{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:4D4CBX67KJOGU7KXLN3WARB4DE","short_pith_number":"pith:4D4CBX67","canonical_record":{"source":{"id":"2606.29684","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2026-06-29T01:17:35Z","cross_cats_sorted":["cs.CV","cs.RO"],"title_canon_sha256":"fdd9ae0830d9c1ac4230244c68c77a1f39b0a75ac32301e92498b0293852dc9f","abstract_canon_sha256":"53157781a96e15b0062fc80aa2b076dc9480d9e6a6f4df1bf6587d56e52dfd5c"},"schema_version":"1.0"},"canonical_sha256":"e0f820dfdf525c6a7d575b7760443c193dffac39bfaf8a382644076202f91172","source":{"kind":"arxiv","id":"2606.29684","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.29684","created_at":"2026-06-30T02:17:30Z"},{"alias_kind":"arxiv_version","alias_value":"2606.29684v1","created_at":"2026-06-30T02:17:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.29684","created_at":"2026-06-30T02:17:30Z"},{"alias_kind":"pith_short_12","alias_value":"4D4CBX67KJOG","created_at":"2026-06-30T02:17:30Z"},{"alias_kind":"pith_short_16","alias_value":"4D4CBX67KJOGU7KX","created_at":"2026-06-30T02:17:30Z"},{"alias_kind":"pith_short_8","alias_value":"4D4CBX67","created_at":"2026-06-30T02:17:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:4D4CBX67KJOGU7KXLN3WARB4DE","target":"record","payload":{"canonical_record":{"source":{"id":"2606.29684","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2026-06-29T01:17:35Z","cross_cats_sorted":["cs.CV","cs.RO"],"title_canon_sha256":"fdd9ae0830d9c1ac4230244c68c77a1f39b0a75ac32301e92498b0293852dc9f","abstract_canon_sha256":"53157781a96e15b0062fc80aa2b076dc9480d9e6a6f4df1bf6587d56e52dfd5c"},"schema_version":"1.0"},"canonical_sha256":"e0f820dfdf525c6a7d575b7760443c193dffac39bfaf8a382644076202f91172","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-30T02:17:30.579731Z","signature_b64":"6K6dvM7aHHPubs+9qNh8xHzWre2OYxrjFkE+Ay5YoKGkc5FCasXGPFZ5jmr6PSECG1uClFxx+bgEb680n2k6CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e0f820dfdf525c6a7d575b7760443c193dffac39bfaf8a382644076202f91172","last_reissued_at":"2026-06-30T02:17:30.579070Z","signature_status":"signed_v1","first_computed_at":"2026-06-30T02:17:30.579070Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.29684","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":"2026-06-30T02:17:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UcM47oJTy5KVVVexmNNfrRq8cWnC4dHb88G5cUR1IWR+hobTGx535d2ghSTJR193qGLmEB1QquVHIN2CVKfLAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T04:37:14.905432Z"},"content_sha256":"68fffaaaf6da1ca9781693e1b5b818a488d2b290f32024d516bcf2554254735b","schema_version":"1.0","event_id":"sha256:68fffaaaf6da1ca9781693e1b5b818a488d2b290f32024d516bcf2554254735b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:4D4CBX67KJOGU7KXLN3WARB4DE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evolutionary Hyperparameter Optimization to Find Lightweight CNN Models for Autonomous Steering","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.RO"],"primary_cat":"cs.NE","authors_text":"Chan-Jin Chung, Devson Butani, Ryan Kaddis","submitted_at":"2026-06-29T01:17:35Z","abstract_excerpt":"This research investigates the optimization of Convolutional and Dense Neural Networks (CNNs and DNNs) for autonomous steering using the (N+M) Evolution Strategy (ES) with the 1/5th success rule. The primary objective is to develop a lightweight CNN based model capable of real-time steering angle prediction, mimicking human driving behavior on predefined paths. The ES algorithm automates hyperparameter tuning, dynamically adjusting parameters such as filter sizes and layer configurations. Data collection encompasses driving scenarios recorded via the LTU ACTor autonomous driving platform, incl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.29684","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/2606.29684/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":"2026-06-30T02:17:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+NoLS1MfG0A8W7ZKCSurJsQThFT186OHx8c/QQ1EBpyYeWV+LnfqyOVllgE2CMoWb5HdUh75y+euXXusY4kHAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T04:37:14.905893Z"},"content_sha256":"693c1410f537b08c1ff61d2f9c64c28f13fab80b4a8233080adba551223260a0","schema_version":"1.0","event_id":"sha256:693c1410f537b08c1ff61d2f9c64c28f13fab80b4a8233080adba551223260a0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4D4CBX67KJOGU7KXLN3WARB4DE/bundle.json","state_url":"https://pith.science