{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:KYXD3G2PWJMHWCXMVI3OR4VOJV","short_pith_number":"pith:KYXD3G2P","canonical_record":{"source":{"id":"2203.04894","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-09T17:20:12Z","cross_cats_sorted":[],"title_canon_sha256":"d0b442d6b5ece15dee8143b7364e155291a48fef095a2455285372dab6c12c8d","abstract_canon_sha256":"e0df51922865ca62885d5735aed2961b39eccf0a0e6243a10fe4b1a133575d3d"},"schema_version":"1.0"},"canonical_sha256":"562e3d9b4fb2587b0aecaa36e8f2ae4d6161185dcb55c7da32326f40f018915d","source":{"kind":"arxiv","id":"2203.04894","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.04894","created_at":"2026-07-05T04:10:40Z"},{"alias_kind":"arxiv_version","alias_value":"2203.04894v2","created_at":"2026-07-05T04:10:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.04894","created_at":"2026-07-05T04:10:40Z"},{"alias_kind":"pith_short_12","alias_value":"KYXD3G2PWJMH","created_at":"2026-07-05T04:10:40Z"},{"alias_kind":"pith_short_16","alias_value":"KYXD3G2PWJMHWCXM","created_at":"2026-07-05T04:10:40Z"},{"alias_kind":"pith_short_8","alias_value":"KYXD3G2P","created_at":"2026-07-05T04:10:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:KYXD3G2PWJMHWCXMVI3OR4VOJV","target":"record","payload":{"canonical_record":{"source":{"id":"2203.04894","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-09T17:20:12Z","cross_cats_sorted":[],"title_canon_sha256":"d0b442d6b5ece15dee8143b7364e155291a48fef095a2455285372dab6c12c8d","abstract_canon_sha256":"e0df51922865ca62885d5735aed2961b39eccf0a0e6243a10fe4b1a133575d3d"},"schema_version":"1.0"},"canonical_sha256":"562e3d9b4fb2587b0aecaa36e8f2ae4d6161185dcb55c7da32326f40f018915d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:10:40.044029Z","signature_b64":"AW5E8aO/T/kl849qEpG4l5H8aighjrYSY+LP6rEreQ+qsEQCAfrRhPg+Qh3S0TDxk0Dq7Kjjs12jcyFlex9qCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"562e3d9b4fb2587b0aecaa36e8f2ae4d6161185dcb55c7da32326f40f018915d","last_reissued_at":"2026-07-05T04:10:40.043498Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:10:40.043498Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.04894","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":"2026-07-05T04:10:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WZUC5g7vZZrR2WqVx3t3X//luXfUredvJNjhNkx95RwybT5Ha37FguMQOxkhepwvJE7hVCIXRvIY1O+iPnWTCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T22:39:24.630816Z"},"content_sha256":"651c0249139b992b5f1a8de3a74085420493e7b6b10faf1a764b15720de58d78","schema_version":"1.0","event_id":"sha256:651c0249139b992b5f1a8de3a74085420493e7b6b10faf1a764b15720de58d78"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:KYXD3G2PWJMHWCXMVI3OR4VOJV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Brain-Inspired Low-Dimensional Computing Classifier for Inference on Tiny Devices","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Shaolei Ren, Shijin Duan, Xiaolin Xu","submitted_at":"2022-03-09T17:20:12Z","abstract_excerpt":"By mimicking brain-like cognition and exploiting parallelism, hyperdimensional computing (HDC) classifiers have been emerging as a lightweight framework to achieve efficient on-device inference. Nonetheless, they have two fundamental drawbacks, heuristic training process and ultra-high dimension, which result in sub-optimal inference accuracy and large model sizes beyond the capability of tiny devices with stringent resource constraints. In this paper, we address these fundamental drawbacks and propose a low-dimensional computing (LDC) alternative. Specifically, by mapping our LDC classifier i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.04894","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2203.04894/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":"2026-07-05T04:10:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RAjn5nAEeeLJ8HlqTBdJL73Sw6Ueq98zPJEafU+N8Jh9TriPnHLT7dWDNPJlsqBv6Khb5Hnhhh4fhxGM8BL9Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T22:39:24.631527Z"},"content_sha256":"022d9bc85104366262fb108f514045dfb059549d69c85df529d1cd13cfcd5b4f","schema_version":"1.0","event_id":"sha256:022d9bc85104366262fb108f514045dfb059549d69c85df529d1cd13cfcd5b4f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KYXD3G2PWJMHWCXMVI3OR4VOJV/bundle.json","state_url":"https://pith.science