{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2015:YXSSL3BGQ6DNJQWGOEDRBRKD7Z","short_pith_number":"pith:YXSSL3BG","canonical_record":{"source":{"id":"1511.09085","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2015-11-29T20:27:15Z","cross_cats_sorted":["cs.AR"],"title_canon_sha256":"0e790334046ce4662f6e4177054e99c2c93685160b4dddb9633fda8210f788e6","abstract_canon_sha256":"2334f4fbca3a0f0d664c29e36701dbbb5b61f78a9d373d624870f650057419ce"},"schema_version":"1.0"},"canonical_sha256":"c5e525ec268786d4c2c6710710c543fe6dc0edb7a092dff98ce592fe129acb8f","source":{"kind":"arxiv","id":"1511.09085","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1511.09085","created_at":"2026-05-18T01:25:33Z"},{"alias_kind":"arxiv_version","alias_value":"1511.09085v2","created_at":"2026-05-18T01:25:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.09085","created_at":"2026-05-18T01:25:33Z"},{"alias_kind":"pith_short_12","alias_value":"YXSSL3BGQ6DN","created_at":"2026-05-18T12:29:52Z"},{"alias_kind":"pith_short_16","alias_value":"YXSSL3BGQ6DNJQWG","created_at":"2026-05-18T12:29:52Z"},{"alias_kind":"pith_short_8","alias_value":"YXSSL3BG","created_at":"2026-05-18T12:29:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2015:YXSSL3BGQ6DNJQWGOEDRBRKD7Z","target":"record","payload":{"canonical_record":{"source":{"id":"1511.09085","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2015-11-29T20:27:15Z","cross_cats_sorted":["cs.AR"],"title_canon_sha256":"0e790334046ce4662f6e4177054e99c2c93685160b4dddb9633fda8210f788e6","abstract_canon_sha256":"2334f4fbca3a0f0d664c29e36701dbbb5b61f78a9d373d624870f650057419ce"},"schema_version":"1.0"},"canonical_sha256":"c5e525ec268786d4c2c6710710c543fe6dc0edb7a092dff98ce592fe129acb8f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:25:33.070601Z","signature_b64":"fqQFpcrjVDOTqoWO4obhHiTVWguMt2dhTZCKMPDVAIvUH18k38DBwqtZBwioUZcq+bGbBPqrwbeB5Z80QQRSCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c5e525ec268786d4c2c6710710c543fe6dc0edb7a092dff98ce592fe129acb8f","last_reissued_at":"2026-05-18T01:25:33.070153Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:25:33.070153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1511.09085","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":"2026-05-18T01:25:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E7lnq2FePC1lsCaU9uqT9Wvv9pZtuCLLXe5QWl7SqUrhOUeHRnyWWkhNDOVgzvMJe1Bl3M/K3zde3pbfwF8LBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T17:03:29.780262Z"},"content_sha256":"9af3a86db209aa8772e1f5d3ae99ac9dd53d418014706a00e2467fd6e60d6cd5","schema_version":"1.0","event_id":"sha256:9af3a86db209aa8772e1f5d3ae99ac9dd53d418014706a00e2467fd6e60d6cd5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2015:YXSSL3BGQ6DNJQWGOEDRBRKD7Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Energy Efficient and High Performance Current-Mode Neural Network Circuit using Memristors and Digitally Assisted Analog CMOS Neurons","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AR"],"primary_cat":"cs.ET","authors_text":"Aranya Goswamy, Kaushik Roy, Manny Jain, Mrigank Sharad, Sagar Kumashi, Siddharth Kumar Singh, Vikash Sehwag","submitted_at":"2015-11-29T20:27:15Z","abstract_excerpt":"Emerging nano-scale programmable Resistive-RAM (RRAM) has been identified as a promising technology for implementing brain-inspired computing hardware. Several neural network architectures, that essentially involve computation of scalar products between input data vectors and stored network weights can be efficiently implemented using high density cross-bar arrays of RRAM integrated with CMOS. In such a design, the CMOS interface may be responsible for providing input excitations and for processing the RRAM output. In order to achieve high energy efficiency along with high integration density "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.09085","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":""},"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":"2026-05-18T01:25:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"407XIhEdaUhiWZVQjfo9mBu/dTK1tX1gsc0C7Foe5dD+lz4sgDT12S8Nb/u/CXa/+ruLvybmL/ci8kIXC4EyCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T17:03:29.780918Z"},"content_sha256":"d95fbabd4a41a385c5e91de6a446165856d121f739a9a8a562e8e08d9744b60a","schema_version":"1.0","event_id":"sha256:d95fbabd4a41a385c5e91de6a446165856d121f739a9a8a562e8e08d9744b60a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YXSSL3BGQ6DNJQWGOEDRBRKD7Z/bundle.json","state_url":"https://pith.