{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:CMEADQ2K3AXD6NUKMVVWGNZK3A","short_pith_number":"pith:CMEADQ2K","canonical_record":{"source":{"id":"1803.10892","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-29T01:24:02Z","cross_cats_sorted":[],"title_canon_sha256":"02e24165d4c263523bd6eedacd14b6c00a90433ea995860dc919a9103fc5a1f2","abstract_canon_sha256":"b538ec036a351b628aa0cab3c099dcde9f13ded816e8a23481be9d61783bb442"},"schema_version":"1.0"},"canonical_sha256":"130801c34ad82e3f368a656b63372ad83ec9df75b0d0160c40c18110a53b1024","source":{"kind":"arxiv","id":"1803.10892","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.10892","created_at":"2026-05-18T00:19:49Z"},{"alias_kind":"arxiv_version","alias_value":"1803.10892v1","created_at":"2026-05-18T00:19:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.10892","created_at":"2026-05-18T00:19:49Z"},{"alias_kind":"pith_short_12","alias_value":"CMEADQ2K3AXD","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"CMEADQ2K3AXD6NUK","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"CMEADQ2K","created_at":"2026-05-18T12:32:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:CMEADQ2K3AXD6NUKMVVWGNZK3A","target":"record","payload":{"canonical_record":{"source":{"id":"1803.10892","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-29T01:24:02Z","cross_cats_sorted":[],"title_canon_sha256":"02e24165d4c263523bd6eedacd14b6c00a90433ea995860dc919a9103fc5a1f2","abstract_canon_sha256":"b538ec036a351b628aa0cab3c099dcde9f13ded816e8a23481be9d61783bb442"},"schema_version":"1.0"},"canonical_sha256":"130801c34ad82e3f368a656b63372ad83ec9df75b0d0160c40c18110a53b1024","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:19:49.870454Z","signature_b64":"ufVTIRf4bVY11osMUcT+AszaeoJRfKjL8uAsB1yPBLQnDCG9uNusojYujhj3RAPDy9h0fNpEcnSe96Uum7L6Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"130801c34ad82e3f368a656b63372ad83ec9df75b0d0160c40c18110a53b1024","last_reissued_at":"2026-05-18T00:19:49.869781Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:19:49.869781Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1803.10892","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":"2026-05-18T00:19:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XGRGOwiznROgCT3xQVU/iyCbEx1FLOL8RKDPKSCVW+mPnoIKH3FgJeM1ydzrpBRd1TxwhHVmPwws6VKKR63rAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-18T19:46:31.752311Z"},"content_sha256":"d40151920b1bc8375d2c8e5c3fa5388ff0c35a66da9d876bbd66e607d83d00e7","schema_version":"1.0","event_id":"sha256:d40151920b1bc8375d2c8e5c3fa5388ff0c35a66da9d876bbd66e607d83d00e7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:CMEADQ2K3AXD6NUKMVVWGNZK3A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Agrim Gupta, Alexandre Alahi, Justin Johnson, Li Fei-Fei, Silvio Savarese","submitted_at":"2018-03-29T01:24:02Z","abstract_excerpt":"Understanding human motion behavior is critical for autonomous moving platforms (like self-driving cars and social robots) if they are to navigate human-centric environments. This is challenging because human motion is inherently multimodal: given a history of human motion paths, there are many socially plausible ways that people could move in the future. We tackle this problem by combining tools from sequence prediction and generative adversarial networks: a recurrent sequence-to-sequence model observes motion histories and predicts future behavior, using a novel pooling mechanism to aggregat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.10892","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":"2026-05-18T00:19:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XbgvaSriB7cJayukb/SBljrjSfaQD6QZM66QZEBaM0RW6ySMWUuCljss0F3wwpPuXkHp67ZjXfmJqAyZOuVxDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-18T19:46:31.753014Z"},"content_sha256":"84d99274c61b12c41a10d514ba94e14cd9f3af4b8d5f32a85895c9744878abec","schema_version":"1.0","event_id":"sha256:84d99274c61b12c41a10d514ba94e14cd9f3af4b8d5f32a85895c9744878abec"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CMEADQ2K3AXD6NUKMVVWGNZK3A/bundle.json","state_url":"https://pith.science/pith/CMEADQ2K3AXD6NUKMVVWGNZK3A