{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:NGMC6C4UD22A3X4UI6TSZUKMJZ","short_pith_number":"pith:NGMC6C4U","canonical_record":{"source":{"id":"2601.10037","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2026-01-15T03:28:28Z","cross_cats_sorted":[],"title_canon_sha256":"bff17cdb2689e2ad1dea6bffab7311885ff6c78c1139132cf0fc90c7e7ead07b","abstract_canon_sha256":"f098c75250bf1e9d5bf74220b23e953b549f62ee534ad233926712ca086b9f37"},"schema_version":"1.0"},"canonical_sha256":"69982f0b941eb40ddf9447a72cd14c4e6fdd46d2399c33c21093b4a903a0ae31","source":{"kind":"arxiv","id":"2601.10037","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.10037","created_at":"2026-07-13T00:17:06Z"},{"alias_kind":"arxiv_version","alias_value":"2601.10037v3","created_at":"2026-07-13T00:17:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.10037","created_at":"2026-07-13T00:17:06Z"},{"alias_kind":"pith_short_12","alias_value":"NGMC6C4UD22A","created_at":"2026-07-13T00:17:06Z"},{"alias_kind":"pith_short_16","alias_value":"NGMC6C4UD22A3X4U","created_at":"2026-07-13T00:17:06Z"},{"alias_kind":"pith_short_8","alias_value":"NGMC6C4U","created_at":"2026-07-13T00:17:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:NGMC6C4UD22A3X4UI6TSZUKMJZ","target":"record","payload":{"canonical_record":{"source":{"id":"2601.10037","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2026-01-15T03:28:28Z","cross_cats_sorted":[],"title_canon_sha256":"bff17cdb2689e2ad1dea6bffab7311885ff6c78c1139132cf0fc90c7e7ead07b","abstract_canon_sha256":"f098c75250bf1e9d5bf74220b23e953b549f62ee534ad233926712ca086b9f37"},"schema_version":"1.0"},"canonical_sha256":"69982f0b941eb40ddf9447a72cd14c4e6fdd46d2399c33c21093b4a903a0ae31","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-13T00:17:06.694633Z","signature_b64":"h5vFxHMtJ33MIyu5ylWMJm1+KvKdwZMVmWYFLeX/Sl+13INPT+SEIZC7BCh8NdBh8Ms1wTwD/xgWN5w3LRfQAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"69982f0b941eb40ddf9447a72cd14c4e6fdd46d2399c33c21093b4a903a0ae31","last_reissued_at":"2026-07-13T00:17:06.693361Z","signature_status":"signed_v1","first_computed_at":"2026-07-13T00:17:06.693361Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2601.10037","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-13T00:17:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BQxL6qS83PLhlNN1ewqOHFgSgEMtztrbAeImAoqb/WHfafj1fVbBFY9ZnoD21ihDQlL2fGaEVfIGJeEXVGV4BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T00:44:08.501932Z"},"content_sha256":"ede1df882f1e7b038a045c0a86a43fcc87a0ad0f9a7c674c1df3a6566bb5c1b2","schema_version":"1.0","event_id":"sha256:ede1df882f1e7b038a045c0a86a43fcc87a0ad0f9a7c674c1df3a6566bb5c1b2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:NGMC6C4UD22A3X4UI6TSZUKMJZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Parameter Efficient Machine Unlearning on Hybrid Resistive Memory based Compute-in-Memory Accelerators","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.ET","authors_text":"Chaoliang Tan, Dashan Shang, Han Wang, Jiajia Zha, Jichang Yang, Kemi Xu, Kwun Hang Wong, Leo Yu Zhang, Ning Lin, Songqi Wang, Wenxing Li, Xiaojuan Qi, Xiaoming Chen, Xinyuan Zhang, Yangu He, Yi Li, Yuxi Chen, Zhongrui Wang, Zihao Li, Zijian Ye","submitted_at":"2026-01-15T03:28:28Z","abstract_excerpt":"Resistive memory compute-in-memory accelerators provide energy efficient analogue matrix vector multiplication for neural network inference, but frequent reprogramming of analogue weights remains costly because of device variability and iterative write and verify operations. This limitation hinders their use in edge model adaptation, including approximate machine unlearning and continual learning, where model parameters may need to be updated repeatedly in response to data deletion requests or newly arriving tasks. Here we present a co-design approach across hardware and software that maps fro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.10037","kind":"arxiv","version":3},"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/2601.10037/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":"2026-07-13T00:17:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Zx6kHljwr/8Fjy313xyEyHKPLw12gu/DSQ1gA0tSZJ82AzVPph61B9igirPgzsujmZWn53fW+Eksb0zn1dviCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T00:44:08.502472Z"},"content_sha256":"6ea6bb6a1363bdd913592cc070587ade142dd0a60ff07f5e2bd2fa5f2cf92485","schema_version":"1.0","event_id":"sha256:6ea6bb6a1363bdd913592cc070587ade142dd0a60ff07f5e2bd2fa5f2cf92485"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NGMC6C4UD22A3X4UI6TSZUKMJZ/bundle.json","state_url":"https://