science/pith/YXSSL3BGQ6DNJQWGOEDRBRKD7Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YXSSL3BGQ6DNJQWGOEDRBRKD7Z/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":"2026-05-25T17:03:29Z","links":{"resolver":"https://pith.science/pith/YXSSL3BGQ6DNJQWGOEDRBRKD7Z","bundle":"https://pith.science/pith/YXSSL3BGQ6DNJQWGOEDRBRKD7Z/bundle.json","state":"https://pith.science/pith/YXSSL3BGQ6DNJQWGOEDRBRKD7Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YXSSL3BGQ6DNJQWGOEDRBRKD7Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2015:YXSSL3BGQ6DNJQWGOEDRBRKD7Z","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":"2334f4fbca3a0f0d664c29e36701dbbb5b61f78a9d373d624870f650057419ce","cross_cats_sorted":["cs.AR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2015-11-29T20:27:15Z","title_canon_sha256":"0e790334046ce4662f6e4177054e99c2c93685160b4dddb9633fda8210f788e6"},"schema_version":"1.0","source":{"id":"1511.09085","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1511.09085","created_at":"2026-05-18T01:25:33Z"},{"alias_kind":"arxiv_version","alias_value":"1511.09085v2","created_at":"2026-05-18T01:25:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1511.09085","created_at":"2026-05-18T01:25:33Z"},{"alias_kind":"pith_short_12","alias_value":"YXSSL3BGQ6DN","created_at":"2026-05-18T12:29:52Z"},{"alias_kind":"pith_short_16","alias_value":"YXSSL3BGQ6DNJQWG","created_at":"2026-05-18T12:29:52Z"},{"alias_kind":"pith_short_8","alias_value":"YXSSL3BG","created_at":"2026-05-18T12:29:52Z"}],"graph_snapshots":[{"event_id":"sha256:d95fbabd4a41a385c5e91de6a446165856d121f739a9a8a562e8e08d9744b60a","target":"graph","created_at":"2026-05-18T01:25:33Z","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":"Emerging nano-scale programmable Resistive-RAM (RRAM) has been identified as a promising technology for implementing brain-inspired computing hardware. Several neural network architectures, that essentially involve computation of scalar products between input data vectors and stored network weights can be efficiently implemented using high density cross-bar arrays of RRAM integrated with CMOS. In such a design, the CMOS interface may be responsible for providing input excitations and for processing the RRAM output. In order to achieve high energy efficiency along with high integration density ","authors_text":"Aranya Goswamy, Kaushik Roy, Manny Jain, Mrigank Sharad, Sagar Kumashi, Siddharth Kumar Singh, Vikash Sehwag","cross_cats":["cs.AR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2015-11-29T20:27:15Z","title":"Energy Efficient and High Performance Current-Mode Neural Network Circuit using Memristors and Digitally Assisted Analog CMOS Neurons"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1511.09085","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":"sha256:9af3a86db209aa8772e1f5d3ae99ac9dd53d418014706a00e2467fd6e60d6cd5","target":"record","created_at":"2026-05-18T01:25:33Z","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":"2334f4fbca3a0f0d664c29e36701dbbb5b61f78a9d373d624870f650057419ce","cross_cats_sorted":["cs.AR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.ET","submitted_at":"2015-11-29T20:27:15Z","title_canon_sha256":"0e790334046ce4662f6e4177054e99c2c93685160b4dddb9633fda8210f788e6"},"schema_version":"1.0","source":{"id":"1511.09085","kind":"arxiv","version":2}},"canonical_sha256":"c5e525ec268786d4c2c6710710c543fe6dc0edb7a092dff98ce592fe129acb8f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c5e525ec268786d4c2c6710710c543fe6dc0edb7a092dff98ce592fe129acb8f","first_computed_at":"2026-05-18T01:25:33.070153Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:25:33.070153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fqQFpcrjVDOTqoWO4obhHiTVWguMt2dhTZCKMPDVAIvUH18k38DBwqtZBwioUZcq+bGbBPqrwbeB5Z80QQRSCA==","signature_status":"signed_v1","signed_at":"2026-05-18T01:25:33.070601Z","signed_message":"canonical_sha256_bytes"},"source_id":"1511.09085","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9af3a86db209aa8772e1f5d3ae99ac9dd53d418014706a00e2467fd6e60d6cd5","sha256:d95fbabd4a41a385c5e91de6a446165856d121f739a9a8a562e8e08d9744b60a"],"state_sha256":"d103a212308578b1b75cc6e50af53a2f0fae1187ccd0caadd5d0b816538b6840"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/Iigpu+dQZhq1s3j8PPxH39Rg1PeYXs/Px9BR4bYpPmqoLjHgYsBO9w5yDA9ex0vGTdCge+VT+1qAM/ly7W7DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T17:03:29.784615Z","bundle_sha256":"345dfd33402bf33e010605a5c6787767a33adc126c7aa47a58044b71db635e9d"}}