{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:VSEKN53O2XHZJ6PGLYD2S6JW3E","short_pith_number":"pith:VSEKN53O","canonical_record":{"source":{"id":"1703.05667","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-03-16T15:14:48Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"41f5dc727aec0f8ac215e2cbf5d63c53f01e5336b7dbeee2fcef85d0269c21b4","abstract_canon_sha256":"b5412308b0b11536cc783121391cd0f98a134443f4ea5cbe2cd3d5d0a3e6e60b"},"schema_version":"1.0"},"canonical_sha256":"ac88a6f76ed5cf94f9e65e07a97936d901f9c6fe845183f1c1754d9cf0da18b4","source":{"kind":"arxiv","id":"1703.05667","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.05667","created_at":"2026-05-18T00:40:17Z"},{"alias_kind":"arxiv_version","alias_value":"1703.05667v2","created_at":"2026-05-18T00:40:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.05667","created_at":"2026-05-18T00:40:17Z"},{"alias_kind":"pith_short_12","alias_value":"VSEKN53O2XHZ","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"VSEKN53O2XHZJ6PG","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"VSEKN53O","created_at":"2026-05-18T12:31:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:VSEKN53O2XHZJ6PGLYD2S6JW3E","target":"record","payload":{"canonical_record":{"source":{"id":"1703.05667","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-03-16T15:14:48Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"41f5dc727aec0f8ac215e2cbf5d63c53f01e5336b7dbeee2fcef85d0269c21b4","abstract_canon_sha256":"b5412308b0b11536cc783121391cd0f98a134443f4ea5cbe2cd3d5d0a3e6e60b"},"schema_version":"1.0"},"canonical_sha256":"ac88a6f76ed5cf94f9e65e07a97936d901f9c6fe845183f1c1754d9cf0da18b4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:40:17.324767Z","signature_b64":"hL1HkAriM3lc1pOd7bYCaHH+j+ZMaokFiLdmtMTU2/O+6uSpIDSK7w2r1HxeGpcnKpkhxZAkwe+RxnOEu8viCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ac88a6f76ed5cf94f9e65e07a97936d901f9c6fe845183f1c1754d9cf0da18b4","last_reissued_at":"2026-05-18T00:40:17.324013Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:40:17.324013Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1703.05667","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:40:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Zsl7anwRCeYJqDYDrK8sVSKW54ha0npCM3hHaZQsi2nw/uwnjHWITuhylkUgqXiSC2zPr24B6lIiJIx02nCWBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T12:38:08.478206Z"},"content_sha256":"34addf2f13f304f698d5b897a1525f1634db6c8394960ba8c3fd53264aee963a","schema_version":"1.0","event_id":"sha256:34addf2f13f304f698d5b897a1525f1634db6c8394960ba8c3fd53264aee963a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:VSEKN53O2XHZJ6PGLYD2S6JW3E","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"End-to-End Learning for Structured Prediction Energy Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"stat.ML","authors_text":"Andrew McCallum, Bishan Yang, David Belanger","submitted_at":"2017-03-16T15:14:48Z","abstract_excerpt":"Structured Prediction Energy Networks (SPENs) are a simple, yet expressive family of structured prediction models (Belanger and McCallum, 2016). An energy function over candidate structured outputs is given by a deep network, and predictions are formed by gradient-based optimization. This paper presents end-to-end learning for SPENs, where the energy function is discriminatively trained by back-propagating through gradient-based prediction. In our experience, the approach is substantially more accurate than the structured SVM method of Belanger and McCallum (2016), as it allows us to use more "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.05667","kind":"arxiv","version":2},"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":"2026-05-18T00:40:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jO8ly4dLLp74rTwaqRvSznELgNql208DD5WZxalZ6krQOBA7+hHTl9w7IXdQUhMXXsKh4OCR62CU2jTpmYJ1Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T12:38:08.478855Z"},"content_sha256":"2e3eeefde587e8d6a9ec99834995be4fb3896c454b108031c59e9da290422434","schema_version":"1.0","event_id":"sha256:2e3eeefde587e8d6a9ec99834995be4fb3896c454b108031c59e9da290422434"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VSEKN53O2XHZJ6PGLYD2S6JW3E/bundle.json","state_url":"https://pith.science