{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:YRWLLH5RPCTPB5RJSIUZNYLPV6","short_pith_number":"pith:YRWLLH5R","canonical_record":{"source":{"id":"2607.13059","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-06T15:46:30Z","cross_cats_sorted":[],"title_canon_sha256":"1e7ab01003fe41fb5914804bb0ad099de47cb0e31d2c289578333741f9334d6a","abstract_canon_sha256":"dce93bbb72eb1256e637213f948a025d77b4060289145fb4b27e8973e6ed85d0"},"schema_version":"1.0"},"canonical_sha256":"c46cb59fb178a6f0f629922996e16faf8fc4e648568b019fc04ebcb632d44549","source":{"kind":"arxiv","id":"2607.13059","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.13059","created_at":"2026-07-16T00:21:54Z"},{"alias_kind":"arxiv_version","alias_value":"2607.13059v1","created_at":"2026-07-16T00:21:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.13059","created_at":"2026-07-16T00:21:54Z"},{"alias_kind":"pith_short_12","alias_value":"YRWLLH5RPCTP","created_at":"2026-07-16T00:21:54Z"},{"alias_kind":"pith_short_16","alias_value":"YRWLLH5RPCTPB5RJ","created_at":"2026-07-16T00:21:54Z"},{"alias_kind":"pith_short_8","alias_value":"YRWLLH5R","created_at":"2026-07-16T00:21:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:YRWLLH5RPCTPB5RJSIUZNYLPV6","target":"record","payload":{"canonical_record":{"source":{"id":"2607.13059","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-06T15:46:30Z","cross_cats_sorted":[],"title_canon_sha256":"1e7ab01003fe41fb5914804bb0ad099de47cb0e31d2c289578333741f9334d6a","abstract_canon_sha256":"dce93bbb72eb1256e637213f948a025d77b4060289145fb4b27e8973e6ed85d0"},"schema_version":"1.0"},"canonical_sha256":"c46cb59fb178a6f0f629922996e16faf8fc4e648568b019fc04ebcb632d44549","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-16T00:21:54.043815Z","signature_b64":"nQy0g0OopjB82M3jhd9jQAGjUUuuuICtyKRtWc518AkNwve8zARa85posqTNQ23WqqMnDnVXhjVu9VTQw64JAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c46cb59fb178a6f0f629922996e16faf8fc4e648568b019fc04ebcb632d44549","last_reissued_at":"2026-07-16T00:21:54.042893Z","signature_status":"signed_v1","first_computed_at":"2026-07-16T00:21:54.042893Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.13059","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":"2026-07-16T00:21:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W6p6Du3+6/AU32pGO9TX46MxE9+nG6Psw+6RWdfvM924eXXzZEhzoAC288Ba8L2KITqMHdIdXe2WTp803MJFCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T15:41:25.417776Z"},"content_sha256":"d50d7308c94448c6483a05ea5d2b7088158fa0cb742c0d92c6b2f614a371ac15","schema_version":"1.0","event_id":"sha256:d50d7308c94448c6483a05ea5d2b7088158fa0cb742c0d92c6b2f614a371ac15"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:YRWLLH5RPCTPB5RJSIUZNYLPV6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GPUSimBench: Towards Scalable and Reliable GPU-Accelerated Simulators in Embodied AI","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Dmitry Yudin, Hengjie Li, Huzhenyu Zhang, Jingcheng Pang, Li Ma, Shenghai Yuan, Wenrui Yan","submitted_at":"2026-07-06T15:46:30Z","abstract_excerpt":"Data-driven embodied AI is rapidly transitioning into a paradigm that scales training through massively parallel simulation, where GPU-accelerated simulators serve as the foundational data infrastructure. However, as computational throughput scales, the underlying trade-offs between parallel efficiency, physical fidelity, and execution determinism remain largely unexamined, hindering the development of reliable robot learning. In this paper, we expose the hidden limits of mainstream GPU-based robotic simulators (e.g., Isaac Lab, Genesis) by introducing GPUSimBench, which focuses on scalability"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.13059","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/2607.13059/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":"2026-07-16T00:21:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jZJqzFqGlFCwjXb53Epw84fdzGDcEfdkw5aTLQcym3b/w9ZWXss7tulnoW37HMzsn2ybKnQiIJ44md/RtT7nCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T15:41:25.418918Z"},"content_sha256":"a1ae12bfab6a802f1c7b51ae3d875834a76d5eb8b3cf2299eba3d9e71e694fd3","schema_version":"1.0","event_id":"sha256:a1ae12bfab6a802f1c7b51ae3d875834a76d5eb8b3cf2299eba3d9e71e694fd3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YRWLLH5RPCTPB5RJSIUZNYLPV6/bundle.json","state_url":"https