/pith/KYXD3G2PWJMHWCXMVI3OR4VOJV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KYXD3G2PWJMHWCXMVI3OR4VOJV/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":"2026-08-16T22:39:24Z","links":{"resolver":"https://pith.science/pith/KYXD3G2PWJMHWCXMVI3OR4VOJV","bundle":"https://pith.science/pith/KYXD3G2PWJMHWCXMVI3OR4VOJV/bundle.json","state":"https://pith.science/pith/KYXD3G2PWJMHWCXMVI3OR4VOJV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KYXD3G2PWJMHWCXMVI3OR4VOJV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:KYXD3G2PWJMHWCXMVI3OR4VOJV","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":"e0df51922865ca62885d5735aed2961b39eccf0a0e6243a10fe4b1a133575d3d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-09T17:20:12Z","title_canon_sha256":"d0b442d6b5ece15dee8143b7364e155291a48fef095a2455285372dab6c12c8d"},"schema_version":"1.0","source":{"id":"2203.04894","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.04894","created_at":"2026-07-05T04:10:40Z"},{"alias_kind":"arxiv_version","alias_value":"2203.04894v2","created_at":"2026-07-05T04:10:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.04894","created_at":"2026-07-05T04:10:40Z"},{"alias_kind":"pith_short_12","alias_value":"KYXD3G2PWJMH","created_at":"2026-07-05T04:10:40Z"},{"alias_kind":"pith_short_16","alias_value":"KYXD3G2PWJMHWCXM","created_at":"2026-07-05T04:10:40Z"},{"alias_kind":"pith_short_8","alias_value":"KYXD3G2P","created_at":"2026-07-05T04:10:40Z"}],"graph_snapshots":[{"event_id":"sha256:022d9bc85104366262fb108f514045dfb059549d69c85df529d1cd13cfcd5b4f","target":"graph","created_at":"2026-07-05T04:10:40Z","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/2203.04894/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"By mimicking brain-like cognition and exploiting parallelism, hyperdimensional computing (HDC) classifiers have been emerging as a lightweight framework to achieve efficient on-device inference. Nonetheless, they have two fundamental drawbacks, heuristic training process and ultra-high dimension, which result in sub-optimal inference accuracy and large model sizes beyond the capability of tiny devices with stringent resource constraints. In this paper, we address these fundamental drawbacks and propose a low-dimensional computing (LDC) alternative. Specifically, by mapping our LDC classifier i","authors_text":"Shaolei Ren, Shijin Duan, Xiaolin Xu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-09T17:20:12Z","title":"A Brain-Inspired Low-Dimensional Computing Classifier for Inference on Tiny Devices"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.04894","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":"sha256:651c0249139b992b5f1a8de3a74085420493e7b6b10faf1a764b15720de58d78","target":"record","created_at":"2026-07-05T04:10:40Z","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":"e0df51922865ca62885d5735aed2961b39eccf0a0e6243a10fe4b1a133575d3d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-03-09T17:20:12Z","title_canon_sha256":"d0b442d6b5ece15dee8143b7364e155291a48fef095a2455285372dab6c12c8d"},"schema_version":"1.0","source":{"id":"2203.04894","kind":"arxiv","version":2}},"canonical_sha256":"562e3d9b4fb2587b0aecaa36e8f2ae4d6161185dcb55c7da32326f40f018915d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"562e3d9b4fb2587b0aecaa36e8f2ae4d6161185dcb55c7da32326f40f018915d","first_computed_at":"2026-07-05T04:10:40.043498Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:10:40.043498Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AW5E8aO/T/kl849qEpG4l5H8aighjrYSY+LP6rEreQ+qsEQCAfrRhPg+Qh3S0TDxk0Dq7Kjjs12jcyFlex9qCg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:10:40.044029Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.04894","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:651c0249139b992b5f1a8de3a74085420493e7b6b10faf1a764b15720de58d78","sha256:022d9bc85104366262fb108f514045dfb059549d69c85df529d1cd13cfcd5b4f"],"state_sha256":"3bfd1ecb0a05fb5e454d6aedfe8e93821ba6bde419013bb1fe140ecc4283b2c6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VWV8TuE4oTocolh8DRCzO1kUz36rHxJ35A5TgPH4nbFt++CTtYr4NiN6Hib6q4Y/mnhoFrRkK791sVLp6VI7CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T22:39:24.635833Z","bundle_sha256":"e9cc8d86c3015eb45106f9631261f3b5d929eaebaed7aff84e0153f4a033701e"}}