{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:HXXLQ25LGLSXYNDHV3PF4GXQCO","short_pith_number":"pith:HXXLQ25L","canonical_record":{"source":{"id":"1803.06731","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-18T20:18:48Z","cross_cats_sorted":[],"title_canon_sha256":"ea62b38ccd9ec46cf7813d7c68e1104f044b778cda862c6ae37cb44cef9f3660","abstract_canon_sha256":"61a12aef23e33d89472bfc47f4dd297c21cc24fc0b0338aa909391df556ceea1"},"schema_version":"1.0"},"canonical_sha256":"3deeb86bab32e57c3467aede5e1af013b4012506661cd4abc90f6fb84a046583","source":{"kind":"arxiv","id":"1803.06731","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.06731","created_at":"2026-05-18T00:20:45Z"},{"alias_kind":"arxiv_version","alias_value":"1803.06731v1","created_at":"2026-05-18T00:20:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.06731","created_at":"2026-05-18T00:20:45Z"},{"alias_kind":"pith_short_12","alias_value":"HXXLQ25LGLSX","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HXXLQ25LGLSXYNDH","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HXXLQ25L","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:HXXLQ25LGLSXYNDHV3PF4GXQCO","target":"record","payload":{"canonical_record":{"source":{"id":"1803.06731","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-18T20:18:48Z","cross_cats_sorted":[],"title_canon_sha256":"ea62b38ccd9ec46cf7813d7c68e1104f044b778cda862c6ae37cb44cef9f3660","abstract_canon_sha256":"61a12aef23e33d89472bfc47f4dd297c21cc24fc0b0338aa909391df556ceea1"},"schema_version":"1.0"},"canonical_sha256":"3deeb86bab32e57c3467aede5e1af013b4012506661cd4abc90f6fb84a046583","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:20:45.158858Z","signature_b64":"HGjVCy/6LndQCh1/6Of6ptLez90yZOMrOGO2qBNcNmOkRAE2bc5Ig+lxSgZqghPVr/WG0mR9V980Z0ax2incCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3deeb86bab32e57c3467aede5e1af013b4012506661cd4abc90f6fb84a046583","last_reissued_at":"2026-05-18T00:20:45.158345Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:20:45.158345Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1803.06731","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":"2026-05-18T00:20:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"//zr2n/JOTh7N5uMEjvyw30UYvnUTx9FB/y9EnM+D9ILiB7IQt6BtfwexTPg3982iugTKJtNOCIA6++ZZP6GDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T05:16:33.766894Z"},"content_sha256":"3613c386b6393fc50c73baf53e803a45a7b62f9cab4ff7d71629e75767dd2238","schema_version":"1.0","event_id":"sha256:3613c386b6393fc50c73baf53e803a45a7b62f9cab4ff7d71629e75767dd2238"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:HXXLQ25LGLSXYNDHV3PF4GXQCO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Discriminative Learning of Latent Features for Zero-Shot Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Jianguo Zhang, Junge Zhang, Kaiqi Huang, Yan Li","submitted_at":"2018-03-18T20:18:48Z","abstract_excerpt":"Zero-shot learning (ZSL) aims to recognize unseen image categories by learning an embedding space between image and semantic representations. For years, among existing works, it has been the center task to learn the proper mapping matrices aligning the visual and semantic space, whilst the importance to learn discriminative representations for ZSL is ignored. In this work, we retrospect existing methods and demonstrate the necessity to learn discriminative representations for both visual and semantic instances of ZSL. We propose an end-to-end network that is capable of 1) automatically discove"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.06731","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":"2026-05-18T00:20:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nwjycg4r4DmEuUHrs9KVeT7U+vn4G+CDxUkkdIZ6+aOdOCn3psdjsb+P9EXvuBctpE8vuJEr22QZGb0G5J6OBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T05:16:33.767271Z"},"content_sha256":"8d754e371e7e54c294de8ec511aef73feead5b6ab44c4b6eafe5399a3263cd85","schema_version":"1.0","event_id":"sha256:8d754e371e7e54c294de8ec511aef73feead5b6ab44c4b6eafe5399a3263cd85"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HXXLQ25LGLSXYNDHV3PF4GXQCO/bundle.json","state_url":"https://pith.science/pith/