/pith/4D4CBX67KJOGU7KXLN3WARB4DE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4D4CBX67KJOGU7KXLN3WARB4DE/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":"2026-07-05T04:37:14Z","links":{"resolver":"https://pith.science/pith/4D4CBX67KJOGU7KXLN3WARB4DE","bundle":"https://pith.science/pith/4D4CBX67KJOGU7KXLN3WARB4DE/bundle.json","state":"https://pith.science/pith/4D4CBX67KJOGU7KXLN3WARB4DE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4D4CBX67KJOGU7KXLN3WARB4DE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:4D4CBX67KJOGU7KXLN3WARB4DE","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":"53157781a96e15b0062fc80aa2b076dc9480d9e6a6f4df1bf6587d56e52dfd5c","cross_cats_sorted":["cs.CV","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2026-06-29T01:17:35Z","title_canon_sha256":"fdd9ae0830d9c1ac4230244c68c77a1f39b0a75ac32301e92498b0293852dc9f"},"schema_version":"1.0","source":{"id":"2606.29684","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.29684","created_at":"2026-06-30T02:17:30Z"},{"alias_kind":"arxiv_version","alias_value":"2606.29684v1","created_at":"2026-06-30T02:17:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.29684","created_at":"2026-06-30T02:17:30Z"},{"alias_kind":"pith_short_12","alias_value":"4D4CBX67KJOG","created_at":"2026-06-30T02:17:30Z"},{"alias_kind":"pith_short_16","alias_value":"4D4CBX67KJOGU7KX","created_at":"2026-06-30T02:17:30Z"},{"alias_kind":"pith_short_8","alias_value":"4D4CBX67","created_at":"2026-06-30T02:17:30Z"}],"graph_snapshots":[{"event_id":"sha256:693c1410f537b08c1ff61d2f9c64c28f13fab80b4a8233080adba551223260a0","target":"graph","created_at":"2026-06-30T02:17:30Z","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/2606.29684/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This research investigates the optimization of Convolutional and Dense Neural Networks (CNNs and DNNs) for autonomous steering using the (N+M) Evolution Strategy (ES) with the 1/5th success rule. The primary objective is to develop a lightweight CNN based model capable of real-time steering angle prediction, mimicking human driving behavior on predefined paths. The ES algorithm automates hyperparameter tuning, dynamically adjusting parameters such as filter sizes and layer configurations. Data collection encompasses driving scenarios recorded via the LTU ACTor autonomous driving platform, incl","authors_text":"Chan-Jin Chung, Devson Butani, Ryan Kaddis","cross_cats":["cs.CV","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2026-06-29T01:17:35Z","title":"Evolutionary Hyperparameter Optimization to Find Lightweight CNN Models for Autonomous Steering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.29684","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":"sha256:68fffaaaf6da1ca9781693e1b5b818a488d2b290f32024d516bcf2554254735b","target":"record","created_at":"2026-06-30T02:17:30Z","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":"53157781a96e15b0062fc80aa2b076dc9480d9e6a6f4df1bf6587d56e52dfd5c","cross_cats_sorted":["cs.CV","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2026-06-29T01:17:35Z","title_canon_sha256":"fdd9ae0830d9c1ac4230244c68c77a1f39b0a75ac32301e92498b0293852dc9f"},"schema_version":"1.0","source":{"id":"2606.29684","kind":"arxiv","version":1}},"canonical_sha256":"e0f820dfdf525c6a7d575b7760443c193dffac39bfaf8a382644076202f91172","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e0f820dfdf525c6a7d575b7760443c193dffac39bfaf8a382644076202f91172","first_computed_at":"2026-06-30T02:17:30.579070Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-30T02:17:30.579070Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6K6dvM7aHHPubs+9qNh8xHzWre2OYxrjFkE+Ay5YoKGkc5FCasXGPFZ5jmr6PSECG1uClFxx+bgEb680n2k6CA==","signature_status":"signed_v1","signed_at":"2026-06-30T02:17:30.579731Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.29684","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:68fffaaaf6da1ca9781693e1b5b818a488d2b290f32024d516bcf2554254735b","sha256:693c1410f537b08c1ff61d2f9c64c28f13fab80b4a8233080adba551223260a0"],"state_sha256":"a4d1533847b149a4420ea4351448bcc2f81e1030f1e1626f487b0d78948ed1e5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xzyp32If+9uKxrzaVN8yI3NQGpBiEtRaE80C2D9QAvxbnWpq9tpa1JnElell+R8CjRjRKgmyivS1YfcQvcdvDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T04:37:14.908051Z","bundle_sha256":"8204f9d9a1138261491253c0b1eed1c4ce1fe8af0cf8e0f72e1ef6bdc9166105"}}