{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:2EK3FOYI5RWXBTQ5SSK5MIZ4AV","short_pith_number":"pith:2EK3FOYI","canonical_record":{"source":{"id":"2203.02583","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-04T21:44:43Z","cross_cats_sorted":[],"title_canon_sha256":"31685e29bf0ea747631a0486a8b73efdf25804b1b5e71f0deb160b3420c8bd90","abstract_canon_sha256":"93af9bf9cf42ea4af839f83e50e16fab685de4ed87a51efea56361c8f4dca1a3"},"schema_version":"1.0"},"canonical_sha256":"d115b2bb08ec6d70ce1d9495d6233c056f974d6f2b91212252103c5f6f493110","source":{"kind":"arxiv","id":"2203.02583","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.02583","created_at":"2026-07-05T04:02:24Z"},{"alias_kind":"arxiv_version","alias_value":"2203.02583v1","created_at":"2026-07-05T04:02:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.02583","created_at":"2026-07-05T04:02:24Z"},{"alias_kind":"pith_short_12","alias_value":"2EK3FOYI5RWX","created_at":"2026-07-05T04:02:24Z"},{"alias_kind":"pith_short_16","alias_value":"2EK3FOYI5RWXBTQ5","created_at":"2026-07-05T04:02:24Z"},{"alias_kind":"pith_short_8","alias_value":"2EK3FOYI","created_at":"2026-07-05T04:02:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:2EK3FOYI5RWXBTQ5SSK5MIZ4AV","target":"record","payload":{"canonical_record":{"source":{"id":"2203.02583","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-04T21:44:43Z","cross_cats_sorted":[],"title_canon_sha256":"31685e29bf0ea747631a0486a8b73efdf25804b1b5e71f0deb160b3420c8bd90","abstract_canon_sha256":"93af9bf9cf42ea4af839f83e50e16fab685de4ed87a51efea56361c8f4dca1a3"},"schema_version":"1.0"},"canonical_sha256":"d115b2bb08ec6d70ce1d9495d6233c056f974d6f2b91212252103c5f6f493110","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:02:24.807486Z","signature_b64":"XFBSeuGksXCUGa6X7Ofn0BpYHbTc7bFHoQRP7G2EU+eRuSxQM5pwAtIsWOpbDTtcrk5qXIZDix9rSjkde5K2Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d115b2bb08ec6d70ce1d9495d6233c056f974d6f2b91212252103c5f6f493110","last_reissued_at":"2026-07-05T04:02:24.807003Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:02:24.807003Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.02583","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":"2026-07-05T04:02:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cK2G9gO5cg7NUHfHwA/fn/U9/2wTbyMsx03UOwdZoL2T1OqLPHiH572zQVfWUug7N1ASp6FXJOeRzz5dqBycCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T19:14:25.720273Z"},"content_sha256":"f9c0ff6d1a5920722db75c1d66161c6bf697ab42ecf8b45c27ef1e436c45ea44","schema_version":"1.0","event_id":"sha256:f9c0ff6d1a5920722db75c1d66161c6bf697ab42ecf8b45c27ef1e436c45ea44"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:2EK3FOYI5RWXBTQ5SSK5MIZ4AV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Online Learning of Reusable Abstract Models for Object Goal Navigation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Lamberto Ballan, Leonardo Lamanna, Luciano Serafini, Paolo Traverso, Tommaso Campari","submitted_at":"2022-03-04T21:44:43Z","abstract_excerpt":"In this paper, we present a novel approach to incrementally learn an Abstract Model of an unknown environment, and show how an agent can reuse the learned model for tackling the Object Goal Navigation task. The Abstract Model is a finite state machine in which each state is an abstraction of a state of the environment, as perceived by the agent in a certain position and orientation. The perceptions are high-dimensional sensory data (e.g., RGB-D images), and the abstraction is reached by exploiting image segmentation and the Taskonomy model bank. The learning of the Abstract Model is accomplish"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.02583","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/2203.02583/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":"2026-07-05T04:02:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dTo43ZZk3jYUFZS8cxS6k/efbFET2fb/I1M9YG18pdCvTVdt5PrQYaT33AyA84I7Q6nF4flE6EPDBjiB53LDAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T19:14:25.720858Z"},"content_sha256":"b10926735209dfae4ca339794222b44fce69fea6882942dc4e601f7e681b3265","schema_version":"1.0","event_id":"sha256:b10926735209dfae4ca339794222b44fce69fea6882942dc4e601f7e681b3265"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2EK3FOYI5RWXBTQ5SSK5MIZ4AV/bundle.json","state_url":