{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:4JN4UB677VYEHPUOIMKBW7FDRZ","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":"80477f167d9e0ff0efe1932d3b92884579bb9062f6c7ec4fd90893f12954b6ae","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-03T15:46:15Z","title_canon_sha256":"bbb4d9e3dc343ad9336b059bacd1eca0fd951b2187302faa739e8e999b348a36"},"schema_version":"1.0","source":{"id":"2304.01089","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.01089","created_at":"2026-07-05T06:11:04Z"},{"alias_kind":"arxiv_version","alias_value":"2304.01089v4","created_at":"2026-07-05T06:11:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.01089","created_at":"2026-07-05T06:11:04Z"},{"alias_kind":"pith_short_12","alias_value":"4JN4UB677VYE","created_at":"2026-07-05T06:11:04Z"},{"alias_kind":"pith_short_16","alias_value":"4JN4UB677VYEHPUO","created_at":"2026-07-05T06:11:04Z"},{"alias_kind":"pith_short_8","alias_value":"4JN4UB67","created_at":"2026-07-05T06:11:04Z"}],"graph_snapshots":[{"event_id":"sha256:dfb928718ca22691107926398521a043e2f61ada62415289a12d35bcb1bf9d79","target":"graph","created_at":"2026-07-05T06:11:04Z","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/2304.01089/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large-scale language models (LLMs) have demonstrated impressive performance, but their deployment presents challenges due to their significant memory usage. This issue can be alleviated through quantization. In this paper, we identify that the challenge in quantizing activations in LLMs arises from varying ranges across channels, rather than solely the presence of outliers. To address this challenge, we introduce a quantization method called RPTQ, which utilizes a reorder-based approach. By rearranging the channels and quantizing them in clusters, RPTQ effectively mitigates the impact of range","authors_text":"Bingzhe Wu, Guangyu Sun, Jiawei Liu, Jiaxiang Wu, Lin Niu, Qiang Wu, Wenyu Liu, Xinggang Wang, Yuzhang Shang, Zhihang Yuan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-03T15:46:15Z","title":"RPTQ: Reorder-based Post-training Quantization for Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.01089","kind":"arxiv","version":4},"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:b473a695fb9e934fb4f62ba7529596ffa93163e9d7cdcd1717dcd8475da14ec7","target":"record","created_at":"2026-07-05T06:11:04Z","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":"80477f167d9e0ff0efe1932d3b92884579bb9062f6c7ec4fd90893f12954b6ae","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-03T15:46:15Z","title_canon_sha256":"bbb4d9e3dc343ad9336b059bacd1eca0fd951b2187302faa739e8e999b348a36"},"schema_version":"1.0","source":{"id":"2304.01089","kind":"arxiv","version":4}},"canonical_sha256":"e25bca07dffd7043be8e43141b7ca38e4dc55c6ff4bb5d58c696e0cbc055ddf8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e25bca07dffd7043be8e43141b7ca38e4dc55c6ff4bb5d58c696e0cbc055ddf8","first_computed_at":"2026-07-05T06:11:04.108588Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:11:04.108588Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9Vl9izo7uH/DrfFruMUpu+y0BsRZDR8HOtlRh1GTQ8dxc5cefW2Yqp4MxadcSY4ZX9QZc/yurXT3AaZO7B6cDg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:11:04.109058Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.01089","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b473a695fb9e934fb4f62ba7529596ffa93163e9d7cdcd1717dcd8475da14ec7","sha256:dfb928718ca22691107926398521a043e2f61ada62415289a12d35bcb1bf9d79"],"state_sha256":"7104b3dda5919a69950ddaaaba57899e905e113b709e9b7070d1b483fa725db3"}