{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:5YDRIB7NZ64WNXJ2HFXB275H5G","short_pith_number":"pith:5YDRIB7N","canonical_record":{"source":{"id":"2409.12471","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-19T05:20:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"9cbf43cf624da457b9cc85d1aef0cefa61aaa6ca9e380bb814bdbe1f56680a32","abstract_canon_sha256":"863d02e8ea8fd4f1ac82745683bcbfbe1443975f8985aab63f3cec56ff21edb1"},"schema_version":"1.0"},"canonical_sha256":"ee071407edcfb966dd3a396e1d7fa7e9ad1d6ffb49cf9b400418a1e3475b4e68","source":{"kind":"arxiv","id":"2409.12471","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.12471","created_at":"2026-07-05T09:08:54Z"},{"alias_kind":"arxiv_version","alias_value":"2409.12471v1","created_at":"2026-07-05T09:08:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.12471","created_at":"2026-07-05T09:08:54Z"},{"alias_kind":"pith_short_12","alias_value":"5YDRIB7NZ64W","created_at":"2026-07-05T09:08:54Z"},{"alias_kind":"pith_short_16","alias_value":"5YDRIB7NZ64WNXJ2","created_at":"2026-07-05T09:08:54Z"},{"alias_kind":"pith_short_8","alias_value":"5YDRIB7N","created_at":"2026-07-05T09:08:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:5YDRIB7NZ64WNXJ2HFXB275H5G","target":"record","payload":{"canonical_record":{"source":{"id":"2409.12471","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-19T05:20:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"9cbf43cf624da457b9cc85d1aef0cefa61aaa6ca9e380bb814bdbe1f56680a32","abstract_canon_sha256":"863d02e8ea8fd4f1ac82745683bcbfbe1443975f8985aab63f3cec56ff21edb1"},"schema_version":"1.0"},"canonical_sha256":"ee071407edcfb966dd3a396e1d7fa7e9ad1d6ffb49cf9b400418a1e3475b4e68","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:08:54.742467Z","signature_b64":"tbeyLhVQ+gdqv1L8275xd9vGI640Brbc86nUM5+9Y8iZ3ixRb0GMMSyxdWL+OvYkWHE+qRmxhbQFZh24LV4XDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ee071407edcfb966dd3a396e1d7fa7e9ad1d6ffb49cf9b400418a1e3475b4e68","last_reissued_at":"2026-07-05T09:08:54.741961Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:08:54.741961Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.12471","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":"2026-07-05T09:08:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nSeWm/Pjl6Ne4CzXhGGKZn0YmVjpBkHt105X32XI+CvKJO6B0gCrdj++2IVIFC3/E1ksIwZdf7OhC/c5eimWBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T16:01:09.372677Z"},"content_sha256":"2d39b47bde459ab07ded96505a3e8fd6c82ace533759a3205de3155809fda445","schema_version":"1.0","event_id":"sha256:2d39b47bde459ab07ded96505a3e8fd6c82ace533759a3205de3155809fda445"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:5YDRIB7NZ64WNXJ2HFXB275H5G","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Arena 4.0: A Comprehensive ROS2 Development and Benchmarking Platform for Human-centric Navigation Using Generative-Model-based Environment Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.RO","authors_text":"Ahmed Martban, Diego Diaz, Harold Soh, Huajian Zeng, Huu Giang Nguyen, Jonas Kreutz, Linh K\\\"astner, Maximilian Ho-Kyoung Schreff, Tim Lenz, Volodymyr Shcherbyna1","submitted_at":"2024-09-19T05:20:13Z","abstract_excerpt":"Building on the foundations of our previous work, this paper introduces Arena 4.0, a significant advancement over Arena 3.0, Arena-Bench, Arena 1.0, and Arena 2.0. Arena 4.0 offers three key novel contributions: (1) a generative-model-based world and scenario generation approach that utilizes large language models (LLMs) and diffusion models to dynamically generate complex, human-centric environments from text prompts or 2D floorplans, useful for the development and benchmarking of social navigation strategies; (2) a comprehensive 3D model database, extendable with additional 3D assets that ar"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.12471","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/2409.12471/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":"2026-07-05T09:08:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yYqaF4ai4zDQrMNboK6CefnjdtF4ISWlQxCBuNuTGgKXAZJ2uYB5iTyIwnaJDGYT+3FLBYaa4Wc/cb6vyLrnAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T16:01:09.373215Z"},"content_sha256":"954f2291797ccd0832d953da4c842615591629d0cc4bb06e04201ce007660364","schema_version":"1.0","event_id":"sha256:954f2291797ccd0832d953da4c842615591629d0cc4bb06e04201ce007660364"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5YDRIB7NZ64WNXJ2HFXB275H5G/bundle.json","state_url":"https