{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:34FFHWFQ6KKLI5ZC2WBHBM4O6A","short_pith_number":"pith:34FFHWFQ","canonical_record":{"source":{"id":"1704.07073","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-24T07:57:37Z","cross_cats_sorted":[],"title_canon_sha256":"32a6b9148c28eaeb66bec3584d123f9e318efd09b926e04eacc5a5e6c34a42ef","abstract_canon_sha256":"f16f4f0a5be7a58ad9245e8927ae36a171ecb36c50bf747d7a96da3fe242c041"},"schema_version":"1.0"},"canonical_sha256":"df0a53d8b0f294b47722d58270b38ef00c0c8a6d5c4a9334786fae386f0de104","source":{"kind":"arxiv","id":"1704.07073","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.07073","created_at":"2026-05-18T00:39:17Z"},{"alias_kind":"arxiv_version","alias_value":"1704.07073v1","created_at":"2026-05-18T00:39:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.07073","created_at":"2026-05-18T00:39:17Z"},{"alias_kind":"pith_short_12","alias_value":"34FFHWFQ6KKL","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_16","alias_value":"34FFHWFQ6KKLI5ZC","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_8","alias_value":"34FFHWFQ","created_at":"2026-05-18T12:30:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:34FFHWFQ6KKLI5ZC2WBHBM4O6A","target":"record","payload":{"canonical_record":{"source":{"id":"1704.07073","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-24T07:57:37Z","cross_cats_sorted":[],"title_canon_sha256":"32a6b9148c28eaeb66bec3584d123f9e318efd09b926e04eacc5a5e6c34a42ef","abstract_canon_sha256":"f16f4f0a5be7a58ad9245e8927ae36a171ecb36c50bf747d7a96da3fe242c041"},"schema_version":"1.0"},"canonical_sha256":"df0a53d8b0f294b47722d58270b38ef00c0c8a6d5c4a9334786fae386f0de104","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:39:17.809344Z","signature_b64":"7OnZXynJNT8xM6XbwokT5ZHBx6ZGHxgdESyJp4nZy/ic+5xKdcxXAn3yoUNQ8kozVRP4e+zd1Zh6sUgtMQLPDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"df0a53d8b0f294b47722d58270b38ef00c0c8a6d5c4a9334786fae386f0de104","last_reissued_at":"2026-05-18T00:39:17.808699Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:39:17.808699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1704.07073","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":"2026-05-18T00:39:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9ooe2vGxbEmIFqKvkEFel4Nx0VcSMnUV0UhqP3EGMcr76sTJyAZSOc5fWrBMJK9T9q4IsgTnoXmS+PgjlOSvDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T13:53:56.284404Z"},"content_sha256":"a0e62b3d5116ae54f3ab4b20c297104acba376c5bf18fafe1c027f8506438b97","schema_version":"1.0","event_id":"sha256:a0e62b3d5116ae54f3ab4b20c297104acba376c5bf18fafe1c027f8506438b97"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:34FFHWFQ6KKLI5ZC2WBHBM4O6A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Selective Encoding for Abstractive Sentence Summarization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Furu Wei, Ming Zhou, Nan Yang, Qingyu Zhou","submitted_at":"2017-04-24T07:57:37Z","abstract_excerpt":"We propose a selective encoding model to extend the sequence-to-sequence framework for abstractive sentence summarization. It consists of a sentence encoder, a selective gate network, and an attention equipped decoder. The sentence encoder and decoder are built with recurrent neural networks. The selective gate network constructs a second level sentence representation by controlling the information flow from encoder to decoder. The second level representation is tailored for sentence summarization task, which leads to better performance. We evaluate our model on the English Gigaword, DUC 2004 "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.07073","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":"2026-05-18T00:39:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MIlprdk9U3MYJJLGKTE72ZIKPM5MuerK070nk9KnbuaY8OTPCqnApQkvYgB/sFRtYNXvlsEhtl8a5iJ+VJpVBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T13:53:56.284801Z"},"content_sha256":"a04ff05acfe15f78b2c41bc692fdcf4fce27a85d188b44b7099b766947b46b4d","schema_version":"1.0","event_id":"sha256:a04ff05acfe15f78b2c41bc692fdcf4fce27a85d188b44b7099b766947b46b4d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/34FFHWFQ6KKLI5ZC2WBHBM4O6A/bundle.json","state_url":"https://pith.science/pith/34FFHWFQ6KKLI5ZC2WBHBM4O6A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/34FFHWFQ6KKLI5ZC2WBHBM4O6A/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":"2026-06-04T13:53:56Z","links":{"resolver":"https://pith.science/pith/34FFHWFQ6KKLI5ZC2WBHBM4O6A","bundle":"https://pith.science/pith/34FFHWFQ6KKLI5ZC2WBHBM4O6A/bundle.json","state":"https://pith.science/pith/34FFHWFQ6KKLI5ZC2WBHBM4O6A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/34FFHWFQ6KKLI5ZC2WBHBM4O6A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:34FFHWFQ6KKLI5ZC2WBHBM4O6A","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":"f16f4f0a5be7a58ad9245e8927ae36a171ecb36c50bf747d7a96da3fe242c041","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-24T07:57:37Z","title_canon_sha256":"32a6b9148c28eaeb66bec3584d123f9e318efd09b926e04eacc5a5e6c34a42ef"},"schema_version":"1.0","source":{"id":"1704.07073","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.07073","created_at":"2026-05-18T00:39:17Z"},{"alias_kind":"arxiv_version","alias_value":"1704.07073v1","created_at":"2026-05-18T00:39:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.07073","created_at":"2026-05-18T00:39:17Z"},{"alias_kind":"pith_short_12","alias_value":"34FFHWFQ6KKL","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_16","alias_value":"34FFHWFQ6KKLI5ZC","created_at":"2026-05-18T12:30:58Z"},{"alias_kind":"pith_short_8","alias_value":"34FFHWFQ","created_at":"2026-05-18T12:30:58Z"}],"graph_snapshots":[{"event_id":"sha256:a04ff05acfe15f78b2c41bc692fdcf4fce27a85d188b44b7099b766947b46b4d","target":"graph","created_at":"2026-05-18T00:39:17Z","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":"We propose a selective encoding model to extend the sequence-to-sequence framework for abstractive sentence summarization. It consists of a sentence encoder, a selective gate network, and an attention equipped decoder. The sentence encoder and decoder are built with recurrent neural networks. The selective gate network constructs a second level sentence representation by controlling the information flow from encoder to decoder. The second level representation is tailored for sentence summarization task, which leads to better performance. We evaluate our model on the English Gigaword, DUC 2004 ","authors_text":"Furu Wei, Ming Zhou, Nan Yang, Qingyu Zhou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-24T07:57:37Z","title":"Selective Encoding for Abstractive Sentence Summarization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.07073","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:a0e62b3d5116ae54f3ab4b20c297104acba376c5bf18fafe1c027f8506438b97","target":"record","created_at":"2026-05-18T00:39:17Z","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":"f16f4f0a5be7a58ad9245e8927ae36a171ecb36c50bf747d7a96da3fe242c041","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-24T07:57:37Z","title_canon_sha256":"32a6b9148c28eaeb66bec3584d123f9e318efd09b926e04eacc5a5e6c34a42ef"},"schema_version":"1.0","source":{"id":"1704.07073","kind":"arxiv","version":1}},"canonical_sha256":"df0a53d8b0f294b47722d58270b38ef00c0c8a6d5c4a9334786fae386f0de104","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"df0a53d8b0f294b47722d58270b38ef00c0c8a6d5c4a9334786fae386f0de104","first_computed_at":"2026-05-18T00:39:17.808699Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:39:17.808699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7OnZXynJNT8xM6XbwokT5ZHBx6ZGHxgdESyJp4nZy/ic+5xKdcxXAn3yoUNQ8kozVRP4e+zd1Zh6sUgtMQLPDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:39:17.809344Z","signed_message":"canonical_sha256_bytes"},"source_id":"1704.07073","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a0e62b3d5116ae54f3ab4b20c297104acba376c5bf18fafe1c027f8506438b97","sha256:a04ff05acfe15f78b2c41bc692fdcf4fce27a85d188b44b7099b766947b46b4d"],"state_sha256":"0840e524d724c2d8effa5eeb03a037a5073dab76bba2c12fa79e35fc76cfc637"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ETAWhvt07uS2fWJtUz7W5gXd5EXeuBO8QghfXKMOjqXKacnhTvuGPajYpTF1qHEhceKL07Cpz5bJq2dfwOTsAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T13:53:56.287183Z","bundle_sha256":"e3dc5c2d709373ae380a81422542612099c57ac4a90d010dd8072c722c75c6cf"}}