{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:IWCSRBJ4XQ4PUNIXIFLESRGKSU","short_pith_number":"pith:IWCSRBJ4","canonical_record":{"source":{"id":"1808.01102","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-03T07:31:01Z","cross_cats_sorted":[],"title_canon_sha256":"f971a1787115507ac116304bd81047fa64a30ec2cbe0ead45e0f0ffae1b3ba19","abstract_canon_sha256":"8dfb92358304814bd54607619ff9fe15e79584de18658cd147643eb361b720b2"},"schema_version":"1.0"},"canonical_sha256":"458528853cbc38fa351741564944ca953c489b13f82f1432ca9726217eab6b9b","source":{"kind":"arxiv","id":"1808.01102","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.01102","created_at":"2026-05-17T23:40:55Z"},{"alias_kind":"arxiv_version","alias_value":"1808.01102v2","created_at":"2026-05-17T23:40:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.01102","created_at":"2026-05-17T23:40:55Z"},{"alias_kind":"pith_short_12","alias_value":"IWCSRBJ4XQ4P","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_16","alias_value":"IWCSRBJ4XQ4PUNIX","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_8","alias_value":"IWCSRBJ4","created_at":"2026-05-18T12:32:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:IWCSRBJ4XQ4PUNIXIFLESRGKSU","target":"record","payload":{"canonical_record":{"source":{"id":"1808.01102","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-03T07:31:01Z","cross_cats_sorted":[],"title_canon_sha256":"f971a1787115507ac116304bd81047fa64a30ec2cbe0ead45e0f0ffae1b3ba19","abstract_canon_sha256":"8dfb92358304814bd54607619ff9fe15e79584de18658cd147643eb361b720b2"},"schema_version":"1.0"},"canonical_sha256":"458528853cbc38fa351741564944ca953c489b13f82f1432ca9726217eab6b9b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:55.959197Z","signature_b64":"ByoP9L2bHBL4LDHDVUkNN5Sq1LjV2kJ8lKYOiJ0DMmEgWAAU7QnSp7v4SUmjZ1r2fgHwYMcIoYemKT6Kc+wyDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"458528853cbc38fa351741564944ca953c489b13f82f1432ca9726217eab6b9b","last_reissued_at":"2026-05-17T23:40:55.958616Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:55.958616Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1808.01102","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":"2026-05-17T23:40:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sk1Dn7oLuMAxLllQZLgdxqXMADmb6yZzL+wZO9y97vKRCCw+wD2JzdcCt/LD1gEaFZpUqfpTxikb358nEjodDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-02T21:44:45.930908Z"},"content_sha256":"8fc06219cc1a9d9da9dc877fec9c05cf8969568aa518ed1f4de303b6bf6915aa","schema_version":"1.0","event_id":"sha256:8fc06219cc1a9d9da9dc877fec9c05cf8969568aa518ed1f4de303b6bf6915aa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:IWCSRBJ4XQ4PUNIXIFLESRGKSU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Hallucinating Agnostic Images to Generalize Across Domains","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Barbara Caputo, Fabio M. Carlucci, Paolo Russo, Tatiana Tommasi","submitted_at":"2018-08-03T07:31:01Z","abstract_excerpt":"The ability to generalize across visual domains is crucial for the robustness of artificial recognition systems. Although many training sources may be available in real contexts, the access to even unlabeled target samples cannot be taken for granted, which makes standard unsupervised domain adaptation methods inapplicable in the wild. In this work we investigate how to exploit multiple sources by hallucinating a deep visual domain composed of images, possibly unrealistic, able to maintain categorical knowledge while discarding specific source styles. The produced agnostic images are the resul"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.01102","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":""},"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":"2026-05-17T23:40:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e98FS48g5XIFfcPJPNj/zKggVz7TYhF3H6wNzHBXKwFne4CGlolOcFsv43ULXhglzAd430vc8t5lVBsbkG5mCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-02T21:44:45.931260Z"},"content_sha256":"dddc1be0c43fb543f492083b78adc5ee41731301a0a4478e9f7dc0656d1a8572","schema_version":"1.0","event_id":"sha256:dddc1be0c43fb543f492083b78adc5ee41731301a0a4478e9f7dc0656d1a8572"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IWCSRBJ4XQ4PUNIXIFLESRGKSU/bundle.json","state_url":"https://