{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:PHJ6BIG6YWJWHQLALEMYJRRCCJ","short_pith_number":"pith:PHJ6BIG6","canonical_record":{"source":{"id":"1903.05153","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-12T19:06:18Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"b830d2a3c8b5ba14bd119741087e5511eb1b2f67bf05c939b5bc292f6880e194","abstract_canon_sha256":"08c0845af794b0862125f70855e720ab1d31209d56285283f5902a0f22aa1c1d"},"schema_version":"1.0"},"canonical_sha256":"79d3e0a0dec59363c160591984c62212540b63e4d9022772ca68a000ce8bad0a","source":{"kind":"arxiv","id":"1903.05153","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.05153","created_at":"2026-05-17T23:51:25Z"},{"alias_kind":"arxiv_version","alias_value":"1903.05153v1","created_at":"2026-05-17T23:51:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.05153","created_at":"2026-05-17T23:51:25Z"},{"alias_kind":"pith_short_12","alias_value":"PHJ6BIG6YWJW","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"PHJ6BIG6YWJWHQLA","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"PHJ6BIG6","created_at":"2026-05-18T12:33:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:PHJ6BIG6YWJWHQLALEMYJRRCCJ","target":"record","payload":{"canonical_record":{"source":{"id":"1903.05153","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-12T19:06:18Z","cross_cats_sorted":["cs.AI","stat.ML"],"title_canon_sha256":"b830d2a3c8b5ba14bd119741087e5511eb1b2f67bf05c939b5bc292f6880e194","abstract_canon_sha256":"08c0845af794b0862125f70855e720ab1d31209d56285283f5902a0f22aa1c1d"},"schema_version":"1.0"},"canonical_sha256":"79d3e0a0dec59363c160591984c62212540b63e4d9022772ca68a000ce8bad0a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:25.298553Z","signature_b64":"SgHih/nrmYK+luNyVGa2D4WR0tMha7Q4djQ877rpMeQe4xlQZKqzxVPv5fOVNylZXCyn0Kx5Iep3ZAoX+seGBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"79d3e0a0dec59363c160591984c62212540b63e4d9022772ca68a000ce8bad0a","last_reissued_at":"2026-05-17T23:51:25.298024Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:25.298024Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.05153","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":"2026-05-17T23:51:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7aHyjqW9mZNLaJXe1Qrgv2iEZ46Mo2sfy9gC+n+7zR+pNtxKOrUZqzX/LJJEAUbBiwFHc6RKACBj52VdEm7JBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T09:08:40.048509Z"},"content_sha256":"d8d1b5a7b747bb0b3788de79a23d361eef593f9480f06506848bc92dbfa95f29","schema_version":"1.0","event_id":"sha256:d8d1b5a7b747bb0b3788de79a23d361eef593f9480f06506848bc92dbfa95f29"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:PHJ6BIG6YWJWHQLALEMYJRRCCJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Sequential Set Generation Method for Predicting Set-Valued Outputs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","stat.ML"],"primary_cat":"cs.LG","authors_text":"Jie Chen, Michael Witbrock, Tian Gao, Vijil Chenthamarakshan","submitted_at":"2019-03-12T19:06:18Z","abstract_excerpt":"Consider a general machine learning setting where the output is a set of labels or sequences. This output set is unordered and its size varies with the input. Whereas multi-label classification methods seem a natural first resort, they are not readily applicable to set-valued outputs because of the growth rate of the output space; and because conventional sequence generation doesn't reflect sets' order-free nature. In this paper, we propose a unified framework--sequential set generation (SSG)--that can handle output sets of labels and sequences. SSG is a meta-algorithm that leverages any proba"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.05153","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":"2026-05-17T23:51:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y8C28Am4ff5PJNJocQYFNiKKkkP5sAJLosEU49S1AoygUZJbIuTZYF9Tr753TYICHhPNMk/+L5hkUIHfJZYdAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T09:08:40.049152Z"},"content_sha256":"d9e4239659cb1ac85f070592f23d169749742f764d5fdfe1ecfb5d7fd2c4bbad","schema_version":"1.0","event_id":"sha256:d9e4239659cb1ac85f070592f23d169749742f764d5fdfe1ecfb5d7fd2c4bbad"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PHJ6BIG6YWJWHQLALEMYJRRCCJ/bundle.json","state_url":"https