{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:ZJFEHQS266DNKEKQ6KS4RRH6ZK","short_pith_number":"pith:ZJFEHQS2","canonical_record":{"source":{"id":"2002.10373","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2020-02-24T16:58:00Z","cross_cats_sorted":[],"title_canon_sha256":"e24ba9823736c97d5024b1677d0a9ac14d84072fe0aec8eec6974bca4216ca1b","abstract_canon_sha256":"a7fd76fffdbe9f35353bcc76b98e344ba187408a190b648a18d0c7597efe6c1e"},"schema_version":"1.0"},"canonical_sha256":"ca4a43c25af786d51150f2a5c8c4feca98fa5263a605db2780c5e3186bc357e6","source":{"kind":"arxiv","id":"2002.10373","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.10373","created_at":"2026-07-05T00:43:16Z"},{"alias_kind":"arxiv_version","alias_value":"2002.10373v1","created_at":"2026-07-05T00:43:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.10373","created_at":"2026-07-05T00:43:16Z"},{"alias_kind":"pith_short_12","alias_value":"ZJFEHQS266DN","created_at":"2026-07-05T00:43:16Z"},{"alias_kind":"pith_short_16","alias_value":"ZJFEHQS266DNKEKQ","created_at":"2026-07-05T00:43:16Z"},{"alias_kind":"pith_short_8","alias_value":"ZJFEHQS2","created_at":"2026-07-05T00:43:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:ZJFEHQS266DNKEKQ6KS4RRH6ZK","target":"record","payload":{"canonical_record":{"source":{"id":"2002.10373","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2020-02-24T16:58:00Z","cross_cats_sorted":[],"title_canon_sha256":"e24ba9823736c97d5024b1677d0a9ac14d84072fe0aec8eec6974bca4216ca1b","abstract_canon_sha256":"a7fd76fffdbe9f35353bcc76b98e344ba187408a190b648a18d0c7597efe6c1e"},"schema_version":"1.0"},"canonical_sha256":"ca4a43c25af786d51150f2a5c8c4feca98fa5263a605db2780c5e3186bc357e6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:43:16.905266Z","signature_b64":"SewWZWwj/tD/+LyaBEjz81spPcHh2YcN11kNb6kPprFhjBuygGN8tKTMeh441P9PgJlmNQajrwqAC9oKwQW5Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ca4a43c25af786d51150f2a5c8c4feca98fa5263a605db2780c5e3186bc357e6","last_reissued_at":"2026-07-05T00:43:16.904786Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:43:16.904786Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2002.10373","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":"2026-07-05T00:43:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TEPkZSY2kmujaKJe0ogmikX5bLW+mJNnPV6lt8ZDZeARiReET0EvRQj1kPOBmwOWkKrybfBCfDqV0l7KkiAqCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T03:05:13.049119Z"},"content_sha256":"ee7dd6e9831a2368407fe97adcb953d228d38fbefd8b1d7b8356548289213a5e","schema_version":"1.0","event_id":"sha256:ee7dd6e9831a2368407fe97adcb953d228d38fbefd8b1d7b8356548289213a5e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:ZJFEHQS266DNKEKQ6KS4RRH6ZK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Symbolic Learning and Reasoning with Noisy Data for Probabilistic Anchoring","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Amy Loutfi, Andreas Persson, Luc De Raedt, Nitesh Kumar, Pedro Zuidberg Dos Martires","submitted_at":"2020-02-24T16:58:00Z","abstract_excerpt":"Robotic agents should be able to learn from sub-symbolic sensor data, and at the same time, be able to reason about objects and communicate with humans on a symbolic level. This raises the question of how to overcome the gap between symbolic and sub-symbolic artificial intelligence. We propose a semantic world modeling approach based on bottom-up object anchoring using an object-centered representation of the world. Perceptual anchoring processes continuous perceptual sensor data and maintains a correspondence to a symbolic representation. We extend the definitions of anchoring to handle multi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.10373","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/2002.10373/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":"2026-07-05T00:43:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w0LYuG/VpDDTsvBJdjRlH9cPyi/eCTS8XmCdDSfy+0AOv5+4BU/1z8D1fAjeP+hwud5u+qw9G0TPngfxLfFRAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T03:05:13.049622Z"},"content_sha256":"0ff2c7afd74e13b07251575ef00293b688d94ff243d8ccf2ebba1ea9fb05ca6e","schema_version":"1.0","event_id":"sha256:0ff2c7afd74e13b07251575ef00293b688d94ff243d8ccf2ebba1ea9fb05ca6e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZJFEHQS266DNKEKQ6KS4RRH6ZK/bundle.json","state_url":"https://pith.science/pith/ZJFEHQS266DNKEKQ6KS4RRH6ZK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZJFEHQS266DNKEKQ6KS4RRH6ZK/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":"2026-08-18T03:05:13Z","links":{"resolver":"https://pith.science/pith/ZJFEHQS266DNKEKQ6KS4RRH6ZK","bundle":"https://pith.science/pith/ZJFEHQS266DNKEKQ6KS4RRH6ZK/bundle.json","state":"https://pith.science/pith/ZJFEHQS266DNKEKQ6KS4RRH6ZK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZJFEHQS266DNKEKQ6KS4RRH6ZK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:ZJFEHQS266DNKEKQ6KS4RRH6ZK","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":"a7fd76fffdbe9f35353bcc76b98e344ba187408a190b648a18d0c7597efe6c1e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2020-02-24T16:58:00Z","title_canon_sha256":"e24ba9823736c97d5024b1677d0a9ac14d84072fe0aec8eec6974bca4216ca1b"},"schema_version":"1.0","source":{"id":"2002.10373","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.10373","created_at":"2026-07-05T00:43:16Z"},{"alias_kind":"arxiv_version","alias_value":"2002.10373v1","created_at":"2026-07-05T00:43:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.10373","created_at":"2026-07-05T00:43:16Z"},{"alias_kind":"pith_short_12","alias_value":"ZJFEHQS266DN","created_at":"2026-07-05T00:43:16Z"},{"alias_kind":"pith_short_16","alias_value":"ZJFEHQS266DNKEKQ","created_at":"2026-07-05T00:43:16Z"},{"alias_kind":"pith_short_8","alias_value":"ZJFEHQS2","created_at":"2026-07-05T00:43:16Z"}],"graph_snapshots":[{"event_id":"sha256:0ff2c7afd74e13b07251575ef00293b688d94ff243d8ccf2ebba1ea9fb05ca6e","target":"graph","created_at":"2026-07-05T00:43:16Z","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/2002.10373/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Robotic agents should be able to learn from sub-symbolic sensor data, and at the same time, be able to reason about objects and communicate with humans on a symbolic level. This raises the question of how to overcome the gap between symbolic and sub-symbolic artificial intelligence. We propose a semantic world modeling approach based on bottom-up object anchoring using an object-centered representation of the world. Perceptual anchoring processes continuous perceptual sensor data and maintains a correspondence to a symbolic representation. We extend the definitions of anchoring to handle multi","authors_text":"Amy Loutfi, Andreas Persson, Luc De Raedt, Nitesh Kumar, Pedro Zuidberg Dos Martires","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2020-02-24T16:58:00Z","title":"Symbolic Learning and Reasoning with Noisy Data for Probabilistic Anchoring"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.10373","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:ee7dd6e9831a2368407fe97adcb953d228d38fbefd8b1d7b8356548289213a5e","target":"record","created_at":"2026-07-05T00:43:16Z","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":"a7fd76fffdbe9f35353bcc76b98e344ba187408a190b648a18d0c7597efe6c1e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2020-02-24T16:58:00Z","title_canon_sha256":"e24ba9823736c97d5024b1677d0a9ac14d84072fe0aec8eec6974bca4216ca1b"},"schema_version":"1.0","source":{"id":"2002.10373","kind":"arxiv","version":1}},"canonical_sha256":"ca4a43c25af786d51150f2a5c8c4feca98fa5263a605db2780c5e3186bc357e6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ca4a43c25af786d51150f2a5c8c4feca98fa5263a605db2780c5e3186bc357e6","first_computed_at":"2026-07-05T00:43:16.904786Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:43:16.904786Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SewWZWwj/tD/+LyaBEjz81spPcHh2YcN11kNb6kPprFhjBuygGN8tKTMeh441P9PgJlmNQajrwqAC9oKwQW5Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:43:16.905266Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.10373","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ee7dd6e9831a2368407fe97adcb953d228d38fbefd8b1d7b8356548289213a5e","sha256:0ff2c7afd74e13b07251575ef00293b688d94ff243d8ccf2ebba1ea9fb05ca6e"],"state_sha256":"c6ca590082c2b02631b4a310a17bf4b5790e04dccfc760a3d85fd9bb3417f8ea"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hHFJQyv4YGNr4u9bZDzenAUc3UDWn34SdngF8MeItlZkx5M3BldsECQbcMLxksiDVtoT8lWJZMngt5LJFIsOBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T03:05:13.054297Z","bundle_sha256":"7e4c70395b618af80a8d9043a26d7af0f33af49d969a46aea2bfe9a3e3beae3d"}}