{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:ZIM3EYK3I6WDLHS33WUIYMIIDE","short_pith_number":"pith:ZIM3EYK3","canonical_record":{"source":{"id":"1712.03878","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-11T16:44:12Z","cross_cats_sorted":["cs.CV","stat.ML"],"title_canon_sha256":"b50320378defc7588810f33eeaba1534f433b819f5ca54c33d390210b8e18a98","abstract_canon_sha256":"977b560143a51db487ef752797985a4e13f5608a1ee3eb2dd586fad82a791ec4"},"schema_version":"1.0"},"canonical_sha256":"ca19b2615b47ac359e5bdda88c31081924e8f0e7076cdfde529ba1712b69fef7","source":{"kind":"arxiv","id":"1712.03878","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.03878","created_at":"2026-05-18T00:13:37Z"},{"alias_kind":"arxiv_version","alias_value":"1712.03878v5","created_at":"2026-05-18T00:13:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.03878","created_at":"2026-05-18T00:13:37Z"},{"alias_kind":"pith_short_12","alias_value":"ZIM3EYK3I6WD","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZIM3EYK3I6WDLHS3","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZIM3EYK3","created_at":"2026-05-18T12:31:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:ZIM3EYK3I6WDLHS33WUIYMIIDE","target":"record","payload":{"canonical_record":{"source":{"id":"1712.03878","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-11T16:44:12Z","cross_cats_sorted":["cs.CV","stat.ML"],"title_canon_sha256":"b50320378defc7588810f33eeaba1534f433b819f5ca54c33d390210b8e18a98","abstract_canon_sha256":"977b560143a51db487ef752797985a4e13f5608a1ee3eb2dd586fad82a791ec4"},"schema_version":"1.0"},"canonical_sha256":"ca19b2615b47ac359e5bdda88c31081924e8f0e7076cdfde529ba1712b69fef7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:13:37.494041Z","signature_b64":"ZipEVz3p9URMuP6WsKqgAtpl27g6a4Hw5in3hL/AikaGg7TtK4nAx7StSEorRy0q2vCrNqVsD0GGQfLGZxuFDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ca19b2615b47ac359e5bdda88c31081924e8f0e7076cdfde529ba1712b69fef7","last_reissued_at":"2026-05-18T00:13:37.493395Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:13:37.493395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1712.03878","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:13:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f7Rz1dqv6NXr6rl0ole4Bgfd2Zc1dUAJ6FEdhbgTBYZcqwEafipmKdF8PRMRI3eJdoaePbDmTVTdlpc5knFjAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T21:21:34.332579Z"},"content_sha256":"e0d137cb68f2926b5245a6221b919bc07aff6c592b3a1aa4a3d1ac6ca083c8a7","schema_version":"1.0","event_id":"sha256:e0d137cb68f2926b5245a6221b919bc07aff6c592b3a1aa4a3d1ac6ca083c8a7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:ZIM3EYK3I6WDLHS33WUIYMIIDE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Generalized Zero-Shot Learning via Synthesized Examples","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","stat.ML"],"primary_cat":"cs.LG","authors_text":"Ashish Mishra, Gundeep Arora, Piyush Rai, Vinay Kumar Verma","submitted_at":"2017-12-11T16:44:12Z","abstract_excerpt":"We present a generative framework for generalized zero-shot learning where the training and test classes are not necessarily disjoint. Built upon a variational autoencoder based architecture, consisting of a probabilistic encoder and a probabilistic conditional decoder, our model can generate novel exemplars from seen/unseen classes, given their respective class attributes. These exemplars can subsequently be used to train any off-the-shelf classification model. One of the key aspects of our encoder-decoder architecture is a feedback-driven mechanism in which a discriminator (a multivariate re"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.03878","kind":"arxiv","version":5},"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":"2026-05-18T00:13:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7wP/Iyn021LA0brhwxfoQ7u8xtNTWjbEPQbP/H2zg0N8quJgpLGNQ0BXTFQcrHm81UIsdRK5iLdHW9txD2tdDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T21:21:34.333308Z"},"content_sha256":"1f22ceab6dcec66443dc284a0fb5938bdbf0deb7fb706681a5178836e37dae44","schema_version":"1.0","event_id":"sha256:1f22ceab6dcec66443dc284a0fb5938bdbf0deb7fb706681a5178836e37dae44"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZIM3EYK3I6WDLHS33WUIYMIIDE/bundle.json","state_url":"https://pith.science/pith/ZIM