{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:T4BG5XBLHYXXKN7XWMQ4LPOWNQ","short_pith_number":"pith:T4BG5XBL","canonical_record":{"source":{"id":"2506.21772","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2025-06-11T09:58:33Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"90eb411c9de7e7f73b24221e7c1f20535bd07cf72d3019a1cf7471b186be19fa","abstract_canon_sha256":"9857a0c55dd4b5f76669505ae4fb279b82a8b815a1f9e672838fb0b2973439a8"},"schema_version":"1.0"},"canonical_sha256":"9f026edc2b3e2f7537f7b321c5bdd66c3f2b5bbe7c361b55b4c73b82c46c8cd0","source":{"kind":"arxiv","id":"2506.21772","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.21772","created_at":"2026-07-05T11:28:00Z"},{"alias_kind":"arxiv_version","alias_value":"2506.21772v1","created_at":"2026-07-05T11:28:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.21772","created_at":"2026-07-05T11:28:00Z"},{"alias_kind":"pith_short_12","alias_value":"T4BG5XBLHYXX","created_at":"2026-07-05T11:28:00Z"},{"alias_kind":"pith_short_16","alias_value":"T4BG5XBLHYXXKN7X","created_at":"2026-07-05T11:28:00Z"},{"alias_kind":"pith_short_8","alias_value":"T4BG5XBL","created_at":"2026-07-05T11:28:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:T4BG5XBLHYXXKN7XWMQ4LPOWNQ","target":"record","payload":{"canonical_record":{"source":{"id":"2506.21772","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2025-06-11T09:58:33Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"90eb411c9de7e7f73b24221e7c1f20535bd07cf72d3019a1cf7471b186be19fa","abstract_canon_sha256":"9857a0c55dd4b5f76669505ae4fb279b82a8b815a1f9e672838fb0b2973439a8"},"schema_version":"1.0"},"canonical_sha256":"9f026edc2b3e2f7537f7b321c5bdd66c3f2b5bbe7c361b55b4c73b82c46c8cd0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:28:00.789549Z","signature_b64":"pGRbIBM6WGPsKmB1FlB2w0yPNWA4Z13lTz0tWMTwMruJZSGmRks1/WmePZFXuDTqc2EzAGJdUg815di4o6UTBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9f026edc2b3e2f7537f7b321c5bdd66c3f2b5bbe7c361b55b4c73b82c46c8cd0","last_reissued_at":"2026-07-05T11:28:00.788981Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:28:00.788981Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.21772","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":"2026-07-05T11:28:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OU0ufsb3/E9Z2YYRSwA/cTQNTYlgphRgqDwh5aB+3tDP0lmLchJuoms7Ia8gPX1zUxJiZMpPIt0A2u90mJp9DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T00:36:09.800994Z"},"content_sha256":"fbbee8e9b73e6f837e6facb91c254d504ec2dd061ba80b9b45e201dacdd85ed3","schema_version":"1.0","event_id":"sha256:fbbee8e9b73e6f837e6facb91c254d504ec2dd061ba80b9b45e201dacdd85ed3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:T4BG5XBLHYXXKN7XWMQ4LPOWNQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Searching Efficient Deep Architectures for Radar Target Detection using Monte-Carlo Tree Search","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"eess.SP","authors_text":"Cyrille Enderli, No\\'e Lallouet, St\\'ephanie Gourdin, Tristan Cazenave","submitted_at":"2025-06-11T09:58:33Z","abstract_excerpt":"Recent research works establish deep neural networks as high performing tools for radar target detection, especially on challenging environments (presence of clutter or interferences, multi-target scenarii...). However, the usually large computational complexity of these networks is one of the factors preventing them from being widely implemented in embedded radar systems. We propose to investigate novel neural architecture search (NAS) methods, based on Monte-Carlo Tree Search (MCTS), for finding neural networks achieving the required detection performance and striving towards a lower computa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.21772","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/2506.21772/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":"2026-07-05T11:28:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"50yFgq73VExrJFY3Z1Jfb2iGM/N6DeDayqaQMZqlM274Q/Sw6iDr+n6QHIHy08hUb6qN/Bl9YFYkShEVtumbAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T00:36:09.801653Z"},"content_sha256":"477cb785f54aac8fffeec57496cb8660939737294860c690e966f31d3abfd8bf","schema_version":"1.0","event_id":"sha256:477cb785f54aac8fffeec57496cb8660939737294860c690e966f31d3abfd8bf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/T4BG5XBLHYXXKN7XWMQ4LPOWNQ/bundle.json","state