{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:BPKPGDRH2YTKF2FSYJU5G7Y6BN","short_pith_number":"pith:BPKPGDRH","canonical_record":{"source":{"id":"1904.07659","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T13:37:15Z","cross_cats_sorted":[],"title_canon_sha256":"6d2140c6f8eec806989e7c61dcab5d36d51abbe2820cddc8f89d4a5a6e0f1add","abstract_canon_sha256":"fb4979a574d83c5dd79b9037df939e72dad0d2f03ff9d5490f72c27197777211"},"schema_version":"1.0"},"canonical_sha256":"0bd4f30e27d626a2e8b2c269d37f1e0b594b687e6c1b7d61e6ece835e56c1d97","source":{"kind":"arxiv","id":"1904.07659","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.07659","created_at":"2026-05-17T23:48:24Z"},{"alias_kind":"arxiv_version","alias_value":"1904.07659v1","created_at":"2026-05-17T23:48:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.07659","created_at":"2026-05-17T23:48:24Z"},{"alias_kind":"pith_short_12","alias_value":"BPKPGDRH2YTK","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"BPKPGDRH2YTKF2FS","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"BPKPGDRH","created_at":"2026-05-18T12:33:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:BPKPGDRH2YTKF2FSYJU5G7Y6BN","target":"record","payload":{"canonical_record":{"source":{"id":"1904.07659","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T13:37:15Z","cross_cats_sorted":[],"title_canon_sha256":"6d2140c6f8eec806989e7c61dcab5d36d51abbe2820cddc8f89d4a5a6e0f1add","abstract_canon_sha256":"fb4979a574d83c5dd79b9037df939e72dad0d2f03ff9d5490f72c27197777211"},"schema_version":"1.0"},"canonical_sha256":"0bd4f30e27d626a2e8b2c269d37f1e0b594b687e6c1b7d61e6ece835e56c1d97","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:48:24.562555Z","signature_b64":"3viUlVUk7pN76iFI2Tz6okPwlEjgzqhUbr8ZpGsV+Q7/81rKwBvBkhWChWtsk1x7YzNomkEn3az3mG+s+782BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0bd4f30e27d626a2e8b2c269d37f1e0b594b687e6c1b7d61e6ece835e56c1d97","last_reissued_at":"2026-05-17T23:48:24.561964Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:48:24.561964Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.07659","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":"2026-05-17T23:48:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cyCrTSSBKEbtTy8/e1Kl+WfLIW6/LU876AhT92s6ggSLx9i6nNcicEjBevuLLWiyD57z+a5bV0hgdzIJkrIbBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T07:38:08.801875Z"},"content_sha256":"29bad306a0e535755625bddc32a354727102217beb4259013adf6b9809afb60c","schema_version":"1.0","event_id":"sha256:29bad306a0e535755625bddc32a354727102217beb4259013adf6b9809afb60c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:BPKPGDRH2YTKF2FSYJU5G7Y6BN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Semantically Aligned Bias Reducing Zero Shot Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Akanksha Paul, Narayanan C. Krishnan, Prateek Munjal","submitted_at":"2019-04-16T13:37:15Z","abstract_excerpt":"Zero shot learning (ZSL) aims to recognize unseen classes by exploiting semantic relationships between seen and unseen classes. Two major problems faced by ZSL algorithms are the hubness problem and the bias towards the seen classes. Existing ZSL methods focus on only one of these problems in the conventional and generalized ZSL setting. In this work, we propose a novel approach, Semantically Aligned Bias Reducing (SABR) ZSL, which focuses on solving both the problems. It overcomes the hubness problem by learning a latent space that preserves the semantic relationship between the labels while "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.07659","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":"2026-05-17T23:48:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W4+CN8x4lc3TuGb0/3bTHXeeZ9GLZcO1Z2hy4eI7hu5f8SNoabwE5kaLL7I/WDSJXmUl24znZ9W4LKi6IWfXBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T07:38:08.802481Z"},"content_sha256":"62d876fd95fbd637ff77fb8aa23264e4c887ea684e54ca41dff795c343aec0e3","schema_version":"1.0","event_id":"sha256:62d876fd95fbd637ff77fb8aa23264e4c887ea684e54ca41dff795c343aec0e3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BPKPGDRH2YTKF2FSYJU5G7Y6BN/bundle.json","state_url":"https://pith.science/pith/BPKPGDRH2YTKF2FSYJU5G7Y6BN