pith.science/pith/IWCSRBJ4XQ4PUNIXIFLESRGKSU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IWCSRBJ4XQ4PUNIXIFLESRGKSU/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":"2026-07-02T21:44:45Z","links":{"resolver":"https://pith.science/pith/IWCSRBJ4XQ4PUNIXIFLESRGKSU","bundle":"https://pith.science/pith/IWCSRBJ4XQ4PUNIXIFLESRGKSU/bundle.json","state":"https://pith.science/pith/IWCSRBJ4XQ4PUNIXIFLESRGKSU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IWCSRBJ4XQ4PUNIXIFLESRGKSU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:IWCSRBJ4XQ4PUNIXIFLESRGKSU","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":"8dfb92358304814bd54607619ff9fe15e79584de18658cd147643eb361b720b2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-03T07:31:01Z","title_canon_sha256":"f971a1787115507ac116304bd81047fa64a30ec2cbe0ead45e0f0ffae1b3ba19"},"schema_version":"1.0","source":{"id":"1808.01102","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1808.01102","created_at":"2026-05-17T23:40:55Z"},{"alias_kind":"arxiv_version","alias_value":"1808.01102v2","created_at":"2026-05-17T23:40:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1808.01102","created_at":"2026-05-17T23:40:55Z"},{"alias_kind":"pith_short_12","alias_value":"IWCSRBJ4XQ4P","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_16","alias_value":"IWCSRBJ4XQ4PUNIX","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_8","alias_value":"IWCSRBJ4","created_at":"2026-05-18T12:32:31Z"}],"graph_snapshots":[{"event_id":"sha256:dddc1be0c43fb543f492083b78adc5ee41731301a0a4478e9f7dc0656d1a8572","target":"graph","created_at":"2026-05-17T23:40:55Z","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"},"paper":{"abstract_excerpt":"The ability to generalize across visual domains is crucial for the robustness of artificial recognition systems. Although many training sources may be available in real contexts, the access to even unlabeled target samples cannot be taken for granted, which makes standard unsupervised domain adaptation methods inapplicable in the wild. In this work we investigate how to exploit multiple sources by hallucinating a deep visual domain composed of images, possibly unrealistic, able to maintain categorical knowledge while discarding specific source styles. The produced agnostic images are the resul","authors_text":"Barbara Caputo, Fabio M. Carlucci, Paolo Russo, Tatiana Tommasi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-03T07:31:01Z","title":"Hallucinating Agnostic Images to Generalize Across Domains"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1808.01102","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":"sha256:8fc06219cc1a9d9da9dc877fec9c05cf8969568aa518ed1f4de303b6bf6915aa","target":"record","created_at":"2026-05-17T23:40:55Z","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":"8dfb92358304814bd54607619ff9fe15e79584de18658cd147643eb361b720b2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-08-03T07:31:01Z","title_canon_sha256":"f971a1787115507ac116304bd81047fa64a30ec2cbe0ead45e0f0ffae1b3ba19"},"schema_version":"1.0","source":{"id":"1808.01102","kind":"arxiv","version":2}},"canonical_sha256":"458528853cbc38fa351741564944ca953c489b13f82f1432ca9726217eab6b9b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"458528853cbc38fa351741564944ca953c489b13f82f1432ca9726217eab6b9b","first_computed_at":"2026-05-17T23:40:55.958616Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:40:55.958616Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ByoP9L2bHBL4LDHDVUkNN5Sq1LjV2kJ8lKYOiJ0DMmEgWAAU7QnSp7v4SUmjZ1r2fgHwYMcIoYemKT6Kc+wyDQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:40:55.959197Z","signed_message":"canonical_sha256_bytes"},"source_id":"1808.01102","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8fc06219cc1a9d9da9dc877fec9c05cf8969568aa518ed1f4de303b6bf6915aa","sha256:dddc1be0c43fb543f492083b78adc5ee41731301a0a4478e9f7dc0656d1a8572"],"state_sha256":"5cd51ee7c992d100d9f40b8038be711cb30ad7c668b1d067899914ec15631c67"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c7l82p5DEz1gylQiZD2oqt287nZ2sNjqffNJ2mA2nL3PUr/BFb3AMDsfdxlXAPrYiFudRmygxADL2FN2e8nyCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-02T21:44:45.933205Z","bundle_sha256":"b0682a9549aff00fcde962a74b8f3efbb427a728cca01fff88d9178f83ced1b0"}}