{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:5QO35BBV6KWEWB4V7J5TCBAKVX","short_pith_number":"pith:5QO35BBV","canonical_record":{"source":{"id":"2105.01799","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2021-05-04T23:44:11Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"05595a1ba68f7c05c90f2c6f810287bde2d3b0539f1af9f78a82d482e4161ae5","abstract_canon_sha256":"e635af8cfbf369f170050f8e02112094de19963b990a368bf75b75b2be5e3edb"},"schema_version":"1.0"},"canonical_sha256":"ec1dbe8435f2ac4b0795fa7b31040aaddf21fcacd2d30beb9c119ef1458e4dfc","source":{"kind":"arxiv","id":"2105.01799","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.01799","created_at":"2026-07-05T02:37:48Z"},{"alias_kind":"arxiv_version","alias_value":"2105.01799v1","created_at":"2026-07-05T02:37:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.01799","created_at":"2026-07-05T02:37:48Z"},{"alias_kind":"pith_short_12","alias_value":"5QO35BBV6KWE","created_at":"2026-07-05T02:37:48Z"},{"alias_kind":"pith_short_16","alias_value":"5QO35BBV6KWEWB4V","created_at":"2026-07-05T02:37:48Z"},{"alias_kind":"pith_short_8","alias_value":"5QO35BBV","created_at":"2026-07-05T02:37:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:5QO35BBV6KWEWB4V7J5TCBAKVX","target":"record","payload":{"canonical_record":{"source":{"id":"2105.01799","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2021-05-04T23:44:11Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"05595a1ba68f7c05c90f2c6f810287bde2d3b0539f1af9f78a82d482e4161ae5","abstract_canon_sha256":"e635af8cfbf369f170050f8e02112094de19963b990a368bf75b75b2be5e3edb"},"schema_version":"1.0"},"canonical_sha256":"ec1dbe8435f2ac4b0795fa7b31040aaddf21fcacd2d30beb9c119ef1458e4dfc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:37:48.367031Z","signature_b64":"jd4RM3dxAwG863c9ol20BXlDujW7myPiUCChke2BRgjIY9BTmWgtspdJ7hlsD1hn7E+BZ/M4Qg+5ah1vCkTdBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ec1dbe8435f2ac4b0795fa7b31040aaddf21fcacd2d30beb9c119ef1458e4dfc","last_reissued_at":"2026-07-05T02:37:48.366637Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:37:48.366637Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2105.01799","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":"2026-07-05T02:37:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MT9B8h0+Hq7ztB7Sw+tsC/0RJQOZnAPoSjPlMR/3c0paQnj0zTPEjBw+/kWqbARBavm/AWTEuo4Dp+lqfupkCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T06:46:47.112973Z"},"content_sha256":"b17e67e16a4377de1c9974f8bf14ad746051179810decc174dbf8d931c084dbc","schema_version":"1.0","event_id":"sha256:b17e67e16a4377de1c9974f8bf14ad746051179810decc174dbf8d931c084dbc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:5QO35BBV6KWEWB4V7J5TCBAKVX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards End-to-End Deep Learning for Autonomous Racing: On Data Collection and a Unified Architecture for Steering and Throttle Prediction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.RO","authors_text":"Aly El Gamal, Benjamin J. Schwartz, Daniel J. Gonzalez, Manuel Mar, Rohan Kumar Manna, Shakti N. Wadekar, Shyam S. Kannan, Vishnu Chellapandi","submitted_at":"2021-05-04T23:44:11Z","abstract_excerpt":"Deep Neural Networks (DNNs) which are trained end-to-end have been successfully applied to solve complex problems that we have not been able to solve in past decades. Autonomous driving is one of the most complex problems which is yet to be completely solved and autonomous racing adds more complexity and exciting challenges to this problem. Towards the challenge of applying end-to-end learning to autonomous racing, this paper shows results on two aspects: (1) Analyzing the relationship between the driving data used for training and the maximum speed at which the DNN can be successfully applied"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.01799","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/2105.01799/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":"2026-07-05T02:37:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Bu/11RpUOzyFziEt7ixtYKZxXyuTXINC8bgkSz4L/FYdqyxR/IZkJ6UeeUHqbwkvGm+8tXfNKfacfq+EWxHlCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T06:46:47.113904Z"},"content_sha256":"7fb6d9592c0ad98a3e821ff6db67b8b0fd842d8824359b769e36795929ce7ea5","schema_version":"1.0","event_id":"sha256:7fb6d9592c0ad98a3e821ff6db67b8b0fd842d8824359b769e36795929ce7ea5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5QO35BBV6KWEWB4V7J5TCBAKVX/bundle.json","state