{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:5DHDBSHCLHEFG7ERQDX5WZBFWN","short_pith_number":"pith:5DHDBSHC","canonical_record":{"source":{"id":"2107.04688","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-07-09T21:24:49Z","cross_cats_sorted":[],"title_canon_sha256":"97013301c1aa92e7f19149f3493ccbd79eff14bb2855d4f33cc56a3e35518119","abstract_canon_sha256":"e1dbbf0d69cc89cbf27a709ffe39f89a5d77dfea66fee5bf560d3d79589db734"},"schema_version":"1.0"},"canonical_sha256":"e8ce30c8e259c8537c9180efdb6425b348db7e72cd1ce1c4ce746acb8b447eaa","source":{"kind":"arxiv","id":"2107.04688","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.04688","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"arxiv_version","alias_value":"2107.04688v1","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.04688","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"pith_short_12","alias_value":"5DHDBSHCLHEF","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"pith_short_16","alias_value":"5DHDBSHCLHEFG7ER","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"pith_short_8","alias_value":"5DHDBSHC","created_at":"2026-07-05T02:56:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:5DHDBSHCLHEFG7ERQDX5WZBFWN","target":"record","payload":{"canonical_record":{"source":{"id":"2107.04688","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-07-09T21:24:49Z","cross_cats_sorted":[],"title_canon_sha256":"97013301c1aa92e7f19149f3493ccbd79eff14bb2855d4f33cc56a3e35518119","abstract_canon_sha256":"e1dbbf0d69cc89cbf27a709ffe39f89a5d77dfea66fee5bf560d3d79589db734"},"schema_version":"1.0"},"canonical_sha256":"e8ce30c8e259c8537c9180efdb6425b348db7e72cd1ce1c4ce746acb8b447eaa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:56:41.621445Z","signature_b64":"5PQp4yAhv3ALyQABE70I6L1PeQQ4rm7gBPxQj4J2eZHUBXJXnhwU9YHdzuT+RObvoXCQO0ZXRa2yMEk+stjTCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e8ce30c8e259c8537c9180efdb6425b348db7e72cd1ce1c4ce746acb8b447eaa","last_reissued_at":"2026-07-05T02:56:41.621034Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:56:41.621034Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2107.04688","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":"2026-07-05T02:56:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NeaqI2eAxj7hFXBOX6Zn3X7jwYMKWWcRefSt5+k5Snjx5E7oDdEa7wyycbNfkZCKM0BjHFDCSrC33vSnnqbxAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-18T12:55:11.646603Z"},"content_sha256":"3ab1adb4b1c9acd4aae162c06f1f5acef493c765cf8f1cdc348efd4d08788967","schema_version":"1.0","event_id":"sha256:3ab1adb4b1c9acd4aae162c06f1f5acef493c765cf8f1cdc348efd4d08788967"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:5DHDBSHCLHEFG7ERQDX5WZBFWN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scaled-Time-Attention Robust Edge Network","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Devin Ridge, Justin Wong, Lihan Yao, Michael Fletcher, Richard Lau, Stephen Arleth, Todd Huster, William C. Headley, William Johnson","submitted_at":"2021-07-09T21:24:49Z","abstract_excerpt":"This paper describes a systematic approach towards building a new family of neural networks based on a delay-loop version of a reservoir neural network. The resulting architecture, called Scaled-Time-Attention Robust Edge (STARE) network, exploits hyper dimensional space and non-multiply-and-add computation to achieve a simpler architecture, which has shallow layers, is simple to train, and is better suited for Edge applications, such as Internet of Things (IoT), over traditional deep neural networks. STARE incorporates new AI concepts such as Attention and Context, and is best suited for temp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.04688","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2107.04688/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T02:56:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2mxUWjS+Atpvo1H3Ht8dWCRxyp0nxzVshA6XTOGTigyFYe5pmaJg7QGhQNlPeb9u05gxd9ZI0ZOCsU6mwsI/CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-18T12:55:11.646967Z"},"content_sha256":"fed00656cca26122da69bc700e7c502b1bd64d5c91b5455fb01fa1d905e61b7a","schema_version":"1.0","event_id":"sha256:fed00656cca26122da69bc700e7c502b1bd64d5c91b5455fb01fa1d905e61b7a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5DHDBSHCLHEFG7ERQDX5WZBFWN/bundle.json","state_url":"https://pith.science/