{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:YFVB2YWBU4CDGTJFQOEK7LHIEV","short_pith_number":"pith:YFVB2YWB","canonical_record":{"source":{"id":"1812.07699","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2018-12-18T23:43:48Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"244aba95725e40167e83d2ea1282d397ef5f43c1f95e4cbff415bb6805c47958","abstract_canon_sha256":"b35ca2eb945eba8cc65263ecde89adc7b1e03fec92ae217e73b27bbba38a6250"},"schema_version":"1.0"},"canonical_sha256":"c16a1d62c1a704334d258388aface82576789b17709577122742981a6cd5e943","source":{"kind":"arxiv","id":"1812.07699","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.07699","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"arxiv_version","alias_value":"1812.07699v1","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.07699","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"pith_short_12","alias_value":"YFVB2YWBU4CD","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"YFVB2YWBU4CDGTJF","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"YFVB2YWB","created_at":"2026-05-18T12:33:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:YFVB2YWBU4CDGTJFQOEK7LHIEV","target":"record","payload":{"canonical_record":{"source":{"id":"1812.07699","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2018-12-18T23:43:48Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"244aba95725e40167e83d2ea1282d397ef5f43c1f95e4cbff415bb6805c47958","abstract_canon_sha256":"b35ca2eb945eba8cc65263ecde89adc7b1e03fec92ae217e73b27bbba38a6250"},"schema_version":"1.0"},"canonical_sha256":"c16a1d62c1a704334d258388aface82576789b17709577122742981a6cd5e943","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:57:56.274303Z","signature_b64":"tZak7t9glkcqAev4/kjxzM1yhXtKKWrYl5CCQqxjTnpTDEbHrl8w9ratG5kONhTFYYBpYDKvnUl9L16RyDpOAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c16a1d62c1a704334d258388aface82576789b17709577122742981a6cd5e943","last_reissued_at":"2026-05-17T23:57:56.273762Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:57:56.273762Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1812.07699","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":"2026-05-17T23:57:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"U3nzknuFKsjWlrsgSIuC591HM7ufOKLBeoSr1TdOx/erZ5p38YZpVoD92JiiVWiOa8RGZSB3Xyf6DSGKtt0+Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T04:30:28.831819Z"},"content_sha256":"e3f58850b2fc3dac5e74170d0ba8ce1e4a76ecb606ce8e4883c330a20c47ebd5","schema_version":"1.0","event_id":"sha256:e3f58850b2fc3dac5e74170d0ba8ce1e4a76ecb606ce8e4883c330a20c47ebd5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:YFVB2YWBU4CDGTJFQOEK7LHIEV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Comparison of LSTMs and Attention Mechanisms for Forecasting Financial Time Series","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Antoine Viscardi, Seung Eun Yi, Thomas Hollis","submitted_at":"2018-12-18T23:43:48Z","abstract_excerpt":"While LSTMs show increasingly promising results for forecasting Financial Time Series (FTS), this paper seeks to assess if attention mechanisms can further improve performance. The hypothesis is that attention can help prevent long-term dependencies experienced by LSTM models. To test this hypothesis, the main contribution of this paper is the implementation of an LSTM with attention. Both the benchmark LSTM and the LSTM with attention were compared and both achieved reasonable performances of up to 60% on five stocks from Kaggle's Two Sigma dataset. This comparative analysis demonstrates that"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.07699","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":"2026-05-17T23:57:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+ecTZOCGv4BA6dvCUxSYkVvgbAS4tjSXovl9nWaKu2LeGKhfRz9HP7R6987/6VUremqSUHlUxT8zvTOPCUHQCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-09T04:30:28.832506Z"},"content_sha256":"e62cb8f4e2abc5f54be4def079e0918bb8eb506eec9a31ea6f3ac46577a7cfa5","schema_version":"1.0","event_id":"sha256:e62cb8f4e2abc5f54be4def079e0918bb8eb506eec9a31ea6f3ac46577a7cfa5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YFVB2YWBU4CDGTJFQOEK7LHIEV/bundle.json","state_url":"https://pith.science/pith/YFVB2YWBU4CDGTJFQOEK7LHIEV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YFVB2YWBU4CDGTJFQOEK7LHIEV/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":"2026-06-09T04:30:28Z","links":{"resolver":"https://pith.science/pith/YFVB2YWBU4CDGTJFQOEK7LHIEV","bundle":"https://pith.science/pith/YFVB2YWBU4CDGTJFQOEK7LHIEV/bundle.json","state":"https://pith.science/pith/YFVB2YWBU4CDGTJFQOEK7LHIEV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YFVB2YWBU4CDGTJFQOEK7LHIEV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:YFVB2YWBU4CDGTJFQOEK7LHIEV","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":"b35ca2eb945eba8cc65263ecde89adc7b1e03fec92ae217e73b27bbba38a6250","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2018-12-18T23:43:48Z","title_canon_sha256":"244aba95725e40167e83d2ea1282d397ef5f43c1f95e4cbff415bb6805c47958"},"schema_version":"1.0","source":{"id":"1812.07699","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1812.07699","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"arxiv_version","alias_value":"1812.07699v1","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1812.07699","created_at":"2026-05-17T23:57:56Z"},{"alias_kind":"pith_short_12","alias_value":"YFVB2YWBU4CD","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"YFVB2YWBU4CDGTJF","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"YFVB2YWB","created_at":"2026-05-18T12:33:04Z"}],"graph_snapshots":[{"event_id":"sha256:e62cb8f4e2abc5f54be4def079e0918bb8eb506eec9a31ea6f3ac46577a7cfa5","target":"graph","created_at":"2026-05-17T23:57:56Z","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":"While LSTMs show increasingly promising results for forecasting Financial Time Series (FTS), this paper seeks to assess if attention mechanisms can further improve performance. The hypothesis is that attention can help prevent long-term dependencies experienced by LSTM models. To test this hypothesis, the main contribution of this paper is the implementation of an LSTM with attention. Both the benchmark LSTM and the LSTM with attention were compared and both achieved reasonable performances of up to 60% on five stocks from Kaggle's Two Sigma dataset. This comparative analysis demonstrates that","authors_text":"Antoine Viscardi, Seung Eun Yi, Thomas Hollis","cross_cats":["stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2018-12-18T23:43:48Z","title":"A Comparison of LSTMs and Attention Mechanisms for Forecasting Financial Time Series"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1812.07699","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:e3f58850b2fc3dac5e74170d0ba8ce1e4a76ecb606ce8e4883c330a20c47ebd5","target":"record","created_at":"2026-05-17T23:57:56Z","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":"b35ca2eb945eba8cc65263ecde89adc7b1e03fec92ae217e73b27bbba38a6250","cross_cats_sorted":["stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2018-12-18T23:43:48Z","title_canon_sha256":"244aba95725e40167e83d2ea1282d397ef5f43c1f95e4cbff415bb6805c47958"},"schema_version":"1.0","source":{"id":"1812.07699","kind":"arxiv","version":1}},"canonical_sha256":"c16a1d62c1a704334d258388aface82576789b17709577122742981a6cd5e943","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c16a1d62c1a704334d258388aface82576789b17709577122742981a6cd5e943","first_computed_at":"2026-05-17T23:57:56.273762Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:57:56.273762Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tZak7t9glkcqAev4/kjxzM1yhXtKKWrYl5CCQqxjTnpTDEbHrl8w9ratG5kONhTFYYBpYDKvnUl9L16RyDpOAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:57:56.274303Z","signed_message":"canonical_sha256_bytes"},"source_id":"1812.07699","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e3f58850b2fc3dac5e74170d0ba8ce1e4a76ecb606ce8e4883c330a20c47ebd5","sha256:e62cb8f4e2abc5f54be4def079e0918bb8eb506eec9a31ea6f3ac46577a7cfa5"],"state_sha256":"d1e3f5c4b093a48d10b43ef8984073ce34a4d1f72043da52199a18fb2db0c781"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fXru3loZohY5BeMi7RPyYbWK/CxfyvjhRefwnoqP2yV18pwR7UVaQXV+dxqI0MOtgj+5KzARSyTKznisnAHPCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-09T04:30:28.838068Z","bundle_sha256":"674b2c0adc101805518bd227f255c633de5c6efb703e4207d306fff4f5d3e4ff"}}