{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:CD3WFUCXM7BLTNYWJQLKL3NOOG","short_pith_number":"pith:CD3WFUCX","canonical_record":{"source":{"id":"1410.3748","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-10-14T16:11:43Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b922d7846fbdcbb98e19ce4ad22766a8817085ff86ac054e4295c2eacf70da08","abstract_canon_sha256":"e58bfd9a6022cf5b8a5195086d9cc9160feaca43e53a779333a8a9d1bcc7ccda"},"schema_version":"1.0"},"canonical_sha256":"10f762d05767c2b9b7164c16a5edae71887badf1e232116a1dc8ef4ee8178bf1","source":{"kind":"arxiv","id":"1410.3748","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1410.3748","created_at":"2026-05-18T02:40:04Z"},{"alias_kind":"arxiv_version","alias_value":"1410.3748v1","created_at":"2026-05-18T02:40:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1410.3748","created_at":"2026-05-18T02:40:04Z"},{"alias_kind":"pith_short_12","alias_value":"CD3WFUCXM7BL","created_at":"2026-05-18T12:28:22Z"},{"alias_kind":"pith_short_16","alias_value":"CD3WFUCXM7BLTNYW","created_at":"2026-05-18T12:28:22Z"},{"alias_kind":"pith_short_8","alias_value":"CD3WFUCX","created_at":"2026-05-18T12:28:22Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:CD3WFUCXM7BLTNYWJQLKL3NOOG","target":"record","payload":{"canonical_record":{"source":{"id":"1410.3748","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-10-14T16:11:43Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b922d7846fbdcbb98e19ce4ad22766a8817085ff86ac054e4295c2eacf70da08","abstract_canon_sha256":"e58bfd9a6022cf5b8a5195086d9cc9160feaca43e53a779333a8a9d1bcc7ccda"},"schema_version":"1.0"},"canonical_sha256":"10f762d05767c2b9b7164c16a5edae71887badf1e232116a1dc8ef4ee8178bf1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:40:04.331994Z","signature_b64":"Y9t+oZmJZIKKF/miBPUCIaWe8XeIKIIzFsqOr7Ujm2hupmOdhwgBKOTtvTMHfPU4HkqJ0bIEjJ2mDyfcGQupBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"10f762d05767c2b9b7164c16a5edae71887badf1e232116a1dc8ef4ee8178bf1","last_reissued_at":"2026-05-18T02:40:04.331592Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:40:04.331592Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1410.3748","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":"2026-05-18T02:40:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aOTYoA0dhaoW3clgcy/jzkTkfdmQKSKRFfVTnT4IHPxyu9bhHaFIU8ZCSO5Qmf5i4emSgi1CtFN/UhJPWxNPDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T09:22:46.737880Z"},"content_sha256":"af2cf5ec99cb627b6267250ff21daef73b562dac301126e24b547b69345c17ef","schema_version":"1.0","event_id":"sha256:af2cf5ec99cb627b6267250ff21daef73b562dac301126e24b547b69345c17ef"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:CD3WFUCXM7BLTNYWJQLKL3NOOG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Zero-Shot Object Recognition System based on Topic Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.CV","authors_text":"Chee Seng Chan, Wai Lam Hoo","submitted_at":"2014-10-14T16:11:43Z","abstract_excerpt":"Object recognition systems usually require fully complete manually labeled training data to train the classifier. In this paper, we study the problem of object recognition where the training samples are missing during the classifier learning stage, a task also known as zero-shot learning. We propose a novel zero-shot learning strategy that utilizes the topic model and hierarchical class concept. Our proposed method advanced where cumbersome human annotation stage (i.e. attribute-based classification) is eliminated. We achieve comparable performance with state-of-the-art algorithms in four publ"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1410.3748","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":""},"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":"2026-05-18T02:40:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"03H7VplcqU1XWeCC0GMnBqDNFyXKwSIRDC68gJyNPGYMbHeUW5enh6u0pckPEDAoArwB/UQPgC4W5bqaVOQ5Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T09:22:46.738621Z"},"content_sha256":"592c8c0e8dd8ec53373b8641e3b0c4d09adb4df5a5f2d6b0255c92dd5c89b8fa","schema_version":"1.0","event_id":"sha256:592c8c0e8dd8ec53373b8641e3b0c4d09adb4df5a5f2d6b0255c92dd5c89b8fa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CD3WFUCXM7BLTNYWJQLKL3NOOG/bundle.json","state_url":"https://pith.science/pith/CD3WFUCXM7BLTNYWJQLKL3NOOG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CD3WFUCXM7BLTNYWJQLKL3NOOG/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":"2026-05-23T09:22:46Z","links":{"resolver":"https://pith.science/pith/CD3WFUCXM7BLTNYWJQLKL3NOOG","bundle":"https://pith.science/pith/CD3WFUCXM7BLTNYWJQLKL3NOOG/bundle.json","state":"https://pith.science/pith/CD3WFUCXM7BLTNYWJQLKL3NOOG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CD3WFUCXM7BLTNYWJQLKL3NOOG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:CD3WFUCXM7BLTNYWJQLKL3NOOG","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":"e58bfd9a6022cf5b8a5195086d9cc9160feaca43e53a779333a8a9d1bcc7ccda","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-10-14T16:11:43Z","title_canon_sha256":"b922d7846fbdcbb98e19ce4ad22766a8817085ff86ac054e4295c2eacf70da08"},"schema_version":"1.0","source":{"id":"1410.3748","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1410.3748","created_at":"2026-05-18T02:40:04Z"},{"alias_kind":"arxiv_version","alias_value":"1410.3748v1","created_at":"2026-05-18T02:40:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1410.3748","created_at":"2026-05-18T02:40:04Z"},{"alias_kind":"pith_short_12","alias_value":"CD3WFUCXM7BL","created_at":"2026-05-18T12:28:22Z"},{"alias_kind":"pith_short_16","alias_value":"CD3WFUCXM7BLTNYW","created_at":"2026-05-18T12:28:22Z"},{"alias_kind":"pith_short_8","alias_value":"CD3WFUCX","created_at":"2026-05-18T12:28:22Z"}],"graph_snapshots":[{"event_id":"sha256:592c8c0e8dd8ec53373b8641e3b0c4d09adb4df5a5f2d6b0255c92dd5c89b8fa","target":"graph","created_at":"2026-05-18T02:40:04Z","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":"Object recognition systems usually require fully complete manually labeled training data to train the classifier. In this paper, we study the problem of object recognition where the training samples are missing during the classifier learning stage, a task also known as zero-shot learning. We propose a novel zero-shot learning strategy that utilizes the topic model and hierarchical class concept. Our proposed method advanced where cumbersome human annotation stage (i.e. attribute-based classification) is eliminated. We achieve comparable performance with state-of-the-art algorithms in four publ","authors_text":"Chee Seng Chan, Wai Lam Hoo","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-10-14T16:11:43Z","title":"Zero-Shot Object Recognition System based on Topic Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1410.3748","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:af2cf5ec99cb627b6267250ff21daef73b562dac301126e24b547b69345c17ef","target":"record","created_at":"2026-05-18T02:40:04Z","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":"e58bfd9a6022cf5b8a5195086d9cc9160feaca43e53a779333a8a9d1bcc7ccda","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2014-10-14T16:11:43Z","title_canon_sha256":"b922d7846fbdcbb98e19ce4ad22766a8817085ff86ac054e4295c2eacf70da08"},"schema_version":"1.0","source":{"id":"1410.3748","kind":"arxiv","version":1}},"canonical_sha256":"10f762d05767c2b9b7164c16a5edae71887badf1e232116a1dc8ef4ee8178bf1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"10f762d05767c2b9b7164c16a5edae71887badf1e232116a1dc8ef4ee8178bf1","first_computed_at":"2026-05-18T02:40:04.331592Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:40:04.331592Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Y9t+oZmJZIKKF/miBPUCIaWe8XeIKIIzFsqOr7Ujm2hupmOdhwgBKOTtvTMHfPU4HkqJ0bIEjJ2mDyfcGQupBg==","signature_status":"signed_v1","signed_at":"2026-05-18T02:40:04.331994Z","signed_message":"canonical_sha256_bytes"},"source_id":"1410.3748","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:af2cf5ec99cb627b6267250ff21daef73b562dac301126e24b547b69345c17ef","sha256:592c8c0e8dd8ec53373b8641e3b0c4d09adb4df5a5f2d6b0255c92dd5c89b8fa"],"state_sha256":"853ef3a4654fec049e52320b5b6d160570aac13500ea7014ff716bcfeae9dacc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cyD3ZcOLyrDPajMJMhPj21a0/u38z3XHWtAZ6MNP/aF1podq8F7l3CuCxbN0HuB9/jZ3WIZOiF5/TBDyRrJXDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T09:22:46.742348Z","bundle_sha256":"e89de1fafc9b4784cc73e7c5362e31c746295bdc4c63fafba2e2886119f9b41a"}}