{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:UVYTC2F7EJ6ZGTWZL2STJ4NJPU","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":"168ab946a80c5baf71a5f854ba25161151dfd81fb9e18384f70ea4454331de6d","cross_cats_sorted":["cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-04T00:02:16Z","title_canon_sha256":"39090c07453c625781ad06181e2cd8c2e9ede1e0614e7e9829d36b75d36c1b6a"},"schema_version":"1.0","source":{"id":"2502.01896","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.01896","created_at":"2026-07-05T10:09:20Z"},{"alias_kind":"arxiv_version","alias_value":"2502.01896v1","created_at":"2026-07-05T10:09:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.01896","created_at":"2026-07-05T10:09:20Z"},{"alias_kind":"pith_short_12","alias_value":"UVYTC2F7EJ6Z","created_at":"2026-07-05T10:09:20Z"},{"alias_kind":"pith_short_16","alias_value":"UVYTC2F7EJ6ZGTWZ","created_at":"2026-07-05T10:09:20Z"},{"alias_kind":"pith_short_8","alias_value":"UVYTC2F7","created_at":"2026-07-05T10:09:20Z"}],"graph_snapshots":[{"event_id":"sha256:c925e726a96fed4501323a462c02405e5fdec2b7069f3f8b4bd1c15396b3cebb","target":"graph","created_at":"2026-07-05T10:09:20Z","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/2502.01896/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this work, we present INTACT, a novel two-phase framework designed to enhance the robustness of deep neural networks (DNNs) against noisy LiDAR data in safety-critical perception tasks. INTACT combines meta-learning with adversarial curriculum training (ACT) to systematically address challenges posed by data corruption and sparsity in 3D point clouds. The meta-learning phase equips a teacher network with task-agnostic priors, enabling it to generate robust saliency maps that identify critical data regions. The ACT phase leverages these saliency maps to progressively expose a student network","authors_text":"Amit Ranjan Trivedi, Divake Kumar, Nastaran Darabi, Sina Tayebati","cross_cats":["cs.RO"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-04T00:02:16Z","title":"INTACT: Inducing Noise Tolerance through Adversarial Curriculum Training for LiDAR-based Safety-Critical Perception and Autonomy"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.01896","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":"sha256:1a3ff98c994af0b00f61003f149f85483b43ca4cc84472b1e4d1cf860a458086","target":"record","created_at":"2026-07-05T10:09:20Z","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":"168ab946a80c5baf71a5f854ba25161151dfd81fb9e18384f70ea4454331de6d","cross_cats_sorted":["cs.RO"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-04T00:02:16Z","title_canon_sha256":"39090c07453c625781ad06181e2cd8c2e9ede1e0614e7e9829d36b75d36c1b6a"},"schema_version":"1.0","source":{"id":"2502.01896","kind":"arxiv","version":1}},"canonical_sha256":"a5713168bf227d934ed95ea534f1a97d09953fa477d64eb9a6621d0450915ab9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a5713168bf227d934ed95ea534f1a97d09953fa477d64eb9a6621d0450915ab9","first_computed_at":"2026-07-05T10:09:20.812983Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:09:20.812983Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"s3hwquUiVqCNygWyWUFpbSBdGCKCwQSQ0dRtVUzgpPH1JGiqb9Ao4Et4OasCEXDpdZBYosf6jy8pZ8Lb625RBg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:09:20.813488Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.01896","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1a3ff98c994af0b00f61003f149f85483b43ca4cc84472b1e4d1cf860a458086","sha256:c925e726a96fed4501323a462c02405e5fdec2b7069f3f8b4bd1c15396b3cebb"],"state_sha256":"2825ae8ee7aa039c103c604f27034197d890c2532cc4c23a9e577bad6aa32bcc"}