{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:4JZN4GBZMMOD4ALIGGB2ERFMFK","short_pith_number":"pith:4JZN4GBZ","canonical_record":{"source":{"id":"2408.02297","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-08-05T08:14:28Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"5ec57b32cc532b605b7a57889f515d4d2cbcbb5edc74595f6d4f4b6a360b5ce5","abstract_canon_sha256":"13dab3b1015e4bd53be6cfe8f05e220445e1f6fc57ba114b57baa4dc2456f518"},"schema_version":"1.0"},"canonical_sha256":"e272de1839631c3e01683183a244ac2ab97bfb21ed43339871f012592b16d6ce","source":{"kind":"arxiv","id":"2408.02297","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.02297","created_at":"2026-07-05T10:00:39Z"},{"alias_kind":"arxiv_version","alias_value":"2408.02297v2","created_at":"2026-07-05T10:00:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.02297","created_at":"2026-07-05T10:00:39Z"},{"alias_kind":"pith_short_12","alias_value":"4JZN4GBZMMOD","created_at":"2026-07-05T10:00:39Z"},{"alias_kind":"pith_short_16","alias_value":"4JZN4GBZMMOD4ALI","created_at":"2026-07-05T10:00:39Z"},{"alias_kind":"pith_short_8","alias_value":"4JZN4GBZ","created_at":"2026-07-05T10:00:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:4JZN4GBZMMOD4ALIGGB2ERFMFK","target":"record","payload":{"canonical_record":{"source":{"id":"2408.02297","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-08-05T08:14:28Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"5ec57b32cc532b605b7a57889f515d4d2cbcbb5edc74595f6d4f4b6a360b5ce5","abstract_canon_sha256":"13dab3b1015e4bd53be6cfe8f05e220445e1f6fc57ba114b57baa4dc2456f518"},"schema_version":"1.0"},"canonical_sha256":"e272de1839631c3e01683183a244ac2ab97bfb21ed43339871f012592b16d6ce","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:00:39.727342Z","signature_b64":"CyFqxY09L6DTi59W/qwvKAUmbvhbcxmoRuDwrMv6fEnzDIHGIKUfJ2Uc968yGrGrZ3oFWGHtIJ/PL7y0DCSeBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e272de1839631c3e01683183a244ac2ab97bfb21ed43339871f012592b16d6ce","last_reissued_at":"2026-07-05T10:00:39.726832Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:00:39.726832Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.02297","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:00:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6lqqDsAh4RGwHNTMqKFt7mVd39flKAqCBZqq+V2mvnsB1CUZaxhYO8Lk4BwxBWEe88rfmrhxjEuvFUlNVrAUCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T18:19:34.947665Z"},"content_sha256":"192dbbbe57f1f6afc69449161eb5526bdce365f221f925836ada1c0568f1293b","schema_version":"1.0","event_id":"sha256:192dbbbe57f1f6afc69449161eb5526bdce365f221f925836ada1c0568f1293b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:4JZN4GBZMMOD4ALIGGB2ERFMFK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Perception Matters: Enhancing Embodied AI with Uncertainty-Aware Semantic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Abhinav Valada, Daniel Honerkamp, Kshitij Sirohi, Sai Prasanna, Tim Welschehold, Wolfram Burgard","submitted_at":"2024-08-05T08:14:28Z","abstract_excerpt":"Embodied AI has made significant progress acting in unexplored environments. However, tasks such as object search have largely focused on efficient policy learning. In this work, we identify several gaps in current search methods: They largely focus on dated perception models, neglect temporal aggregation, and transfer from ground truth directly to noisy perception at test time, without accounting for the resulting overconfidence in the perceived state. We address the identified problems through calibrated perception probabilities and uncertainty across aggregation and found decisions, thereby"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.02297","kind":"arxiv","version":2},"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/2408.02297/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":"2026-07-05T10:00:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kO2BAvjdMuaaKl9uUkZge4MUakYYLEJDovSEO8bY14mYnHQzFxLu+9+Mg4WmgGnCQC6gL4WE/2RYwzZ95KyBAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T18:19:34.948413Z"},"content_sha256":"bd00267d0c94e3f45b09a6b92412434a8c17174c82efb4a455d93a2ce9866857","schema_version":"1.0","event_id":"sha256:bd00267d0c94e3f45b09a6b92412434a8c17174c82efb4a455d93a2ce9866857"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4JZN4GBZMMOD4ALIGGB2ERFMFK/bundle.json","state_url":"https://pith.science