3EYK3I6WDLHS33WUIYMIIDE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZIM3EYK3I6WDLHS33WUIYMIIDE/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":"2026-05-31T21:21:34Z","links":{"resolver":"https://pith.science/pith/ZIM3EYK3I6WDLHS33WUIYMIIDE","bundle":"https://pith.science/pith/ZIM3EYK3I6WDLHS33WUIYMIIDE/bundle.json","state":"https://pith.science/pith/ZIM3EYK3I6WDLHS33WUIYMIIDE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZIM3EYK3I6WDLHS33WUIYMIIDE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:ZIM3EYK3I6WDLHS33WUIYMIIDE","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":"977b560143a51db487ef752797985a4e13f5608a1ee3eb2dd586fad82a791ec4","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-11T16:44:12Z","title_canon_sha256":"b50320378defc7588810f33eeaba1534f433b819f5ca54c33d390210b8e18a98"},"schema_version":"1.0","source":{"id":"1712.03878","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1712.03878","created_at":"2026-05-18T00:13:37Z"},{"alias_kind":"arxiv_version","alias_value":"1712.03878v5","created_at":"2026-05-18T00:13:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.03878","created_at":"2026-05-18T00:13:37Z"},{"alias_kind":"pith_short_12","alias_value":"ZIM3EYK3I6WD","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_16","alias_value":"ZIM3EYK3I6WDLHS3","created_at":"2026-05-18T12:31:59Z"},{"alias_kind":"pith_short_8","alias_value":"ZIM3EYK3","created_at":"2026-05-18T12:31:59Z"}],"graph_snapshots":[{"event_id":"sha256:1f22ceab6dcec66443dc284a0fb5938bdbf0deb7fb706681a5178836e37dae44","target":"graph","created_at":"2026-05-18T00:13:37Z","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":"We present a generative framework for generalized zero-shot learning where the training and test classes are not necessarily disjoint. Built upon a variational autoencoder based architecture, consisting of a probabilistic encoder and a probabilistic conditional decoder, our model can generate novel exemplars from seen/unseen classes, given their respective class attributes. These exemplars can subsequently be used to train any off-the-shelf classification model. One of the key aspects of our encoder-decoder architecture is a feedback-driven mechanism in which a discriminator (a multivariate re","authors_text":"Ashish Mishra, Gundeep Arora, Piyush Rai, Vinay Kumar Verma","cross_cats":["cs.CV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-11T16:44:12Z","title":"Generalized Zero-Shot Learning via Synthesized Examples"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.03878","kind":"arxiv","version":5},"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:e0d137cb68f2926b5245a6221b919bc07aff6c592b3a1aa4a3d1ac6ca083c8a7","target":"record","created_at":"2026-05-18T00:13:37Z","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":"977b560143a51db487ef752797985a4e13f5608a1ee3eb2dd586fad82a791ec4","cross_cats_sorted":["cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2017-12-11T16:44:12Z","title_canon_sha256":"b50320378defc7588810f33eeaba1534f433b819f5ca54c33d390210b8e18a98"},"schema_version":"1.0","source":{"id":"1712.03878","kind":"arxiv","version":5}},"canonical_sha256":"ca19b2615b47ac359e5bdda88c31081924e8f0e7076cdfde529ba1712b69fef7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ca19b2615b47ac359e5bdda88c31081924e8f0e7076cdfde529ba1712b69fef7","first_computed_at":"2026-05-18T00:13:37.493395Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:13:37.493395Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZipEVz3p9URMuP6WsKqgAtpl27g6a4Hw5in3hL/AikaGg7TtK4nAx7StSEorRy0q2vCrNqVsD0GGQfLGZxuFDA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:13:37.494041Z","signed_message":"canonical_sha256_bytes"},"source_id":"1712.03878","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e0d137cb68f2926b5245a6221b919bc07aff6c592b3a1aa4a3d1ac6ca083c8a7","sha256:1f22ceab6dcec66443dc284a0fb5938bdbf0deb7fb706681a5178836e37dae44"],"state_sha256":"78781765fb1fb2094b46b422a1d0e607ef2ea3810dfde5efe049644af74fde97"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jyJNJ9ve382WeNoZ4dFMZQkoRcu3UrZSdBt5678BelHZsgzZCCUUm2EOoE5nBi5CXUiMc5HQUvLvsOQjj1r1Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T21:21:34.337334Z","bundle_sha256":"2f639f83a06a3c9fe022c61e8f2f66d94037c416107b0da9e9bcdfd6101d5068"}}