{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:HLC7RF3N3CHJGJDTZZ3WF7SXEE","short_pith_number":"pith:HLC7RF3N","canonical_record":{"source":{"id":"1907.03953","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2019-07-09T03:13:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0e9c606e1cbcebd4aa89ca5dabdef3aa7c917494de46cbcc117d770aea109454","abstract_canon_sha256":"2a5a4fa056746748c736b745a6f4b609adadad4484274adcf85b1f6917873b81"},"schema_version":"1.0"},"canonical_sha256":"3ac5f8976dd88e932473ce7762fe572100b2170cf036411de0e333edec8bb8ba","source":{"kind":"arxiv","id":"1907.03953","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.03953","created_at":"2026-05-17T23:41:06Z"},{"alias_kind":"arxiv_version","alias_value":"1907.03953v1","created_at":"2026-05-17T23:41:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.03953","created_at":"2026-05-17T23:41:06Z"},{"alias_kind":"pith_short_12","alias_value":"HLC7RF3N3CHJ","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"HLC7RF3N3CHJGJDT","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"HLC7RF3N","created_at":"2026-05-18T12:33:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:HLC7RF3N3CHJGJDTZZ3WF7SXEE","target":"record","payload":{"canonical_record":{"source":{"id":"1907.03953","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2019-07-09T03:13:58Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"0e9c606e1cbcebd4aa89ca5dabdef3aa7c917494de46cbcc117d770aea109454","abstract_canon_sha256":"2a5a4fa056746748c736b745a6f4b609adadad4484274adcf85b1f6917873b81"},"schema_version":"1.0"},"canonical_sha256":"3ac5f8976dd88e932473ce7762fe572100b2170cf036411de0e333edec8bb8ba","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:41:06.262937Z","signature_b64":"A1jrnOpfZnyg4PYDseaJIQDjUhAvBJQ4Vu/rVuy+DtP+ExNNvuyGhDGBBpkRFV1KpLnAaG0VSWnogFV+SJ8BDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3ac5f8976dd88e932473ce7762fe572100b2170cf036411de0e333edec8bb8ba","last_reissued_at":"2026-05-17T23:41:06.262364Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:41:06.262364Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.03953","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":"2026-05-17T23:41:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"B1KHDvGGpLXyZbx/9b10ESM4ovrq8KGhCdfxrtwHJKRpVmi1Pn2XDOEw2x1dEWowwJ+umrQtnucquqFg/itdBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T14:49:02.736702Z"},"content_sha256":"58fde3847c8f2c4560b2de7ba961db96930e5c607db5bd557db45948b3ba683e","schema_version":"1.0","event_id":"sha256:58fde3847c8f2c4560b2de7ba961db96930e5c607db5bd557db45948b3ba683e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:HLC7RF3N3CHJGJDTZZ3WF7SXEE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient Cloth Simulation using Miniature Cloth and Upscaling Deep Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.GR","authors_text":"In-Kwon Lee, Tae Min Lee, Young Jin Oh","submitted_at":"2019-07-09T03:13:58Z","abstract_excerpt":"Cloth simulation requires a fast and stable method for interactively and realistically visualizing fabric materials using computer graphics. We propose an efficient cloth simulation method using miniature cloth simulation and upscaling Deep Neural Networks (DNN). The upscaling DNNs generate the target cloth simulation from the results of physically-based simulations of a miniature cloth that has similar physical properties to those of the target cloth. We have verified the utility of the proposed method through experiments, and the results demonstrate that it is possible to generate fast and s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.03953","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":""},"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":"2026-05-17T23:41:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zrbmAzQQGlZcKZL+/UO+PAGHPYDUIsktu45qwf8qG2kc4cBB10uZ9DIusuapHss8ElUin9wotjpMhN72+9hEDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T14:49:02.737118Z"},"content_sha256":"d5ef233eb28df6f4a29fad871866f6bf96ae663c43925615896d7452fa2014ea","schema_version":"1.0","event_id":"sha256:d5ef233eb28df6f4a29fad871866f6bf96ae663c43925615896d7452fa2014ea"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HLC7RF3N3CHJGJDTZZ3WF7SXEE/bundle.json","state_url":"https