://pith.science/pith/PHJ6BIG6YWJWHQLALEMYJRRCCJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PHJ6BIG6YWJWHQLALEMYJRRCCJ/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":"2026-05-27T09:08:40Z","links":{"resolver":"https://pith.science/pith/PHJ6BIG6YWJWHQLALEMYJRRCCJ","bundle":"https://pith.science/pith/PHJ6BIG6YWJWHQLALEMYJRRCCJ/bundle.json","state":"https://pith.science/pith/PHJ6BIG6YWJWHQLALEMYJRRCCJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PHJ6BIG6YWJWHQLALEMYJRRCCJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:PHJ6BIG6YWJWHQLALEMYJRRCCJ","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":"08c0845af794b0862125f70855e720ab1d31209d56285283f5902a0f22aa1c1d","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-12T19:06:18Z","title_canon_sha256":"b830d2a3c8b5ba14bd119741087e5511eb1b2f67bf05c939b5bc292f6880e194"},"schema_version":"1.0","source":{"id":"1903.05153","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.05153","created_at":"2026-05-17T23:51:25Z"},{"alias_kind":"arxiv_version","alias_value":"1903.05153v1","created_at":"2026-05-17T23:51:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.05153","created_at":"2026-05-17T23:51:25Z"},{"alias_kind":"pith_short_12","alias_value":"PHJ6BIG6YWJW","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_16","alias_value":"PHJ6BIG6YWJWHQLA","created_at":"2026-05-18T12:33:24Z"},{"alias_kind":"pith_short_8","alias_value":"PHJ6BIG6","created_at":"2026-05-18T12:33:24Z"}],"graph_snapshots":[{"event_id":"sha256:d9e4239659cb1ac85f070592f23d169749742f764d5fdfe1ecfb5d7fd2c4bbad","target":"graph","created_at":"2026-05-17T23:51:25Z","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":"Consider a general machine learning setting where the output is a set of labels or sequences. This output set is unordered and its size varies with the input. Whereas multi-label classification methods seem a natural first resort, they are not readily applicable to set-valued outputs because of the growth rate of the output space; and because conventional sequence generation doesn't reflect sets' order-free nature. In this paper, we propose a unified framework--sequential set generation (SSG)--that can handle output sets of labels and sequences. SSG is a meta-algorithm that leverages any proba","authors_text":"Jie Chen, Michael Witbrock, Tian Gao, Vijil Chenthamarakshan","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-12T19:06:18Z","title":"A Sequential Set Generation Method for Predicting Set-Valued Outputs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.05153","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:d8d1b5a7b747bb0b3788de79a23d361eef593f9480f06506848bc92dbfa95f29","target":"record","created_at":"2026-05-17T23:51:25Z","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":"08c0845af794b0862125f70855e720ab1d31209d56285283f5902a0f22aa1c1d","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-03-12T19:06:18Z","title_canon_sha256":"b830d2a3c8b5ba14bd119741087e5511eb1b2f67bf05c939b5bc292f6880e194"},"schema_version":"1.0","source":{"id":"1903.05153","kind":"arxiv","version":1}},"canonical_sha256":"79d3e0a0dec59363c160591984c62212540b63e4d9022772ca68a000ce8bad0a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"79d3e0a0dec59363c160591984c62212540b63e4d9022772ca68a000ce8bad0a","first_computed_at":"2026-05-17T23:51:25.298024Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:51:25.298024Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"SgHih/nrmYK+luNyVGa2D4WR0tMha7Q4djQ877rpMeQe4xlQZKqzxVPv5fOVNylZXCyn0Kx5Iep3ZAoX+seGBg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:51:25.298553Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.05153","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d8d1b5a7b747bb0b3788de79a23d361eef593f9480f06506848bc92dbfa95f29","sha256:d9e4239659cb1ac85f070592f23d169749742f764d5fdfe1ecfb5d7fd2c4bbad"],"state_sha256":"8c2c8f988669dac80e15944836c6ff1acd1cfd6813db0590351785367dbbac2d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GCp+W9npSlKIgoc2yF0zb373190bUcBWScQPbgC8Q2hJ0Yn7qmgJg0LHTCRlBYQ8C27Kig9QKSA8I5I7dPDCDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T09:08:40.052661Z","bundle_sha256":"e837bf6e3d28568db3bdbfd867e78616d2ab5772a9cc7d7291480bb2adfa19b7"}}