://pith.science/pith/YRWLLH5RPCTPB5RJSIUZNYLPV6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YRWLLH5RPCTPB5RJSIUZNYLPV6/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":"2026-08-04T15:41:25Z","links":{"resolver":"https://pith.science/pith/YRWLLH5RPCTPB5RJSIUZNYLPV6","bundle":"https://pith.science/pith/YRWLLH5RPCTPB5RJSIUZNYLPV6/bundle.json","state":"https://pith.science/pith/YRWLLH5RPCTPB5RJSIUZNYLPV6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YRWLLH5RPCTPB5RJSIUZNYLPV6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:YRWLLH5RPCTPB5RJSIUZNYLPV6","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":"dce93bbb72eb1256e637213f948a025d77b4060289145fb4b27e8973e6ed85d0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-06T15:46:30Z","title_canon_sha256":"1e7ab01003fe41fb5914804bb0ad099de47cb0e31d2c289578333741f9334d6a"},"schema_version":"1.0","source":{"id":"2607.13059","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.13059","created_at":"2026-07-16T00:21:54Z"},{"alias_kind":"arxiv_version","alias_value":"2607.13059v1","created_at":"2026-07-16T00:21:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.13059","created_at":"2026-07-16T00:21:54Z"},{"alias_kind":"pith_short_12","alias_value":"YRWLLH5RPCTP","created_at":"2026-07-16T00:21:54Z"},{"alias_kind":"pith_short_16","alias_value":"YRWLLH5RPCTPB5RJ","created_at":"2026-07-16T00:21:54Z"},{"alias_kind":"pith_short_8","alias_value":"YRWLLH5R","created_at":"2026-07-16T00:21:54Z"}],"graph_snapshots":[{"event_id":"sha256:a1ae12bfab6a802f1c7b51ae3d875834a76d5eb8b3cf2299eba3d9e71e694fd3","target":"graph","created_at":"2026-07-16T00:21:54Z","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/2607.13059/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Data-driven embodied AI is rapidly transitioning into a paradigm that scales training through massively parallel simulation, where GPU-accelerated simulators serve as the foundational data infrastructure. However, as computational throughput scales, the underlying trade-offs between parallel efficiency, physical fidelity, and execution determinism remain largely unexamined, hindering the development of reliable robot learning. In this paper, we expose the hidden limits of mainstream GPU-based robotic simulators (e.g., Isaac Lab, Genesis) by introducing GPUSimBench, which focuses on scalability","authors_text":"Dmitry Yudin, Hengjie Li, Huzhenyu Zhang, Jingcheng Pang, Li Ma, Shenghai Yuan, Wenrui Yan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-06T15:46:30Z","title":"GPUSimBench: Towards Scalable and Reliable GPU-Accelerated Simulators in Embodied AI"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.13059","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:d50d7308c94448c6483a05ea5d2b7088158fa0cb742c0d92c6b2f614a371ac15","target":"record","created_at":"2026-07-16T00:21:54Z","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":"dce93bbb72eb1256e637213f948a025d77b4060289145fb4b27e8973e6ed85d0","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-06T15:46:30Z","title_canon_sha256":"1e7ab01003fe41fb5914804bb0ad099de47cb0e31d2c289578333741f9334d6a"},"schema_version":"1.0","source":{"id":"2607.13059","kind":"arxiv","version":1}},"canonical_sha256":"c46cb59fb178a6f0f629922996e16faf8fc4e648568b019fc04ebcb632d44549","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c46cb59fb178a6f0f629922996e16faf8fc4e648568b019fc04ebcb632d44549","first_computed_at":"2026-07-16T00:21:54.042893Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-16T00:21:54.042893Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nQy0g0OopjB82M3jhd9jQAGjUUuuuICtyKRtWc518AkNwve8zARa85posqTNQ23WqqMnDnVXhjVu9VTQw64JAw==","signature_status":"signed_v1","signed_at":"2026-07-16T00:21:54.043815Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.13059","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d50d7308c94448c6483a05ea5d2b7088158fa0cb742c0d92c6b2f614a371ac15","sha256:a1ae12bfab6a802f1c7b51ae3d875834a76d5eb8b3cf2299eba3d9e71e694fd3"],"state_sha256":"34d56cd9b117e8b5e58e81fd0b3001041541f21098b2fd859595e695ee8aafbc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+H6ZHqbA99fkN4seEFJAcpxJvBZNoUbUHfUsY7Cb6RZA8HnGdja7uoNjUoF6ofHiSemLu5dx03l36g3zkM7TBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T15:41:25.432729Z","bundle_sha256":"14786e106ec572f646745e82b62619eed9e13d12f0f3da0311e7ae0879a5e0f2"}}