{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:5SQGH7C6FNGGTBNNIOICJENJJD","short_pith_number":"pith:5SQGH7C6","canonical_record":{"source":{"id":"1806.02366","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2018-06-06T18:14:59Z","cross_cats_sorted":[],"title_canon_sha256":"ee118599f82cf8345dc72c6659eb9086519c0f9e9641cbb0cb61527536ed0540","abstract_canon_sha256":"9e0bb5d58853c7f2c40fe22fafa1807d800891e73190ff5d10f2608b823a6653"},"schema_version":"1.0"},"canonical_sha256":"eca063fc5e2b4c6985ad43902491a948cdfcd278eba9f5975b2550381a421410","source":{"kind":"arxiv","id":"1806.02366","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.02366","created_at":"2026-05-18T00:13:57Z"},{"alias_kind":"arxiv_version","alias_value":"1806.02366v1","created_at":"2026-05-18T00:13:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.02366","created_at":"2026-05-18T00:13:57Z"},{"alias_kind":"pith_short_12","alias_value":"5SQGH7C6FNGG","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_16","alias_value":"5SQGH7C6FNGGTBNN","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_8","alias_value":"5SQGH7C6","created_at":"2026-05-18T12:32:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:5SQGH7C6FNGGTBNNIOICJENJJD","target":"record","payload":{"canonical_record":{"source":{"id":"1806.02366","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2018-06-06T18:14:59Z","cross_cats_sorted":[],"title_canon_sha256":"ee118599f82cf8345dc72c6659eb9086519c0f9e9641cbb0cb61527536ed0540","abstract_canon_sha256":"9e0bb5d58853c7f2c40fe22fafa1807d800891e73190ff5d10f2608b823a6653"},"schema_version":"1.0"},"canonical_sha256":"eca063fc5e2b4c6985ad43902491a948cdfcd278eba9f5975b2550381a421410","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:13:57.117125Z","signature_b64":"viJc/CUSavLuKyxIm7NwF1IYctYxaZdxSiaJ4XgjyyqyDwtbeJic1k1A0Onr0mtxxAmVKQDmeHM2Z57GrZivCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eca063fc5e2b4c6985ad43902491a948cdfcd278eba9f5975b2550381a421410","last_reissued_at":"2026-05-18T00:13:57.116497Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:13:57.116497Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.02366","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":"2026-05-18T00:13:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PyGVnPeyX9A5P8hLfbbREV67SAzCalXgRcZHaM/rqzdJ15iV7XAexklwt317l6f/PbJ4nUKb5RHW9HAPNkdVBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T21:01:09.656700Z"},"content_sha256":"d7dd9b96d676ec97c6ffac3012332ee197df632d369dc9b05215799ffeabed30","schema_version":"1.0","event_id":"sha256:d7dd9b96d676ec97c6ffac3012332ee197df632d369dc9b05215799ffeabed30"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:5SQGH7C6FNGGTBNNIOICJENJJD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Design of CMOS-memristor Circuits for LSTM architecture","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.ET","authors_text":"Alex Pappachen James, Kamilya Smagulova, Kazybek Adam, Olga Krestinskaya","submitted_at":"2018-06-06T18:14:59Z","abstract_excerpt":"Long Short-Term memory (LSTM) architecture is a well-known approach for building recurrent neural networks (RNN) useful in sequential processing of data in application to natural language processing. The near-sensor hardware implementation of LSTM is challenged due to large parallelism and complexity. We propose a 0.18 m CMOS, GST memristor LSTM hardware architecture for near-sensor processing. The proposed system is validated in a forecasting problem based on Keras model."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.02366","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":"2026-05-18T00:13:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Clqdtsgzk6e7z69FY2R/ZAU3o1R4PJaYw2Kyd9eSTI0E4jCFMh5bvs8ftOuBsrwSEmwGj0Vy3R7DYf/xXbygAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T21:01:09.657395Z"},"content_sha256":"a3178f51814c0065e87f8f30fd9ba987f9180d04bbcfbc57ad855aaea45dc8b6","schema_version":"1.0","event_id":"sha256:a3178f51814c0065e87f8f30fd9ba987f9180d04bbcfbc57ad855aaea45dc8b6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5SQGH7C6FNGGTBNNIOICJENJJD/bundle.json","state_url":"https://