{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:SZ4EVOWBXIBNXJYZ76DG37TEIM","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":"ca1316e8e307b8625b9321446d7458403f96f7809f364adb71f905a5095eefd1","cross_cats_sorted":["cs.AI","cs.SE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-04-08T11:19:16Z","title_canon_sha256":"40487e9a05c37da18b1d277dddbbdfe106fc475a44ecabab4575b1ca79843469"},"schema_version":"1.0","source":{"id":"2204.04220","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2204.04220","created_at":"2026-07-05T04:12:54Z"},{"alias_kind":"arxiv_version","alias_value":"2204.04220v1","created_at":"2026-07-05T04:12:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2204.04220","created_at":"2026-07-05T04:12:54Z"},{"alias_kind":"pith_short_12","alias_value":"SZ4EVOWBXIBN","created_at":"2026-07-05T04:12:54Z"},{"alias_kind":"pith_short_16","alias_value":"SZ4EVOWBXIBNXJYZ","created_at":"2026-07-05T04:12:54Z"},{"alias_kind":"pith_short_8","alias_value":"SZ4EVOWB","created_at":"2026-07-05T04:12:54Z"}],"graph_snapshots":[{"event_id":"sha256:9f0b04d8f9ea0ab71221a4ed390b3f8028572405088cf419e5d2f0af53c7d4d5","target":"graph","created_at":"2026-07-05T04:12:54Z","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/2204.04220/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep Neural Networks (DNNs) have gained considerable attention in the past decades due to their astounding performance in different applications, such as natural language modeling, self-driving assistance, and source code understanding. With rapid exploration, more and more complex DNN architectures have been proposed along with huge pre-trained model parameters. The common way to use such DNN models in user-friendly devices (e.g., mobile phones) is to perform model compression before deployment. However, recent research has demonstrated that model compression, e.g., model quantization, yields","authors_text":"Maxime Cordy, Mike Papadakis, Qiang Hu, Wei Ma, Xiaofei Xie, Yuejun Guo, Yves Le Traon","cross_cats":["cs.AI","cs.SE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-04-08T11:19:16Z","title":"Characterizing and Understanding the Behavior of Quantized Models for Reliable Deployment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2204.04220","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:ed12cf0154e2cd563ed55ac8b0f1126304b67316350b80dfdb78604ead17f91b","target":"record","created_at":"2026-07-05T04:12:54Z","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":"ca1316e8e307b8625b9321446d7458403f96f7809f364adb71f905a5095eefd1","cross_cats_sorted":["cs.AI","cs.SE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-04-08T11:19:16Z","title_canon_sha256":"40487e9a05c37da18b1d277dddbbdfe106fc475a44ecabab4575b1ca79843469"},"schema_version":"1.0","source":{"id":"2204.04220","kind":"arxiv","version":1}},"canonical_sha256":"96784abac1ba02dba719ff866dfe644319d825135930296c99cd21cd41604653","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"96784abac1ba02dba719ff866dfe644319d825135930296c99cd21cd41604653","first_computed_at":"2026-07-05T04:12:54.574667Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:12:54.574667Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"F7t47YkgKqaZJA1GElqBLZVUm4jrV7vV6tCYJ7J32J4HE7WXHL8vrfcukVex06jEtSCw+Ny41LdhYrXqnbJoAA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:12:54.575096Z","signed_message":"canonical_sha256_bytes"},"source_id":"2204.04220","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ed12cf0154e2cd563ed55ac8b0f1126304b67316350b80dfdb78604ead17f91b","sha256:9f0b04d8f9ea0ab71221a4ed390b3f8028572405088cf419e5d2f0af53c7d4d5"],"state_sha256":"a0ac591f36c6af5efa66b999d4c2314ba77ec10017ac56bf0aa6f0c0b85e5d1d"}