://pith.science/pith/5YDRIB7NZ64WNXJ2HFXB275H5G/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5YDRIB7NZ64WNXJ2HFXB275H5G/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":"2026-08-13T16:01:09Z","links":{"resolver":"https://pith.science/pith/5YDRIB7NZ64WNXJ2HFXB275H5G","bundle":"https://pith.science/pith/5YDRIB7NZ64WNXJ2HFXB275H5G/bundle.json","state":"https://pith.science/pith/5YDRIB7NZ64WNXJ2HFXB275H5G/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5YDRIB7NZ64WNXJ2HFXB275H5G/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:5YDRIB7NZ64WNXJ2HFXB275H5G","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":"863d02e8ea8fd4f1ac82745683bcbfbe1443975f8985aab63f3cec56ff21edb1","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-19T05:20:13Z","title_canon_sha256":"9cbf43cf624da457b9cc85d1aef0cefa61aaa6ca9e380bb814bdbe1f56680a32"},"schema_version":"1.0","source":{"id":"2409.12471","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.12471","created_at":"2026-07-05T09:08:54Z"},{"alias_kind":"arxiv_version","alias_value":"2409.12471v1","created_at":"2026-07-05T09:08:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.12471","created_at":"2026-07-05T09:08:54Z"},{"alias_kind":"pith_short_12","alias_value":"5YDRIB7NZ64W","created_at":"2026-07-05T09:08:54Z"},{"alias_kind":"pith_short_16","alias_value":"5YDRIB7NZ64WNXJ2","created_at":"2026-07-05T09:08:54Z"},{"alias_kind":"pith_short_8","alias_value":"5YDRIB7N","created_at":"2026-07-05T09:08:54Z"}],"graph_snapshots":[{"event_id":"sha256:954f2291797ccd0832d953da4c842615591629d0cc4bb06e04201ce007660364","target":"graph","created_at":"2026-07-05T09:08:54Z","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/2409.12471/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Building on the foundations of our previous work, this paper introduces Arena 4.0, a significant advancement over Arena 3.0, Arena-Bench, Arena 1.0, and Arena 2.0. Arena 4.0 offers three key novel contributions: (1) a generative-model-based world and scenario generation approach that utilizes large language models (LLMs) and diffusion models to dynamically generate complex, human-centric environments from text prompts or 2D floorplans, useful for the development and benchmarking of social navigation strategies; (2) a comprehensive 3D model database, extendable with additional 3D assets that ar","authors_text":"Ahmed Martban, Diego Diaz, Harold Soh, Huajian Zeng, Huu Giang Nguyen, Jonas Kreutz, Linh K\\\"astner, Maximilian Ho-Kyoung Schreff, Tim Lenz, Volodymyr Shcherbyna1","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-19T05:20:13Z","title":"Arena 4.0: A Comprehensive ROS2 Development and Benchmarking Platform for Human-centric Navigation Using Generative-Model-based Environment Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.12471","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":"sha256:2d39b47bde459ab07ded96505a3e8fd6c82ace533759a3205de3155809fda445","target":"record","created_at":"2026-07-05T09:08:54Z","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":"863d02e8ea8fd4f1ac82745683bcbfbe1443975f8985aab63f3cec56ff21edb1","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-09-19T05:20:13Z","title_canon_sha256":"9cbf43cf624da457b9cc85d1aef0cefa61aaa6ca9e380bb814bdbe1f56680a32"},"schema_version":"1.0","source":{"id":"2409.12471","kind":"arxiv","version":1}},"canonical_sha256":"ee071407edcfb966dd3a396e1d7fa7e9ad1d6ffb49cf9b400418a1e3475b4e68","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ee071407edcfb966dd3a396e1d7fa7e9ad1d6ffb49cf9b400418a1e3475b4e68","first_computed_at":"2026-07-05T09:08:54.741961Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:08:54.741961Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tbeyLhVQ+gdqv1L8275xd9vGI640Brbc86nUM5+9Y8iZ3ixRb0GMMSyxdWL+OvYkWHE+qRmxhbQFZh24LV4XDA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:08:54.742467Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.12471","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2d39b47bde459ab07ded96505a3e8fd6c82ace533759a3205de3155809fda445","sha256:954f2291797ccd0832d953da4c842615591629d0cc4bb06e04201ce007660364"],"state_sha256":"6954887413618485ef4cb15f02fe6fae69f61f0e3ed93d56ce2de042f5e4bf7c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ojjH40pS0QIV/hH9inYORtp2aXob1YlFWr/Rv9iRhp0iEzhwOklaAkB/gnHRSHf/xuzX7tJI+meC1XiJJHeNAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T16:01:09.382251Z","bundle_sha256":"c412e927c25770d3f14c704fd4c54cbf6e8beb8478e55e9e9089edd280988708"}}