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CMEADQ2K3AXD6NUKMVVWGNZK3A/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":"2026-05-18T19:46:31Z","links":{"resolver":"https://pith.science/pith/CMEADQ2K3AXD6NUKMVVWGNZK3A","bundle":"https://pith.science/pith/CMEADQ2K3AXD6NUKMVVWGNZK3A/bundle.json","state":"https://pith.science/pith/CMEADQ2K3AXD6NUKMVVWGNZK3A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CMEADQ2K3AXD6NUKMVVWGNZK3A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:CMEADQ2K3AXD6NUKMVVWGNZK3A","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":"b538ec036a351b628aa0cab3c099dcde9f13ded816e8a23481be9d61783bb442","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-29T01:24:02Z","title_canon_sha256":"02e24165d4c263523bd6eedacd14b6c00a90433ea995860dc919a9103fc5a1f2"},"schema_version":"1.0","source":{"id":"1803.10892","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.10892","created_at":"2026-05-18T00:19:49Z"},{"alias_kind":"arxiv_version","alias_value":"1803.10892v1","created_at":"2026-05-18T00:19:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.10892","created_at":"2026-05-18T00:19:49Z"},{"alias_kind":"pith_short_12","alias_value":"CMEADQ2K3AXD","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_16","alias_value":"CMEADQ2K3AXD6NUK","created_at":"2026-05-18T12:32:16Z"},{"alias_kind":"pith_short_8","alias_value":"CMEADQ2K","created_at":"2026-05-18T12:32:16Z"}],"graph_snapshots":[{"event_id":"sha256:84d99274c61b12c41a10d514ba94e14cd9f3af4b8d5f32a85895c9744878abec","target":"graph","created_at":"2026-05-18T00:19:49Z","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":"Understanding human motion behavior is critical for autonomous moving platforms (like self-driving cars and social robots) if they are to navigate human-centric environments. This is challenging because human motion is inherently multimodal: given a history of human motion paths, there are many socially plausible ways that people could move in the future. We tackle this problem by combining tools from sequence prediction and generative adversarial networks: a recurrent sequence-to-sequence model observes motion histories and predicts future behavior, using a novel pooling mechanism to aggregat","authors_text":"Agrim Gupta, Alexandre Alahi, Justin Johnson, Li Fei-Fei, Silvio Savarese","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-29T01:24:02Z","title":"Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.10892","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:d40151920b1bc8375d2c8e5c3fa5388ff0c35a66da9d876bbd66e607d83d00e7","target":"record","created_at":"2026-05-18T00:19:49Z","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":"b538ec036a351b628aa0cab3c099dcde9f13ded816e8a23481be9d61783bb442","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-29T01:24:02Z","title_canon_sha256":"02e24165d4c263523bd6eedacd14b6c00a90433ea995860dc919a9103fc5a1f2"},"schema_version":"1.0","source":{"id":"1803.10892","kind":"arxiv","version":1}},"canonical_sha256":"130801c34ad82e3f368a656b63372ad83ec9df75b0d0160c40c18110a53b1024","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"130801c34ad82e3f368a656b63372ad83ec9df75b0d0160c40c18110a53b1024","first_computed_at":"2026-05-18T00:19:49.869781Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:19:49.869781Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ufVTIRf4bVY11osMUcT+AszaeoJRfKjL8uAsB1yPBLQnDCG9uNusojYujhj3RAPDy9h0fNpEcnSe96Uum7L6Bg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:19:49.870454Z","signed_message":"canonical_sha256_bytes"},"source_id":"1803.10892","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d40151920b1bc8375d2c8e5c3fa5388ff0c35a66da9d876bbd66e607d83d00e7","sha256:84d99274c61b12c41a10d514ba94e14cd9f3af4b8d5f32a85895c9744878abec"],"state_sha256":"a8286b9a516e46f19db28891ff671038cf9382bfcbbbb21fbd71742a20ec6cee"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CSaSPzh+vplJD0bb2wu+B5io8xrfOkL0qthCZNqLtJWIwFUQj2r2Bg2pPbWultQJbw3WNzHwvIEIAYtk14B9Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-18T19:46:31.755204Z","bundle_sha256":"1d3bfff0e6beed1124436958f3d127581e84bc82f04d94e2352c9281801027f2"}}