://pith.science/pith/HLC7RF3N3CHJGJDTZZ3WF7SXEE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HLC7RF3N3CHJGJDTZZ3WF7SXEE/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":"2026-05-30T14:49:02Z","links":{"resolver":"https://pith.science/pith/HLC7RF3N3CHJGJDTZZ3WF7SXEE","bundle":"https://pith.science/pith/HLC7RF3N3CHJGJDTZZ3WF7SXEE/bundle.json","state":"https://pith.science/pith/HLC7RF3N3CHJGJDTZZ3WF7SXEE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HLC7RF3N3CHJGJDTZZ3WF7SXEE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:HLC7RF3N3CHJGJDTZZ3WF7SXEE","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":"2a5a4fa056746748c736b745a6f4b609adadad4484274adcf85b1f6917873b81","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2019-07-09T03:13:58Z","title_canon_sha256":"0e9c606e1cbcebd4aa89ca5dabdef3aa7c917494de46cbcc117d770aea109454"},"schema_version":"1.0","source":{"id":"1907.03953","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.03953","created_at":"2026-05-17T23:41:06Z"},{"alias_kind":"arxiv_version","alias_value":"1907.03953v1","created_at":"2026-05-17T23:41:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.03953","created_at":"2026-05-17T23:41:06Z"},{"alias_kind":"pith_short_12","alias_value":"HLC7RF3N3CHJ","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"HLC7RF3N3CHJGJDT","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"HLC7RF3N","created_at":"2026-05-18T12:33:18Z"}],"graph_snapshots":[{"event_id":"sha256:d5ef233eb28df6f4a29fad871866f6bf96ae663c43925615896d7452fa2014ea","target":"graph","created_at":"2026-05-17T23:41:06Z","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"},"paper":{"abstract_excerpt":"Cloth simulation requires a fast and stable method for interactively and realistically visualizing fabric materials using computer graphics. We propose an efficient cloth simulation method using miniature cloth simulation and upscaling Deep Neural Networks (DNN). The upscaling DNNs generate the target cloth simulation from the results of physically-based simulations of a miniature cloth that has similar physical properties to those of the target cloth. We have verified the utility of the proposed method through experiments, and the results demonstrate that it is possible to generate fast and s","authors_text":"In-Kwon Lee, Tae Min Lee, Young Jin Oh","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2019-07-09T03:13:58Z","title":"Efficient Cloth Simulation using Miniature Cloth and Upscaling Deep Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.03953","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":"sha256:58fde3847c8f2c4560b2de7ba961db96930e5c607db5bd557db45948b3ba683e","target":"record","created_at":"2026-05-17T23:41:06Z","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":"2a5a4fa056746748c736b745a6f4b609adadad4484274adcf85b1f6917873b81","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.GR","submitted_at":"2019-07-09T03:13:58Z","title_canon_sha256":"0e9c606e1cbcebd4aa89ca5dabdef3aa7c917494de46cbcc117d770aea109454"},"schema_version":"1.0","source":{"id":"1907.03953","kind":"arxiv","version":1}},"canonical_sha256":"3ac5f8976dd88e932473ce7762fe572100b2170cf036411de0e333edec8bb8ba","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3ac5f8976dd88e932473ce7762fe572100b2170cf036411de0e333edec8bb8ba","first_computed_at":"2026-05-17T23:41:06.262364Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:41:06.262364Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"A1jrnOpfZnyg4PYDseaJIQDjUhAvBJQ4Vu/rVuy+DtP+ExNNvuyGhDGBBpkRFV1KpLnAaG0VSWnogFV+SJ8BDg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:41:06.262937Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.03953","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:58fde3847c8f2c4560b2de7ba961db96930e5c607db5bd557db45948b3ba683e","sha256:d5ef233eb28df6f4a29fad871866f6bf96ae663c43925615896d7452fa2014ea"],"state_sha256":"2f04b3a13bed9ce7ae2bc5c05df84a4dd9dd76afe5630af9790b47202d6234bb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XfZFdCZ38Nxi4Nv8SYoaaDc8E7PYgjl3WbX1KjIHcNMuG6SoEDXwQSKnAD89wEhR3yeLxosQlDaEH3xPddy3BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T14:49:02.739763Z","bundle_sha256":"869975bc089ba76e489a4785baa918b019a38ad642ab00383f1a7678f20962fa"}}