/pith/VSEKN53O2XHZJ6PGLYD2S6JW3E/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VSEKN53O2XHZJ6PGLYD2S6JW3E/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":"2026-05-27T12:38:08Z","links":{"resolver":"https://pith.science/pith/VSEKN53O2XHZJ6PGLYD2S6JW3E","bundle":"https://pith.science/pith/VSEKN53O2XHZJ6PGLYD2S6JW3E/bundle.json","state":"https://pith.science/pith/VSEKN53O2XHZJ6PGLYD2S6JW3E/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VSEKN53O2XHZJ6PGLYD2S6JW3E/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:VSEKN53O2XHZJ6PGLYD2S6JW3E","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":"b5412308b0b11536cc783121391cd0f98a134443f4ea5cbe2cd3d5d0a3e6e60b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-03-16T15:14:48Z","title_canon_sha256":"41f5dc727aec0f8ac215e2cbf5d63c53f01e5336b7dbeee2fcef85d0269c21b4"},"schema_version":"1.0","source":{"id":"1703.05667","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1703.05667","created_at":"2026-05-18T00:40:17Z"},{"alias_kind":"arxiv_version","alias_value":"1703.05667v2","created_at":"2026-05-18T00:40:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1703.05667","created_at":"2026-05-18T00:40:17Z"},{"alias_kind":"pith_short_12","alias_value":"VSEKN53O2XHZ","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"VSEKN53O2XHZJ6PG","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"VSEKN53O","created_at":"2026-05-18T12:31:49Z"}],"graph_snapshots":[{"event_id":"sha256:2e3eeefde587e8d6a9ec99834995be4fb3896c454b108031c59e9da290422434","target":"graph","created_at":"2026-05-18T00:40:17Z","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":"Structured Prediction Energy Networks (SPENs) are a simple, yet expressive family of structured prediction models (Belanger and McCallum, 2016). An energy function over candidate structured outputs is given by a deep network, and predictions are formed by gradient-based optimization. This paper presents end-to-end learning for SPENs, where the energy function is discriminatively trained by back-propagating through gradient-based prediction. In our experience, the approach is substantially more accurate than the structured SVM method of Belanger and McCallum (2016), as it allows us to use more ","authors_text":"Andrew McCallum, Bishan Yang, David Belanger","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-03-16T15:14:48Z","title":"End-to-End Learning for Structured Prediction Energy Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1703.05667","kind":"arxiv","version":2},"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":"sha256:34addf2f13f304f698d5b897a1525f1634db6c8394960ba8c3fd53264aee963a","target":"record","created_at":"2026-05-18T00:40:17Z","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":"b5412308b0b11536cc783121391cd0f98a134443f4ea5cbe2cd3d5d0a3e6e60b","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2017-03-16T15:14:48Z","title_canon_sha256":"41f5dc727aec0f8ac215e2cbf5d63c53f01e5336b7dbeee2fcef85d0269c21b4"},"schema_version":"1.0","source":{"id":"1703.05667","kind":"arxiv","version":2}},"canonical_sha256":"ac88a6f76ed5cf94f9e65e07a97936d901f9c6fe845183f1c1754d9cf0da18b4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ac88a6f76ed5cf94f9e65e07a97936d901f9c6fe845183f1c1754d9cf0da18b4","first_computed_at":"2026-05-18T00:40:17.324013Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:40:17.324013Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hL1HkAriM3lc1pOd7bYCaHH+j+ZMaokFiLdmtMTU2/O+6uSpIDSK7w2r1HxeGpcnKpkhxZAkwe+RxnOEu8viCg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:40:17.324767Z","signed_message":"canonical_sha256_bytes"},"source_id":"1703.05667","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:34addf2f13f304f698d5b897a1525f1634db6c8394960ba8c3fd53264aee963a","sha256:2e3eeefde587e8d6a9ec99834995be4fb3896c454b108031c59e9da290422434"],"state_sha256":"5e4a3edd088aeb44b1435517f08bcc0db9bec0b8cb51eac4c58f97b1ab2b04f0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"osLH+qNHNaEbcWWPSwKJkfu5coeqzpHRDMVrVv3yo/Sqp/EXtqBD7P/RM/gRJPBUbxrJc7ruEGkYJbMRvesiBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T12:38:08.482464Z","bundle_sha256":"d50d8d02ca8b3e83fe0ceac935cf179b65dad2e91ef486cd0e7a43de517c9444"}}