pith.science/pith/5SQGH7C6FNGGTBNNIOICJENJJD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5SQGH7C6FNGGTBNNIOICJENJJD/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":"2026-06-08T21:01:09Z","links":{"resolver":"https://pith.science/pith/5SQGH7C6FNGGTBNNIOICJENJJD","bundle":"https://pith.science/pith/5SQGH7C6FNGGTBNNIOICJENJJD/bundle.json","state":"https://pith.science/pith/5SQGH7C6FNGGTBNNIOICJENJJD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5SQGH7C6FNGGTBNNIOICJENJJD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:5SQGH7C6FNGGTBNNIOICJENJJD","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":"9e0bb5d58853c7f2c40fe22fafa1807d800891e73190ff5d10f2608b823a6653","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2018-06-06T18:14:59Z","title_canon_sha256":"ee118599f82cf8345dc72c6659eb9086519c0f9e9641cbb0cb61527536ed0540"},"schema_version":"1.0","source":{"id":"1806.02366","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.02366","created_at":"2026-05-18T00:13:57Z"},{"alias_kind":"arxiv_version","alias_value":"1806.02366v1","created_at":"2026-05-18T00:13:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.02366","created_at":"2026-05-18T00:13:57Z"},{"alias_kind":"pith_short_12","alias_value":"5SQGH7C6FNGG","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_16","alias_value":"5SQGH7C6FNGGTBNN","created_at":"2026-05-18T12:32:08Z"},{"alias_kind":"pith_short_8","alias_value":"5SQGH7C6","created_at":"2026-05-18T12:32:08Z"}],"graph_snapshots":[{"event_id":"sha256:a3178f51814c0065e87f8f30fd9ba987f9180d04bbcfbc57ad855aaea45dc8b6","target":"graph","created_at":"2026-05-18T00:13:57Z","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":"Long Short-Term memory (LSTM) architecture is a well-known approach for building recurrent neural networks (RNN) useful in sequential processing of data in application to natural language processing. The near-sensor hardware implementation of LSTM is challenged due to large parallelism and complexity. We propose a 0.18 m CMOS, GST memristor LSTM hardware architecture for near-sensor processing. The proposed system is validated in a forecasting problem based on Keras model.","authors_text":"Alex Pappachen James, Kamilya Smagulova, Kazybek Adam, Olga Krestinskaya","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2018-06-06T18:14:59Z","title":"Design of CMOS-memristor Circuits for LSTM architecture"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.02366","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:d7dd9b96d676ec97c6ffac3012332ee197df632d369dc9b05215799ffeabed30","target":"record","created_at":"2026-05-18T00:13:57Z","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":"9e0bb5d58853c7f2c40fe22fafa1807d800891e73190ff5d10f2608b823a6653","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2018-06-06T18:14:59Z","title_canon_sha256":"ee118599f82cf8345dc72c6659eb9086519c0f9e9641cbb0cb61527536ed0540"},"schema_version":"1.0","source":{"id":"1806.02366","kind":"arxiv","version":1}},"canonical_sha256":"eca063fc5e2b4c6985ad43902491a948cdfcd278eba9f5975b2550381a421410","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eca063fc5e2b4c6985ad43902491a948cdfcd278eba9f5975b2550381a421410","first_computed_at":"2026-05-18T00:13:57.116497Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:13:57.116497Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"viJc/CUSavLuKyxIm7NwF1IYctYxaZdxSiaJ4XgjyyqyDwtbeJic1k1A0Onr0mtxxAmVKQDmeHM2Z57GrZivCw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:13:57.117125Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.02366","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d7dd9b96d676ec97c6ffac3012332ee197df632d369dc9b05215799ffeabed30","sha256:a3178f51814c0065e87f8f30fd9ba987f9180d04bbcfbc57ad855aaea45dc8b6"],"state_sha256":"3dc3004b7d95b363295f2eef12ad62cd9fc9f9f35c43db69fd49f516bf9a2e26"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E9CByj2R2gtnyt+fVy3Ftav45zmG8SpqMrWPnm5DgrbBkufyUMZ7yiFagBIpGQNPz6gWAEm6cQc5iAOJb9z/Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T21:01:09.661810Z","bundle_sha256":"965a24ecfea75105e837f7a93cb381bd41ab99659db036c734ab9f8a054297ec"}}