pith/5DHDBSHCLHEFG7ERQDX5WZBFWN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5DHDBSHCLHEFG7ERQDX5WZBFWN/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":"2026-07-18T12:55:11Z","links":{"resolver":"https://pith.science/pith/5DHDBSHCLHEFG7ERQDX5WZBFWN","bundle":"https://pith.science/pith/5DHDBSHCLHEFG7ERQDX5WZBFWN/bundle.json","state":"https://pith.science/pith/5DHDBSHCLHEFG7ERQDX5WZBFWN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5DHDBSHCLHEFG7ERQDX5WZBFWN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:5DHDBSHCLHEFG7ERQDX5WZBFWN","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":"e1dbbf0d69cc89cbf27a709ffe39f89a5d77dfea66fee5bf560d3d79589db734","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-07-09T21:24:49Z","title_canon_sha256":"97013301c1aa92e7f19149f3493ccbd79eff14bb2855d4f33cc56a3e35518119"},"schema_version":"1.0","source":{"id":"2107.04688","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2107.04688","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"arxiv_version","alias_value":"2107.04688v1","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2107.04688","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"pith_short_12","alias_value":"5DHDBSHCLHEF","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"pith_short_16","alias_value":"5DHDBSHCLHEFG7ER","created_at":"2026-07-05T02:56:41Z"},{"alias_kind":"pith_short_8","alias_value":"5DHDBSHC","created_at":"2026-07-05T02:56:41Z"}],"graph_snapshots":[{"event_id":"sha256:fed00656cca26122da69bc700e7c502b1bd64d5c91b5455fb01fa1d905e61b7a","target":"graph","created_at":"2026-07-05T02:56:41Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2107.04688/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper describes a systematic approach towards building a new family of neural networks based on a delay-loop version of a reservoir neural network. The resulting architecture, called Scaled-Time-Attention Robust Edge (STARE) network, exploits hyper dimensional space and non-multiply-and-add computation to achieve a simpler architecture, which has shallow layers, is simple to train, and is better suited for Edge applications, such as Internet of Things (IoT), over traditional deep neural networks. STARE incorporates new AI concepts such as Attention and Context, and is best suited for temp","authors_text":"Devin Ridge, Justin Wong, Lihan Yao, Michael Fletcher, Richard Lau, Stephen Arleth, Todd Huster, William C. Headley, William Johnson","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-07-09T21:24:49Z","title":"Scaled-Time-Attention Robust Edge Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2107.04688","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":"sha256:3ab1adb4b1c9acd4aae162c06f1f5acef493c765cf8f1cdc348efd4d08788967","target":"record","created_at":"2026-07-05T02:56:41Z","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":"e1dbbf0d69cc89cbf27a709ffe39f89a5d77dfea66fee5bf560d3d79589db734","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2021-07-09T21:24:49Z","title_canon_sha256":"97013301c1aa92e7f19149f3493ccbd79eff14bb2855d4f33cc56a3e35518119"},"schema_version":"1.0","source":{"id":"2107.04688","kind":"arxiv","version":1}},"canonical_sha256":"e8ce30c8e259c8537c9180efdb6425b348db7e72cd1ce1c4ce746acb8b447eaa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e8ce30c8e259c8537c9180efdb6425b348db7e72cd1ce1c4ce746acb8b447eaa","first_computed_at":"2026-07-05T02:56:41.621034Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:56:41.621034Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5PQp4yAhv3ALyQABE70I6L1PeQQ4rm7gBPxQj4J2eZHUBXJXnhwU9YHdzuT+RObvoXCQO0ZXRa2yMEk+stjTCg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:56:41.621445Z","signed_message":"canonical_sha256_bytes"},"source_id":"2107.04688","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3ab1adb4b1c9acd4aae162c06f1f5acef493c765cf8f1cdc348efd4d08788967","sha256:fed00656cca26122da69bc700e7c502b1bd64d5c91b5455fb01fa1d905e61b7a"],"state_sha256":"4cc928120d06c92855695470a9351e3252bf5a792cbdf0b01200c882cf9dd50c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y3Gfb3Hgs/Roi9eZsrZ1Wb1uhkvJ/FuwUvzK+iycsrmUIP/7w2kBJCRGwt+7cg0DDFi7roRp8E6qv7IoC8dpDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-18T12:55:11.649445Z","bundle_sha256":"4ee4cb99e4711ec62e7f69c58959dfcf4e56539004c6e92cf7b61e1a05f01bed"}}