"https://pith.science/pith/2EK3FOYI5RWXBTQ5SSK5MIZ4AV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2EK3FOYI5RWXBTQ5SSK5MIZ4AV/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":"2026-08-23T19:14:25Z","links":{"resolver":"https://pith.science/pith/2EK3FOYI5RWXBTQ5SSK5MIZ4AV","bundle":"https://pith.science/pith/2EK3FOYI5RWXBTQ5SSK5MIZ4AV/bundle.json","state":"https://pith.science/pith/2EK3FOYI5RWXBTQ5SSK5MIZ4AV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2EK3FOYI5RWXBTQ5SSK5MIZ4AV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:2EK3FOYI5RWXBTQ5SSK5MIZ4AV","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":"93af9bf9cf42ea4af839f83e50e16fab685de4ed87a51efea56361c8f4dca1a3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-04T21:44:43Z","title_canon_sha256":"31685e29bf0ea747631a0486a8b73efdf25804b1b5e71f0deb160b3420c8bd90"},"schema_version":"1.0","source":{"id":"2203.02583","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.02583","created_at":"2026-07-05T04:02:24Z"},{"alias_kind":"arxiv_version","alias_value":"2203.02583v1","created_at":"2026-07-05T04:02:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.02583","created_at":"2026-07-05T04:02:24Z"},{"alias_kind":"pith_short_12","alias_value":"2EK3FOYI5RWX","created_at":"2026-07-05T04:02:24Z"},{"alias_kind":"pith_short_16","alias_value":"2EK3FOYI5RWXBTQ5","created_at":"2026-07-05T04:02:24Z"},{"alias_kind":"pith_short_8","alias_value":"2EK3FOYI","created_at":"2026-07-05T04:02:24Z"}],"graph_snapshots":[{"event_id":"sha256:b10926735209dfae4ca339794222b44fce69fea6882942dc4e601f7e681b3265","target":"graph","created_at":"2026-07-05T04:02:24Z","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/2203.02583/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we present a novel approach to incrementally learn an Abstract Model of an unknown environment, and show how an agent can reuse the learned model for tackling the Object Goal Navigation task. The Abstract Model is a finite state machine in which each state is an abstraction of a state of the environment, as perceived by the agent in a certain position and orientation. The perceptions are high-dimensional sensory data (e.g., RGB-D images), and the abstraction is reached by exploiting image segmentation and the Taskonomy model bank. The learning of the Abstract Model is accomplish","authors_text":"Lamberto Ballan, Leonardo Lamanna, Luciano Serafini, Paolo Traverso, Tommaso Campari","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-04T21:44:43Z","title":"Online Learning of Reusable Abstract Models for Object Goal Navigation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.02583","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:f9c0ff6d1a5920722db75c1d66161c6bf697ab42ecf8b45c27ef1e436c45ea44","target":"record","created_at":"2026-07-05T04:02:24Z","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":"93af9bf9cf42ea4af839f83e50e16fab685de4ed87a51efea56361c8f4dca1a3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-04T21:44:43Z","title_canon_sha256":"31685e29bf0ea747631a0486a8b73efdf25804b1b5e71f0deb160b3420c8bd90"},"schema_version":"1.0","source":{"id":"2203.02583","kind":"arxiv","version":1}},"canonical_sha256":"d115b2bb08ec6d70ce1d9495d6233c056f974d6f2b91212252103c5f6f493110","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d115b2bb08ec6d70ce1d9495d6233c056f974d6f2b91212252103c5f6f493110","first_computed_at":"2026-07-05T04:02:24.807003Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:02:24.807003Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XFBSeuGksXCUGa6X7Ofn0BpYHbTc7bFHoQRP7G2EU+eRuSxQM5pwAtIsWOpbDTtcrk5qXIZDix9rSjkde5K2Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:02:24.807486Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.02583","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f9c0ff6d1a5920722db75c1d66161c6bf697ab42ecf8b45c27ef1e436c45ea44","sha256:b10926735209dfae4ca339794222b44fce69fea6882942dc4e601f7e681b3265"],"state_sha256":"a208c738ddc9c1c7d43d87de187b2b31e3f143aac93ade2bb879476ca50d46c5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sge6duvxI6M5XArzetqCE1prePLyqaQ7l5PYc/LsYX5/uOg9YjNkdOFmw/Tk1ucerLE54+DIbzMg/iUx6heIAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T19:14:25.725794Z","bundle_sha256":"06835545c44cb4ad275324196a5de92188e47ce159a1f3ff5ff673047e3d52fa"}}