc74e12e047e2764569432f64f1e800cc0d2eb49bd9ea1fcffb96"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:RLDG62C5NRGN7MIX5G7AI2DRDV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Structure-CLIP: Towards Scene Graph Knowledge to Enhance Multi-modal Structured Representations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.MM"],"primary_cat":"cs.CL","authors_text":"Jiji Tang, Rongsheng Zhang, Tangjie Lv, Weijie Chen, Wen Zhang, Xinfeng Zhang, Yufeng Huang, Zeng Zhao, Zhipeng Hu, Zhou Zhao, Zhuo Chen","submitted_at":"2023-05-06T03:57:05Z","abstract_excerpt":"Large-scale vision-language pre-training has achieved significant performance in multi-modal understanding and generation tasks. However, existing methods often perform poorly on image-text matching tasks that require structured representations, i.e., representations of objects, attributes, and relations. As illustrated in Fig.~reffig:case (a), the models cannot make a distinction between ``An astronaut rides a horse\" and ``A horse rides an astronaut\". This is because they fail to fully leverage structured knowledge when learning representations in multi-modal scenarios. In this paper, we pres"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.06152","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/2305.06152/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":"2026-07-05T07:23:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UE9oLzQPf18ca4RiUwLHRb1vOcduzUmogoAE9P/wprtFxHl4HG6d/kQgdNUIMNnAgEw3ADWMHycwU9ujShWqDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T09:29:52.209324Z"},"content_sha256":"8449a56674b311afed815ecce82b601ec7d3ff28945862dd9c0ba4e5696dae6e","schema_version":"1.0","event_id":"sha256:8449a56674b311afed815ecce82b601ec7d3ff28945862dd9c0ba4e5696dae6e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RLDG62C5NRGN7MIX5G7AI2DRDV/bundle.json","state_url":"https://pith.science/pith/RLDG62C5NRGN7MIX5G7AI2DRDV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RLDG62C5NRGN7MIX5G7AI2DRDV/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":"2026-08-10T09:29:52Z","links":{"resolver":"https://pith.science/pith/RLDG62C5NRGN7MIX5G7AI2DRDV","bundle":"https://pith.science/pith/RLDG62C5NRGN7MIX5G7AI2DRDV/bundle.json","state":"https://pith.science/pith/RLDG62C5NRGN7MIX5G7AI2DRDV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RLDG62C5NRGN7MIX5G7AI2DRDV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:RLDG62C5NRGN7MIX5G7AI2DRDV","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":"5fe469afb3b83fcaa7f51f981181050ddb64ab435c9090157f91f0a4e0aa77a4","cross_cats_sorted":["cs.AI","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-06T03:57:05Z","title_canon_sha256":"c8c91c61a6cc8122a4406df18df94702149a4535becec61d4083d1754f935ffa"},"schema_version":"1.0","source":{"id":"2305.06152","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.06152","created_at":"2026-07-05T07:23:25Z"},{"alias_kind":"arxiv_version","alias_value":"2305.06152v3","created_at":"2026-07-05T07:23:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.06152","created_at":"2026-07-05T07:23:25Z"},{"alias_kind":"pith_short_12","alias_value":"RLDG62C5NRGN","created_at":"2026-07-05T07:23:25Z"},{"alias_kind":"pith_short_16","alias_value":"RLDG62C5NRGN7MIX","created_at":"2026-07-05T07:23:25Z"},{"alias_kind":"pith_short_8","alias_value":"RLDG62C5","created_at":"2026-07-05T07:23:25Z"}],"graph_snapshots":[{"event_id":"sha256:8449a56674b311afed815ecce82b601ec7d3ff28945862dd9c0ba4e5696dae6e","target":"graph","created_at":"2026-07-05T07:23:25Z","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/2305.06152/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large-scale vision-language pre-training has achieved significant performance in multi-modal understanding and generation tasks. However, existing methods often perform poorly on image-text matching tasks that require structured representations, i.e., representations of objects, attributes, and relations. As illustrated in Fig.~reffig:case (a), the models cannot make a distinction between ``An astronaut rides a horse\" and ``A horse rides an astronaut\". This is because they fail to fully leverage structured knowledge when learning representations in multi-modal scenarios. In this paper, we pres","authors_text":"Jiji Tang, Rongsheng Zhang, Tangjie Lv, Weijie Chen, Wen Zhang, Xinfeng Zhang, Yufeng Huang, Zeng Zhao, Zhipeng Hu, Zhou Zhao, Zhuo Chen","cross_cats":["cs.AI","cs.MM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-06T03:57:05Z","title":"Structure-CLIP: Towards Scene Graph Knowledge to Enhance Multi-modal Structured Representations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.06152","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:b15d42365aafc74e12e047e2764569432f64f1e800cc0d2eb49bd9ea1fcffb96","target":"record","created_at":"2026-07-05T07:23:25Z","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":"5fe469afb3b83fcaa7f51f981181050ddb64ab435c9090157f91f0a4e0aa77a4","cross_cats_sorted":["cs.AI","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-06T03:57:05Z","title_canon_sha256":"c8c91c61a6cc8122a4406df18df94702149a4535becec61d4083d1754f935ffa"},"schema_version":"1.0","source":{"id":"2305.06152","kind":"arxiv","version":3}},"canonical_sha256":"8ac66f685d6c4cdfb117e9be0468711d43652b995ccea8dec2906e58a9192e8a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8ac66f685d6c4cdfb117e9be0468711d43652b995ccea8dec2906e58a9192e8a","first_computed_at":"2026-07-05T07:23:25.768069Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:23:25.768069Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zsXoLCjAihAell6YE2g5dPdsewFiBq3tlMDh7OnyhAWNkgrjscro6bAa6UdRrE1xGRTbwsoJPppoBfPq28AmAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:23:25.768543Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.06152","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b15d42365aafc74e12e047e2764569432f64f1e800cc0d2eb49bd9ea1fcffb96","sha256:8449a56674b311afed815ecce82b601ec7d3ff28945862dd9c0ba4e5696dae6e"],"state_sha256":"8e4b189b9414f524a08fb5712c6122a26e00361f378f25f5a94eea14d255688a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FCqVJlbAH3H8Lkfxlef+5rbm0+WQrNC7MkSSYqJlgQH/LMm4ke+BbOhkXOc//+biXYXzfek/DSL2OLm4S1doBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T09:29:52.218151Z","bundle_sha256":"e373ee35baf0ded9a0cf0c620191e2014e42aee5b6d70e0fd6a43470d3a4d3cf"}}