{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:445VCP7NDGC4472NLGENQDMWTB","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":"61c3e704be282fc740e85e77e4467fefe6878d3c518586f66c617258101830ad","cross_cats_sorted":["cs.AR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-03-25T14:40:59Z","title_canon_sha256":"d41a771574a2097dc377e219ea1b16116da35f03a162bea8a30e4df2a60385a1"},"schema_version":"1.0","source":{"id":"2303.16100","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.16100","created_at":"2026-07-05T06:00:37Z"},{"alias_kind":"arxiv_version","alias_value":"2303.16100v2","created_at":"2026-07-05T06:00:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.16100","created_at":"2026-07-05T06:00:37Z"},{"alias_kind":"pith_short_12","alias_value":"445VCP7NDGC4","created_at":"2026-07-05T06:00:37Z"},{"alias_kind":"pith_short_16","alias_value":"445VCP7NDGC4472N","created_at":"2026-07-05T06:00:37Z"},{"alias_kind":"pith_short_8","alias_value":"445VCP7N","created_at":"2026-07-05T06:00:37Z"}],"graph_snapshots":[{"event_id":"sha256:29fe7f915943c3f04d439a20e9df0ac753ed2f0d64ced3b95f1e2de8938349d8","target":"graph","created_at":"2026-07-05T06:00:37Z","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/2303.16100/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Executing machine learning inference tasks on resource-constrained edge devices requires careful hardware-software co-design optimizations. Recent examples have shown how transformer-based deep neural network models such as ALBERT can be used to enable the execution of natural language processing (NLP) inference on mobile systems-on-chip housing custom hardware accelerators. However, while these existing solutions are effective in alleviating the latency, energy, and area costs of running single NLP tasks, achieving multi-task inference requires running computations over multiple variants of t","authors_text":"Aleksandre Avaliani, Marco Donato, Zirui Fu","cross_cats":["cs.AR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-03-25T14:40:59Z","title":"Energy-efficient Task Adaptation for NLP Edge Inference Leveraging Heterogeneous Memory Architectures"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.16100","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":"sha256:46c0b66d1936f2fe9ee67bdd364b790af399be3925c99f1661e52b2bbd61a3b9","target":"record","created_at":"2026-07-05T06:00:37Z","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":"61c3e704be282fc740e85e77e4467fefe6878d3c518586f66c617258101830ad","cross_cats_sorted":["cs.AR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-03-25T14:40:59Z","title_canon_sha256":"d41a771574a2097dc377e219ea1b16116da35f03a162bea8a30e4df2a60385a1"},"schema_version":"1.0","source":{"id":"2303.16100","kind":"arxiv","version":2}},"canonical_sha256":"e73b513fed1985ce7f4d5988d80d969873453f1328b998402c9a996aa1fc5150","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e73b513fed1985ce7f4d5988d80d969873453f1328b998402c9a996aa1fc5150","first_computed_at":"2026-07-05T06:00:37.007075Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:00:37.007075Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5ATUrQxDap+GVevlXJ5Gjzst5CBbdUBDJXc61kxuYxNfwD+q70nk4CFoEaI4oIp4kAHREi3m8GuqJSW3OgPkAw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:00:37.007560Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.16100","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:46c0b66d1936f2fe9ee67bdd364b790af399be3925c99f1661e52b2bbd61a3b9","sha256:29fe7f915943c3f04d439a20e9df0ac753ed2f0d64ced3b95f1e2de8938349d8"],"state_sha256":"11e605baad5395a3e9c18b7dfa569ff2e3992470e7d7ac0e23a171d7656339a8"}