_url":"https://pith.science/pith/T4BG5XBLHYXXKN7XWMQ4LPOWNQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/T4BG5XBLHYXXKN7XWMQ4LPOWNQ/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":"2026-08-10T00:36:09Z","links":{"resolver":"https://pith.science/pith/T4BG5XBLHYXXKN7XWMQ4LPOWNQ","bundle":"https://pith.science/pith/T4BG5XBLHYXXKN7XWMQ4LPOWNQ/bundle.json","state":"https://pith.science/pith/T4BG5XBLHYXXKN7XWMQ4LPOWNQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/T4BG5XBLHYXXKN7XWMQ4LPOWNQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:T4BG5XBLHYXXKN7XWMQ4LPOWNQ","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":"9857a0c55dd4b5f76669505ae4fb279b82a8b815a1f9e672838fb0b2973439a8","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2025-06-11T09:58:33Z","title_canon_sha256":"90eb411c9de7e7f73b24221e7c1f20535bd07cf72d3019a1cf7471b186be19fa"},"schema_version":"1.0","source":{"id":"2506.21772","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.21772","created_at":"2026-07-05T11:28:00Z"},{"alias_kind":"arxiv_version","alias_value":"2506.21772v1","created_at":"2026-07-05T11:28:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.21772","created_at":"2026-07-05T11:28:00Z"},{"alias_kind":"pith_short_12","alias_value":"T4BG5XBLHYXX","created_at":"2026-07-05T11:28:00Z"},{"alias_kind":"pith_short_16","alias_value":"T4BG5XBLHYXXKN7X","created_at":"2026-07-05T11:28:00Z"},{"alias_kind":"pith_short_8","alias_value":"T4BG5XBL","created_at":"2026-07-05T11:28:00Z"}],"graph_snapshots":[{"event_id":"sha256:477cb785f54aac8fffeec57496cb8660939737294860c690e966f31d3abfd8bf","target":"graph","created_at":"2026-07-05T11:28:00Z","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/2506.21772/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent research works establish deep neural networks as high performing tools for radar target detection, especially on challenging environments (presence of clutter or interferences, multi-target scenarii...). However, the usually large computational complexity of these networks is one of the factors preventing them from being widely implemented in embedded radar systems. We propose to investigate novel neural architecture search (NAS) methods, based on Monte-Carlo Tree Search (MCTS), for finding neural networks achieving the required detection performance and striving towards a lower computa","authors_text":"Cyrille Enderli, No\\'e Lallouet, St\\'ephanie Gourdin, Tristan Cazenave","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2025-06-11T09:58:33Z","title":"Searching Efficient Deep Architectures for Radar Target Detection using Monte-Carlo Tree Search"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.21772","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:fbbee8e9b73e6f837e6facb91c254d504ec2dd061ba80b9b45e201dacdd85ed3","target":"record","created_at":"2026-07-05T11:28:00Z","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":"9857a0c55dd4b5f76669505ae4fb279b82a8b815a1f9e672838fb0b2973439a8","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2025-06-11T09:58:33Z","title_canon_sha256":"90eb411c9de7e7f73b24221e7c1f20535bd07cf72d3019a1cf7471b186be19fa"},"schema_version":"1.0","source":{"id":"2506.21772","kind":"arxiv","version":1}},"canonical_sha256":"9f026edc2b3e2f7537f7b321c5bdd66c3f2b5bbe7c361b55b4c73b82c46c8cd0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9f026edc2b3e2f7537f7b321c5bdd66c3f2b5bbe7c361b55b4c73b82c46c8cd0","first_computed_at":"2026-07-05T11:28:00.788981Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:28:00.788981Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pGRbIBM6WGPsKmB1FlB2w0yPNWA4Z13lTz0tWMTwMruJZSGmRks1/WmePZFXuDTqc2EzAGJdUg815di4o6UTBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:28:00.789549Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.21772","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fbbee8e9b73e6f837e6facb91c254d504ec2dd061ba80b9b45e201dacdd85ed3","sha256:477cb785f54aac8fffeec57496cb8660939737294860c690e966f31d3abfd8bf"],"state_sha256":"25958befd8da3e7d9224d0e80b6935114e690f2a32c8ecd43505a54ddca01c1e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WXzFYb2ieaAwXPG1Mj9asSVtVReCNhOq5SpiTOKtoambHr2DzxAKWvQX6wOFsZb01nY7fqNJf2qYi21BhnpaBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T00:36:09.806627Z","bundle_sha256":"48aab2ee6989425c03e26116441d4091c3c3d28e835c42586682445111ecd5a0"}}