pith.science/pith/NGMC6C4UD22A3X4UI6TSZUKMJZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NGMC6C4UD22A3X4UI6TSZUKMJZ/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":"2026-08-06T00:44:08Z","links":{"resolver":"https://pith.science/pith/NGMC6C4UD22A3X4UI6TSZUKMJZ","bundle":"https://pith.science/pith/NGMC6C4UD22A3X4UI6TSZUKMJZ/bundle.json","state":"https://pith.science/pith/NGMC6C4UD22A3X4UI6TSZUKMJZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NGMC6C4UD22A3X4UI6TSZUKMJZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:NGMC6C4UD22A3X4UI6TSZUKMJZ","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":"f098c75250bf1e9d5bf74220b23e953b549f62ee534ad233926712ca086b9f37","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2026-01-15T03:28:28Z","title_canon_sha256":"bff17cdb2689e2ad1dea6bffab7311885ff6c78c1139132cf0fc90c7e7ead07b"},"schema_version":"1.0","source":{"id":"2601.10037","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.10037","created_at":"2026-07-13T00:17:06Z"},{"alias_kind":"arxiv_version","alias_value":"2601.10037v3","created_at":"2026-07-13T00:17:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.10037","created_at":"2026-07-13T00:17:06Z"},{"alias_kind":"pith_short_12","alias_value":"NGMC6C4UD22A","created_at":"2026-07-13T00:17:06Z"},{"alias_kind":"pith_short_16","alias_value":"NGMC6C4UD22A3X4U","created_at":"2026-07-13T00:17:06Z"},{"alias_kind":"pith_short_8","alias_value":"NGMC6C4U","created_at":"2026-07-13T00:17:06Z"}],"graph_snapshots":[{"event_id":"sha256:6ea6bb6a1363bdd913592cc070587ade142dd0a60ff07f5e2bd2fa5f2cf92485","target":"graph","created_at":"2026-07-13T00:17:06Z","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/2601.10037/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Resistive memory compute-in-memory accelerators provide energy efficient analogue matrix vector multiplication for neural network inference, but frequent reprogramming of analogue weights remains costly because of device variability and iterative write and verify operations. This limitation hinders their use in edge model adaptation, including approximate machine unlearning and continual learning, where model parameters may need to be updated repeatedly in response to data deletion requests or newly arriving tasks. Here we present a co-design approach across hardware and software that maps fro","authors_text":"Chaoliang Tan, Dashan Shang, Han Wang, Jiajia Zha, Jichang Yang, Kemi Xu, Kwun Hang Wong, Leo Yu Zhang, Ning Lin, Songqi Wang, Wenxing Li, Xiaojuan Qi, Xiaoming Chen, Xinyuan Zhang, Yangu He, Yi Li, Yuxi Chen, Zhongrui Wang, Zihao Li, Zijian Ye","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2026-01-15T03:28:28Z","title":"Parameter Efficient Machine Unlearning on Hybrid Resistive Memory based Compute-in-Memory Accelerators"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.10037","kind":"arxiv","version":3},"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:ede1df882f1e7b038a045c0a86a43fcc87a0ad0f9a7c674c1df3a6566bb5c1b2","target":"record","created_at":"2026-07-13T00:17:06Z","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":"f098c75250bf1e9d5bf74220b23e953b549f62ee534ad233926712ca086b9f37","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2026-01-15T03:28:28Z","title_canon_sha256":"bff17cdb2689e2ad1dea6bffab7311885ff6c78c1139132cf0fc90c7e7ead07b"},"schema_version":"1.0","source":{"id":"2601.10037","kind":"arxiv","version":3}},"canonical_sha256":"69982f0b941eb40ddf9447a72cd14c4e6fdd46d2399c33c21093b4a903a0ae31","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"69982f0b941eb40ddf9447a72cd14c4e6fdd46d2399c33c21093b4a903a0ae31","first_computed_at":"2026-07-13T00:17:06.693361Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-13T00:17:06.693361Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"h5vFxHMtJ33MIyu5ylWMJm1+KvKdwZMVmWYFLeX/Sl+13INPT+SEIZC7BCh8NdBh8Ms1wTwD/xgWN5w3LRfQAw==","signature_status":"signed_v1","signed_at":"2026-07-13T00:17:06.694633Z","signed_message":"canonical_sha256_bytes"},"source_id":"2601.10037","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ede1df882f1e7b038a045c0a86a43fcc87a0ad0f9a7c674c1df3a6566bb5c1b2","sha256:6ea6bb6a1363bdd913592cc070587ade142dd0a60ff07f5e2bd2fa5f2cf92485"],"state_sha256":"07e3901e9217f2ecc1fed58fbcd2601f1c3ec0ecf95b5d379da19ba505f2e7e6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b7j96oGW4Jbf0irlF+ZnHPDQjx9nIgJFXksOmQUCZDwWjD3p+t7ld+nmzKBL3EpY3uhxF75axa1Xzo2W3pCkAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T00:44:08.508756Z","bundle_sha256":"781954668bd12012f3c01be11f69592660ac1da351d617e2df19fc0f115a26e8"}}