{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:WBZQGAKK2QKJOOG4BTUM35BSS3","short_pith_number":"pith:WBZQGAKK","canonical_record":{"source":{"id":"2607.17351","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-07-19T17:26:34Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"47920354dbac7c1c189eb150213a3c2cd95b1c1a8c266e29c03f417bfdbab340","abstract_canon_sha256":"aab9b66fbd1db6852e601181affadd7d22c74f542ea24cd8acea3c929571e566"},"schema_version":"1.0"},"canonical_sha256":"b07303014ad4149738dc0ce8cdf43296d1d2452467cc5a7f577ef3a450d2b9ba","source":{"kind":"arxiv","id":"2607.17351","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.17351","created_at":"2026-07-21T01:21:29Z"},{"alias_kind":"arxiv_version","alias_value":"2607.17351v1","created_at":"2026-07-21T01:21:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.17351","created_at":"2026-07-21T01:21:29Z"},{"alias_kind":"pith_short_12","alias_value":"WBZQGAKK2QKJ","created_at":"2026-07-21T01:21:29Z"},{"alias_kind":"pith_short_16","alias_value":"WBZQGAKK2QKJOOG4","created_at":"2026-07-21T01:21:29Z"},{"alias_kind":"pith_short_8","alias_value":"WBZQGAKK","created_at":"2026-07-21T01:21:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:WBZQGAKK2QKJOOG4BTUM35BSS3","target":"record","payload":{"canonical_record":{"source":{"id":"2607.17351","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-07-19T17:26:34Z","cross_cats_sorted":["cs.RO"],"title_canon_sha256":"47920354dbac7c1c189eb150213a3c2cd95b1c1a8c266e29c03f417bfdbab340","abstract_canon_sha256":"aab9b66fbd1db6852e601181affadd7d22c74f542ea24cd8acea3c929571e566"},"schema_version":"1.0"},"canonical_sha256":"b07303014ad4149738dc0ce8cdf43296d1d2452467cc5a7f577ef3a450d2b9ba","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-21T01:21:29.177925Z","signature_b64":"Cu6blf3Zytl6ekuwhhYtkblHsm+HjLOLlhe0u2WcSjfdL6uvwyijZT/LUPkEHwZmafXVAPJfQG+HvRMWZBW3Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b07303014ad4149738dc0ce8cdf43296d1d2452467cc5a7f577ef3a450d2b9ba","last_reissued_at":"2026-07-21T01:21:29.173443Z","signature_status":"signed_v1","first_computed_at":"2026-07-21T01:21:29.173443Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.17351","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":"2026-07-21T01:21:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+hAt3V/blddyiOn0mn+0RqxO4p3tANS0eacnqLul884lVH9CukLVs9ZmVaGgscDdrASnXddkBn2YlyLyPr1fDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T16:02:39.160148Z"},"content_sha256":"8c798082058cec76fe9d7e1ed824fc918057c32ff7b36d9ab847267336384b0e","schema_version":"1.0","event_id":"sha256:8c798082058cec76fe9d7e1ed824fc918057c32ff7b36d9ab847267336384b0e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:WBZQGAKK2QKJOOG4BTUM35BSS3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO"],"primary_cat":"cs.AI","authors_text":"Barak Pinkovich, Chaim Baskin, Eli Goldenshluger","submitted_at":"2026-07-19T17:26:34Z","abstract_excerpt":"DeeperRadar is a radar-centric, sensor-stack-conditioned framework that co-designs radar sensing and multi-modal 3D detection for autonomous mobility by learning a sparse acquisition pattern end-to-end with the fusion model. A learnable MIMO design module is trained end-to-end within a fusion network that operates directly on raw radar ADC data together with camera images and LiDAR point clouds. During training, the design module is supervised by the other sensors, enabling the system to learn both which receiver antennas to activate and the effective number of them. At deployment, the design "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.17351","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/2607.17351/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":"2026-07-21T01:21:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1tZeA2DSZiVht1Z+kdw87tw/68D2/KzY9sM5xKBp+1XQPGUUqN/yRu0NEhLLfxBP4JesZzb7iFZYtKnSw2MDDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T16:02:39.161099Z"},"content_sha256":"183248a4cd459514f5e26d64f55784d6d4b27d237cc0131f9f01c0777aa36435","schema_version":"1.0","event_id":"sha256:183248a4cd459514f5e26d64f55784d6d4b27d237cc0131f9f01c0777aa36435"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:WBZQGAKK2QKJOOG4BTUM35BSS3","target":"integrity","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1109/LRA.2024.3502058) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"M. Zeller, D. C. Herraez, B. Ayan, J. Behley, M. Heidingsfeld, and C. Stachniss, “Semrafiner: Panoptic segmentation in sparse and noisy radar point clouds,”IEEE Robotics and Automation Letters, p. 1–8, 2024. [Online]. Available: http://dx.d","arxiv_id":"2607.17351","detector":"doi_compliance","evidence":{"ref_index":21,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"10.1109/lra.2024","reconstructed_doi":"10.1109/LRA.2024.3502058"},"severity":"advisory","ref_index":21,"audited_at":"2026-08-01T18:29:06.782857Z","event_type":"pith.integrity.v1","detected_doi":"10.1109/LRA.2024.3502058","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"9b41dd08d931d022b6cd57915a17610e85542eb9c07a4c0adfe51402d4dd078a","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.1.0","detected_arxiv_id":null,"integrity_event_id":16394,"payload_sha256":"9b9f625a23dca9d0eb920e0b35bff754883db77966215bc353469ef315944796","signature_b64":"RGsbjsQGOD3Cq1WebGV3Zl9ngAqAFhhH/EQHdQV3vXcSneLLUoE9j1y4g9HSEJ9mbCHGvhipGpsnhYmpT/IxAw==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-01T18:33:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lSPcNILTLVm1PY9PsnxOKdrb46u2QmTgEyYwphFPsVhjWzqBe1tUSlPgGpVrUWCW2/QyI3yoxrPJKG914LarAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T16:02:39.164962Z"},"content_sha256":"93ac478505cdfa03c0d3c9e4fcb0d206a745e086b87e161053a3ff1f020cd444","schema_version":"1.0","event_id":"sha256:93ac478505cdfa03c0d3c9e4fcb0d206a745e086b87e161053a3ff1f020cd444"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WBZQGAKK2QKJOOG4BTUM35BSS3/bundle.json","state_url":"https://pith.science/pith/WBZQGAKK2QKJOOG4BTUM35BSS3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WBZQGAKK2QKJOOG4BTUM35BSS3/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":"2026-08-06T16:02:39Z","links":{"resolver":"https://pith.science/pith/WBZQGAKK2QKJOOG4BTUM35BSS3","bundle":"https://pith.science/pith/WBZQGAKK2QKJOOG4BTUM35BSS3/bundle.json","state":"https://pith.science/pith/WBZQGAKK2QKJOOG4BTUM35BSS3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WBZQGAKK2QKJOOG4BTUM35BSS3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WBZQGAKK2QKJOOG4BTUM35BSS3","merge_version":"pith-open-graph-merge-v1","event_count":3,"valid_event_count":3,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"aab9b66fbd1db6852e601181affadd7d22c74f542ea24cd8acea3c929571e566","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-07-19T17:26:34Z","title_canon_sha256":"47920354dbac7c1c189eb150213a3c2cd95b1c1a8c266e29c03f417bfdbab340"},"schema_version":"1.0","source":{"id":"2607.17351","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.17351","created_at":"2026-07-21T01:21:29Z"},{"alias_kind":"arxiv_version","alias_value":"2607.17351v1","created_at":"2026-07-21T01:21:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.17351","created_at":"2026-07-21T01:21:29Z"},{"alias_kind":"pith_short_12","alias_value":"WBZQGAKK2QKJ","created_at":"2026-07-21T01:21:29Z"},{"alias_kind":"pith_short_16","alias_value":"WBZQGAKK2QKJOOG4","created_at":"2026-07-21T01:21:29Z"},{"alias_kind":"pith_short_8","alias_value":"WBZQGAKK","created_at":"2026-07-21T01:21:29Z"}],"graph_snapshots":[{"event_id":"sha256:183248a4cd459514f5e26d64f55784d6d4b27d237cc0131f9f01c0777aa36435","target":"graph","created_at":"2026-07-21T01:21:29Z","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/2607.17351/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"DeeperRadar is a radar-centric, sensor-stack-conditioned framework that co-designs radar sensing and multi-modal 3D detection for autonomous mobility by learning a sparse acquisition pattern end-to-end with the fusion model. A learnable MIMO design module is trained end-to-end within a fusion network that operates directly on raw radar ADC data together with camera images and LiDAR point clouds. During training, the design module is supervised by the other sensors, enabling the system to learn both which receiver antennas to activate and the effective number of them. At deployment, the design ","authors_text":"Barak Pinkovich, Chaim Baskin, Eli Goldenshluger","cross_cats":["cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-07-19T17:26:34Z","title":"DeeperRadar: End-to-End MIMO Radar Design and Multi-Modal Fusion for Autonomous Vehicle Perception"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.17351","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":"sha256:8c798082058cec76fe9d7e1ed824fc918057c32ff7b36d9ab847267336384b0e","target":"record","created_at":"2026-07-21T01:21:29Z","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":"aab9b66fbd1db6852e601181affadd7d22c74f542ea24cd8acea3c929571e566","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-07-19T17:26:34Z","title_canon_sha256":"47920354dbac7c1c189eb150213a3c2cd95b1c1a8c266e29c03f417bfdbab340"},"schema_version":"1.0","source":{"id":"2607.17351","kind":"arxiv","version":1}},"canonical_sha256":"b07303014ad4149738dc0ce8cdf43296d1d2452467cc5a7f577ef3a450d2b9ba","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b07303014ad4149738dc0ce8cdf43296d1d2452467cc5a7f577ef3a450d2b9ba","first_computed_at":"2026-07-21T01:21:29.173443Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-21T01:21:29.173443Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Cu6blf3Zytl6ekuwhhYtkblHsm+HjLOLlhe0u2WcSjfdL6uvwyijZT/LUPkEHwZmafXVAPJfQG+HvRMWZBW3Bg==","signature_status":"signed_v1","signed_at":"2026-07-21T01:21:29.177925Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.17351","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8c798082058cec76fe9d7e1ed824fc918057c32ff7b36d9ab847267336384b0e","sha256:183248a4cd459514f5e26d64f55784d6d4b27d237cc0131f9f01c0777aa36435","sha256:93ac478505cdfa03c0d3c9e4fcb0d206a745e086b87e161053a3ff1f020cd444"],"state_sha256":"948bf86689a87ff66ba2d3865913db5d0c3de64f044afaef1d461338c198f58f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dLGfhRJV6Iq4ca5zYJwbZqJe2OMWk3eR4OXxctwDbF/lj9d2yzCKsH/ZvHqb9wAOpoYZbvdlmagPOPIs7WURAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T16:02:39.168828Z","bundle_sha256":"0c524cb77677a2ec1f123c5e063835b5d0b68ccf41b659cc58fdf4ee10f03483"}}