HXXLQ25LGLSXYNDHV3PF4GXQCO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HXXLQ25LGLSXYNDHV3PF4GXQCO/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":"2026-05-27T05:16:33Z","links":{"resolver":"https://pith.science/pith/HXXLQ25LGLSXYNDHV3PF4GXQCO","bundle":"https://pith.science/pith/HXXLQ25LGLSXYNDHV3PF4GXQCO/bundle.json","state":"https://pith.science/pith/HXXLQ25LGLSXYNDHV3PF4GXQCO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HXXLQ25LGLSXYNDHV3PF4GXQCO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:HXXLQ25LGLSXYNDHV3PF4GXQCO","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":"61a12aef23e33d89472bfc47f4dd297c21cc24fc0b0338aa909391df556ceea1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-18T20:18:48Z","title_canon_sha256":"ea62b38ccd9ec46cf7813d7c68e1104f044b778cda862c6ae37cb44cef9f3660"},"schema_version":"1.0","source":{"id":"1803.06731","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1803.06731","created_at":"2026-05-18T00:20:45Z"},{"alias_kind":"arxiv_version","alias_value":"1803.06731v1","created_at":"2026-05-18T00:20:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1803.06731","created_at":"2026-05-18T00:20:45Z"},{"alias_kind":"pith_short_12","alias_value":"HXXLQ25LGLSX","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HXXLQ25LGLSXYNDH","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HXXLQ25L","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:8d754e371e7e54c294de8ec511aef73feead5b6ab44c4b6eafe5399a3263cd85","target":"graph","created_at":"2026-05-18T00:20:45Z","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":"Zero-shot learning (ZSL) aims to recognize unseen image categories by learning an embedding space between image and semantic representations. For years, among existing works, it has been the center task to learn the proper mapping matrices aligning the visual and semantic space, whilst the importance to learn discriminative representations for ZSL is ignored. In this work, we retrospect existing methods and demonstrate the necessity to learn discriminative representations for both visual and semantic instances of ZSL. We propose an end-to-end network that is capable of 1) automatically discove","authors_text":"Jianguo Zhang, Junge Zhang, Kaiqi Huang, Yan Li","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-18T20:18:48Z","title":"Discriminative Learning of Latent Features for Zero-Shot Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.06731","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":"sha256:3613c386b6393fc50c73baf53e803a45a7b62f9cab4ff7d71629e75767dd2238","target":"record","created_at":"2026-05-18T00:20:45Z","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":"61a12aef23e33d89472bfc47f4dd297c21cc24fc0b0338aa909391df556ceea1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-03-18T20:18:48Z","title_canon_sha256":"ea62b38ccd9ec46cf7813d7c68e1104f044b778cda862c6ae37cb44cef9f3660"},"schema_version":"1.0","source":{"id":"1803.06731","kind":"arxiv","version":1}},"canonical_sha256":"3deeb86bab32e57c3467aede5e1af013b4012506661cd4abc90f6fb84a046583","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3deeb86bab32e57c3467aede5e1af013b4012506661cd4abc90f6fb84a046583","first_computed_at":"2026-05-18T00:20:45.158345Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:20:45.158345Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"HGjVCy/6LndQCh1/6Of6ptLez90yZOMrOGO2qBNcNmOkRAE2bc5Ig+lxSgZqghPVr/WG0mR9V980Z0ax2incCw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:20:45.158858Z","signed_message":"canonical_sha256_bytes"},"source_id":"1803.06731","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3613c386b6393fc50c73baf53e803a45a7b62f9cab4ff7d71629e75767dd2238","sha256:8d754e371e7e54c294de8ec511aef73feead5b6ab44c4b6eafe5399a3263cd85"],"state_sha256":"c3a9a53d9be3376c5790c2b68bf3218ad551039a9c312a00faa449b9164e27b6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8ewUtLfPdJLo1jxDk+2wulRqBn09Pn+tafhkM2FKCP2CDPb6qJxAu6HpOlZsMMI7/XqGDZlKVQvaRRJAHJsVBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T05:16:33.769725Z","bundle_sha256":"35fcb553dc6c426d4b6d829c9b019d2f04c6fbf01111f11b51175a35638f64f2"}}