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BPKPGDRH2YTKF2FSYJU5G7Y6BN/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":"2026-07-08T07:38:08Z","links":{"resolver":"https://pith.science/pith/BPKPGDRH2YTKF2FSYJU5G7Y6BN","bundle":"https://pith.science/pith/BPKPGDRH2YTKF2FSYJU5G7Y6BN/bundle.json","state":"https://pith.science/pith/BPKPGDRH2YTKF2FSYJU5G7Y6BN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BPKPGDRH2YTKF2FSYJU5G7Y6BN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:BPKPGDRH2YTKF2FSYJU5G7Y6BN","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":"fb4979a574d83c5dd79b9037df939e72dad0d2f03ff9d5490f72c27197777211","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T13:37:15Z","title_canon_sha256":"6d2140c6f8eec806989e7c61dcab5d36d51abbe2820cddc8f89d4a5a6e0f1add"},"schema_version":"1.0","source":{"id":"1904.07659","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.07659","created_at":"2026-05-17T23:48:24Z"},{"alias_kind":"arxiv_version","alias_value":"1904.07659v1","created_at":"2026-05-17T23:48:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.07659","created_at":"2026-05-17T23:48:24Z"},{"alias_kind":"pith_short_12","alias_value":"BPKPGDRH2YTK","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_16","alias_value":"BPKPGDRH2YTKF2FS","created_at":"2026-05-18T12:33:12Z"},{"alias_kind":"pith_short_8","alias_value":"BPKPGDRH","created_at":"2026-05-18T12:33:12Z"}],"graph_snapshots":[{"event_id":"sha256:62d876fd95fbd637ff77fb8aa23264e4c887ea684e54ca41dff795c343aec0e3","target":"graph","created_at":"2026-05-17T23:48:24Z","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"},"paper":{"abstract_excerpt":"Zero shot learning (ZSL) aims to recognize unseen classes by exploiting semantic relationships between seen and unseen classes. Two major problems faced by ZSL algorithms are the hubness problem and the bias towards the seen classes. Existing ZSL methods focus on only one of these problems in the conventional and generalized ZSL setting. In this work, we propose a novel approach, Semantically Aligned Bias Reducing (SABR) ZSL, which focuses on solving both the problems. It overcomes the hubness problem by learning a latent space that preserves the semantic relationship between the labels while ","authors_text":"Akanksha Paul, Narayanan C. Krishnan, Prateek Munjal","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T13:37:15Z","title":"Semantically Aligned Bias Reducing Zero Shot Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.07659","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":"sha256:29bad306a0e535755625bddc32a354727102217beb4259013adf6b9809afb60c","target":"record","created_at":"2026-05-17T23:48:24Z","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":"fb4979a574d83c5dd79b9037df939e72dad0d2f03ff9d5490f72c27197777211","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-04-16T13:37:15Z","title_canon_sha256":"6d2140c6f8eec806989e7c61dcab5d36d51abbe2820cddc8f89d4a5a6e0f1add"},"schema_version":"1.0","source":{"id":"1904.07659","kind":"arxiv","version":1}},"canonical_sha256":"0bd4f30e27d626a2e8b2c269d37f1e0b594b687e6c1b7d61e6ece835e56c1d97","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0bd4f30e27d626a2e8b2c269d37f1e0b594b687e6c1b7d61e6ece835e56c1d97","first_computed_at":"2026-05-17T23:48:24.561964Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:48:24.561964Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3viUlVUk7pN76iFI2Tz6okPwlEjgzqhUbr8ZpGsV+Q7/81rKwBvBkhWChWtsk1x7YzNomkEn3az3mG+s+782BQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:48:24.562555Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.07659","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:29bad306a0e535755625bddc32a354727102217beb4259013adf6b9809afb60c","sha256:62d876fd95fbd637ff77fb8aa23264e4c887ea684e54ca41dff795c343aec0e3"],"state_sha256":"0c9816a13df9feaaa8abe62623ecf749df4858eed76b26be10ff47f0ccb7f5d0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tx5ZjL3z6kW0zgEg7f+SNrd3BZwYRqGkC5SEOMCm+4N4Egj6nqKEQVpZypKy0jAcFOb/dDYl/FlADGNRsFjQAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T07:38:08.805943Z","bundle_sha256":"528d9eb93132a2be24f5ca5d25163c5315a303ea0f05c8c00d5987c856a6b860"}}