{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WV7ECLODUN2UWJBLNSZMXAPKO6","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":"5838afc65d2570cd0081668656daa95f416c819c81596c1858b2c4578df9107f","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-28T07:04:19Z","title_canon_sha256":"59b9c709cf67ff1efe21df256715d30c588394642796df343258ee35637bdd13"},"schema_version":"1.0","source":{"id":"2503.01901","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.01901","created_at":"2026-07-05T10:23:32Z"},{"alias_kind":"arxiv_version","alias_value":"2503.01901v1","created_at":"2026-07-05T10:23:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.01901","created_at":"2026-07-05T10:23:32Z"},{"alias_kind":"pith_short_12","alias_value":"WV7ECLODUN2U","created_at":"2026-07-05T10:23:32Z"},{"alias_kind":"pith_short_16","alias_value":"WV7ECLODUN2UWJBL","created_at":"2026-07-05T10:23:32Z"},{"alias_kind":"pith_short_8","alias_value":"WV7ECLOD","created_at":"2026-07-05T10:23:32Z"}],"graph_snapshots":[{"event_id":"sha256:a4dbd2da73f8109bb6d1d787999241d771b5233bd100e213220ea2765e1a889e","target":"graph","created_at":"2026-07-05T10:23:32Z","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/2503.01901/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Serving Large Language Models (LLMs) is costly. However, post-training weight quantization can address this problem by both compressing their sizes for limited memory and saving bandwidth for acceleration. As not all weight dimensions are equally important, those methods typically rely on a sensitivity metric, which indicates the element-wise influence of weights on loss function and is used to preprocess original weights for better quantization. In this work, we conduct an empirical study on the accuracy of the sensitivity metric, and find that existing gradient and Hessian based metrics are ","authors_text":"Chang Chen, Jianfei Chen, Jintao Zhang, Jun Zhu, Weiyu Huang, Yuezhou Hu, Zichen Liang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-28T07:04:19Z","title":"Identifying Sensitive Weights via Post-quantization Integral"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.01901","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":"sha256:8305a016b1eee87326ce3a041d9f8ebeb2be00d24cf3726b74f0135080a21b2f","target":"record","created_at":"2026-07-05T10:23:32Z","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":"5838afc65d2570cd0081668656daa95f416c819c81596c1858b2c4578df9107f","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-28T07:04:19Z","title_canon_sha256":"59b9c709cf67ff1efe21df256715d30c588394642796df343258ee35637bdd13"},"schema_version":"1.0","source":{"id":"2503.01901","kind":"arxiv","version":1}},"canonical_sha256":"b57e412dc3a3754b242b6cb2cb81ea779eb6bb48f4c4562c7c51eff1cedd4814","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b57e412dc3a3754b242b6cb2cb81ea779eb6bb48f4c4562c7c51eff1cedd4814","first_computed_at":"2026-07-05T10:23:32.200576Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:23:32.200576Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7Bl232N6nCaWczDyjz1grrt5Ycc7+pg5AkfNFshphn3CDe7qZF/jDxoGCQmJbNkrjbRlcjkebdD7rt/7EIR+Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:23:32.201247Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.01901","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8305a016b1eee87326ce3a041d9f8ebeb2be00d24cf3726b74f0135080a21b2f","sha256:a4dbd2da73f8109bb6d1d787999241d771b5233bd100e213220ea2765e1a889e"],"state_sha256":"91a5c4ec0984815c6b899de1a650cf1c21e96024a686925a4cd30a6d24cc5933"}