{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2EIMENSKJ3MSUUOPDGSPXBM7GK","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":"33ad917125b76f8b5eb195ec208faf5ae33b99c40e673578be446765e47d9a72","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-16T06:44:14Z","title_canon_sha256":"2adbd0fec8ab5ad5d125b199e52a11edace468403554934f52be88e57a0c77a0"},"schema_version":"1.0","source":{"id":"2507.11959","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.11959","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"arxiv_version","alias_value":"2507.11959v1","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.11959","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"pith_short_12","alias_value":"2EIMENSKJ3MS","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"pith_short_16","alias_value":"2EIMENSKJ3MSUUOP","created_at":"2026-07-05T11:38:11Z"},{"alias_kind":"pith_short_8","alias_value":"2EIMENSK","created_at":"2026-07-05T11:38:11Z"}],"graph_snapshots":[{"event_id":"sha256:03472b4a1729f8da27951f816e08708d5e2e47bc6f5dce09c8f8c8d3de76043c","target":"graph","created_at":"2026-07-05T11:38:11Z","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/2507.11959/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have demonstrated remarkable performance across various natural language processing (NLP) tasks. However, their deployment is challenging due to the substantial computational resources required. Power-of-two (PoT) quantization is a general tool to counteract this difficulty. Albeit previous works on PoT quantization can be efficiently dequantized on CPUs using fixed-point addition, it showed less effectiveness on GPUs. The reason is entanglement of the sign bit and sequential bit manipulations needed for dequantization. We propose a novel POT quantization framework","authors_text":"Boxing Chen, Jerry Huang, Peng Lu, Vahid Partovi Nia, Xiao-Wen Chang, Xinyu Wang, Yufei Cui","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-16T06:44:14Z","title":"PoTPTQ: A Two-step Power-of-Two Post-training for LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.11959","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:bb9f33a7ed8a201cd07ec5e8e788df26c907a2c015f5077def5384fce728bb89","target":"record","created_at":"2026-07-05T11:38:11Z","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":"33ad917125b76f8b5eb195ec208faf5ae33b99c40e673578be446765e47d9a72","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2025-07-16T06:44:14Z","title_canon_sha256":"2adbd0fec8ab5ad5d125b199e52a11edace468403554934f52be88e57a0c77a0"},"schema_version":"1.0","source":{"id":"2507.11959","kind":"arxiv","version":1}},"canonical_sha256":"d110c2364a4ed92a51cf19a4fb859f3299ad1c699e98fdd448f51cc5b1a0f7ea","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d110c2364a4ed92a51cf19a4fb859f3299ad1c699e98fdd448f51cc5b1a0f7ea","first_computed_at":"2026-07-05T11:38:11.580468Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:38:11.580468Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vzuAolUx8yqAjw9UloWzFQaQLXxHqCFhtrD7Bg+3cb/gwS6tr7H9Yokre1rtWarHGmi70D441QUyeeNYiYHSBA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:38:11.580943Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.11959","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bb9f33a7ed8a201cd07ec5e8e788df26c907a2c015f5077def5384fce728bb89","sha256:03472b4a1729f8da27951f816e08708d5e2e47bc6f5dce09c8f8c8d3de76043c"],"state_sha256":"a704d29e735951a23274ac272a7d780f00ce3a8d890b9dd720ee3d38994dec4d"}