_url":"https://pith.science/pith/5QO35BBV6KWEWB4V7J5TCBAKVX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5QO35BBV6KWEWB4V7J5TCBAKVX/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":"2026-08-14T06:46:47Z","links":{"resolver":"https://pith.science/pith/5QO35BBV6KWEWB4V7J5TCBAKVX","bundle":"https://pith.science/pith/5QO35BBV6KWEWB4V7J5TCBAKVX/bundle.json","state":"https://pith.science/pith/5QO35BBV6KWEWB4V7J5TCBAKVX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5QO35BBV6KWEWB4V7J5TCBAKVX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:5QO35BBV6KWEWB4V7J5TCBAKVX","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":"e635af8cfbf369f170050f8e02112094de19963b990a368bf75b75b2be5e3edb","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2021-05-04T23:44:11Z","title_canon_sha256":"05595a1ba68f7c05c90f2c6f810287bde2d3b0539f1af9f78a82d482e4161ae5"},"schema_version":"1.0","source":{"id":"2105.01799","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.01799","created_at":"2026-07-05T02:37:48Z"},{"alias_kind":"arxiv_version","alias_value":"2105.01799v1","created_at":"2026-07-05T02:37:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.01799","created_at":"2026-07-05T02:37:48Z"},{"alias_kind":"pith_short_12","alias_value":"5QO35BBV6KWE","created_at":"2026-07-05T02:37:48Z"},{"alias_kind":"pith_short_16","alias_value":"5QO35BBV6KWEWB4V","created_at":"2026-07-05T02:37:48Z"},{"alias_kind":"pith_short_8","alias_value":"5QO35BBV","created_at":"2026-07-05T02:37:48Z"}],"graph_snapshots":[{"event_id":"sha256:7fb6d9592c0ad98a3e821ff6db67b8b0fd842d8824359b769e36795929ce7ea5","target":"graph","created_at":"2026-07-05T02:37:48Z","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/2105.01799/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep Neural Networks (DNNs) which are trained end-to-end have been successfully applied to solve complex problems that we have not been able to solve in past decades. Autonomous driving is one of the most complex problems which is yet to be completely solved and autonomous racing adds more complexity and exciting challenges to this problem. Towards the challenge of applying end-to-end learning to autonomous racing, this paper shows results on two aspects: (1) Analyzing the relationship between the driving data used for training and the maximum speed at which the DNN can be successfully applied","authors_text":"Aly El Gamal, Benjamin J. Schwartz, Daniel J. Gonzalez, Manuel Mar, Rohan Kumar Manna, Shakti N. Wadekar, Shyam S. Kannan, Vishnu Chellapandi","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2021-05-04T23:44:11Z","title":"Towards End-to-End Deep Learning for Autonomous Racing: On Data Collection and a Unified Architecture for Steering and Throttle Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.01799","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:b17e67e16a4377de1c9974f8bf14ad746051179810decc174dbf8d931c084dbc","target":"record","created_at":"2026-07-05T02:37:48Z","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":"e635af8cfbf369f170050f8e02112094de19963b990a368bf75b75b2be5e3edb","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2021-05-04T23:44:11Z","title_canon_sha256":"05595a1ba68f7c05c90f2c6f810287bde2d3b0539f1af9f78a82d482e4161ae5"},"schema_version":"1.0","source":{"id":"2105.01799","kind":"arxiv","version":1}},"canonical_sha256":"ec1dbe8435f2ac4b0795fa7b31040aaddf21fcacd2d30beb9c119ef1458e4dfc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ec1dbe8435f2ac4b0795fa7b31040aaddf21fcacd2d30beb9c119ef1458e4dfc","first_computed_at":"2026-07-05T02:37:48.366637Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:37:48.366637Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jd4RM3dxAwG863c9ol20BXlDujW7myPiUCChke2BRgjIY9BTmWgtspdJ7hlsD1hn7E+BZ/M4Qg+5ah1vCkTdBA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:37:48.367031Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.01799","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b17e67e16a4377de1c9974f8bf14ad746051179810decc174dbf8d931c084dbc","sha256:7fb6d9592c0ad98a3e821ff6db67b8b0fd842d8824359b769e36795929ce7ea5"],"state_sha256":"c27c2ec261723d39ee0db2ec630985a308ab1b6525c3d5fd8bd3172c358e9594"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ob4shaxX+o6uPUiMpQhITrrVPCETMHkQbolcpEMq1cYLITcAgqZvqrzoj2pZBnWc1cfpq8wr25TXcHo9hqIGBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T06:46:47.119476Z","bundle_sha256":"f7b9ef9dca9c2d8df493af4f541179967454b3e8ac3b833830526bfc8f095317"}}