/pith/4JZN4GBZMMOD4ALIGGB2ERFMFK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4JZN4GBZMMOD4ALIGGB2ERFMFK/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":"2026-08-10T18:19:34Z","links":{"resolver":"https://pith.science/pith/4JZN4GBZMMOD4ALIGGB2ERFMFK","bundle":"https://pith.science/pith/4JZN4GBZMMOD4ALIGGB2ERFMFK/bundle.json","state":"https://pith.science/pith/4JZN4GBZMMOD4ALIGGB2ERFMFK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4JZN4GBZMMOD4ALIGGB2ERFMFK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4JZN4GBZMMOD4ALIGGB2ERFMFK","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":"13dab3b1015e4bd53be6cfe8f05e220445e1f6fc57ba114b57baa4dc2456f518","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-08-05T08:14:28Z","title_canon_sha256":"5ec57b32cc532b605b7a57889f515d4d2cbcbb5edc74595f6d4f4b6a360b5ce5"},"schema_version":"1.0","source":{"id":"2408.02297","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.02297","created_at":"2026-07-05T10:00:39Z"},{"alias_kind":"arxiv_version","alias_value":"2408.02297v2","created_at":"2026-07-05T10:00:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.02297","created_at":"2026-07-05T10:00:39Z"},{"alias_kind":"pith_short_12","alias_value":"4JZN4GBZMMOD","created_at":"2026-07-05T10:00:39Z"},{"alias_kind":"pith_short_16","alias_value":"4JZN4GBZMMOD4ALI","created_at":"2026-07-05T10:00:39Z"},{"alias_kind":"pith_short_8","alias_value":"4JZN4GBZ","created_at":"2026-07-05T10:00:39Z"}],"graph_snapshots":[{"event_id":"sha256:bd00267d0c94e3f45b09a6b92412434a8c17174c82efb4a455d93a2ce9866857","target":"graph","created_at":"2026-07-05T10:00:39Z","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/2408.02297/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Embodied AI has made significant progress acting in unexplored environments. However, tasks such as object search have largely focused on efficient policy learning. In this work, we identify several gaps in current search methods: They largely focus on dated perception models, neglect temporal aggregation, and transfer from ground truth directly to noisy perception at test time, without accounting for the resulting overconfidence in the perceived state. We address the identified problems through calibrated perception probabilities and uncertainty across aggregation and found decisions, thereby","authors_text":"Abhinav Valada, Daniel Honerkamp, Kshitij Sirohi, Sai Prasanna, Tim Welschehold, Wolfram Burgard","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-08-05T08:14:28Z","title":"Perception Matters: Enhancing Embodied AI with Uncertainty-Aware Semantic Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.02297","kind":"arxiv","version":2},"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":"sha256:192dbbbe57f1f6afc69449161eb5526bdce365f221f925836ada1c0568f1293b","target":"record","created_at":"2026-07-05T10:00:39Z","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":"13dab3b1015e4bd53be6cfe8f05e220445e1f6fc57ba114b57baa4dc2456f518","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-08-05T08:14:28Z","title_canon_sha256":"5ec57b32cc532b605b7a57889f515d4d2cbcbb5edc74595f6d4f4b6a360b5ce5"},"schema_version":"1.0","source":{"id":"2408.02297","kind":"arxiv","version":2}},"canonical_sha256":"e272de1839631c3e01683183a244ac2ab97bfb21ed43339871f012592b16d6ce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e272de1839631c3e01683183a244ac2ab97bfb21ed43339871f012592b16d6ce","first_computed_at":"2026-07-05T10:00:39.726832Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:00:39.726832Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CyFqxY09L6DTi59W/qwvKAUmbvhbcxmoRuDwrMv6fEnzDIHGIKUfJ2Uc968yGrGrZ3oFWGHtIJ/PL7y0DCSeBg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:00:39.727342Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.02297","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:192dbbbe57f1f6afc69449161eb5526bdce365f221f925836ada1c0568f1293b","sha256:bd00267d0c94e3f45b09a6b92412434a8c17174c82efb4a455d93a2ce9866857"],"state_sha256":"e4567b27e380ad3d9741eda129a46cb7c02e563bc4f9135ed4900cbdadea4715"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"J6X/W8IloWiYOqrHV+97ir5yysp4f7iIugHW7yT2t8XOTiw2NqEvGjspJzvdpPfKs8RhltMR6t8Y4Z3oYa2oDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T18:19:34.954217Z","bundle_sha256":"f4f296451b0775afccc5175f63d06d76b878afa42dff0881bd25232bb05d7b91"}}