{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:2Z6JOGKKKCNA3UOZ3GSWLFFGT4","short_pith_number":"pith:2Z6JOGKK","canonical_record":{"source":{"id":"2505.20932","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T09:21:36Z","cross_cats_sorted":[],"title_canon_sha256":"85d5eec9bea2f3ee9d4cfe60743995477f7b76e36022b5b7884dc223a68907d4","abstract_canon_sha256":"9ce2460615bdfd9877b6b6c29b40a3860c74645aa17c492ff5dfe3ef96d189ca"},"schema_version":"1.0"},"canonical_sha256":"d67c97194a509a0dd1d9d9a56594a69f2bde7f6e9cf0c355d91101a853003d0e","source":{"kind":"arxiv","id":"2505.20932","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.20932","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"arxiv_version","alias_value":"2505.20932v1","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.20932","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"pith_short_12","alias_value":"2Z6JOGKKKCNA","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"pith_short_16","alias_value":"2Z6JOGKKKCNA3UOZ","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"pith_short_8","alias_value":"2Z6JOGKK","created_at":"2026-07-05T11:10:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:2Z6JOGKKKCNA3UOZ3GSWLFFGT4","target":"record","payload":{"canonical_record":{"source":{"id":"2505.20932","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T09:21:36Z","cross_cats_sorted":[],"title_canon_sha256":"85d5eec9bea2f3ee9d4cfe60743995477f7b76e36022b5b7884dc223a68907d4","abstract_canon_sha256":"9ce2460615bdfd9877b6b6c29b40a3860c74645aa17c492ff5dfe3ef96d189ca"},"schema_version":"1.0"},"canonical_sha256":"d67c97194a509a0dd1d9d9a56594a69f2bde7f6e9cf0c355d91101a853003d0e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:10:21.212769Z","signature_b64":"Bh3DV+Qt4wTg6SLLOjmYCfq07/xdbvadkDp5EJeF8WVUIG5Wxs3lesMzrh1iawUSDcSAsKqyQcwp/9z8ZyYBDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d67c97194a509a0dd1d9d9a56594a69f2bde7f6e9cf0c355d91101a853003d0e","last_reissued_at":"2026-07-05T11:10:21.212262Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:10:21.212262Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.20932","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:10:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E9/C3Xcf1bMVeea9aLscbsZihHusqnAblGWtmq7uVMeCRx9cpiDiWX8421gJAHRy9b0pW05wrolnkHv0sEo6Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T12:18:31.946800Z"},"content_sha256":"0e3dca6db70759b0b8a044baad99713a363f9c691085613561d3d445fb10bcfa","schema_version":"1.0","event_id":"sha256:0e3dca6db70759b0b8a044baad99713a363f9c691085613561d3d445fb10bcfa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:2Z6JOGKKKCNA3UOZ3GSWLFFGT4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"QwT-v2: Practical, Effective and Efficient Post-Training Quantization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hao Yu, Jianxin Wu, Minghao Fu, Ningyuan Tang","submitted_at":"2025-05-27T09:21:36Z","abstract_excerpt":"Network quantization is arguably one of the most practical network compression approaches for reducing the enormous resource consumption of modern deep neural networks. They usually require diverse and subtle design choices for specific architecture and tasks. Instead, the QwT method is a simple and general approach which introduces lightweight additional structures to improve quantization. But QwT incurs extra parameters and latency. More importantly, QwT is not compatible with many hardware platforms. In this paper, we propose QwT-v2, which not only enjoys all advantages of but also resolves"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.20932","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2505.20932/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:10:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q5W/jYCN9JMGy+PsHn6xKDDg2UHS2snUjRn2+jQqFoATFsB3GKC3AUtfZNyZOb4nmcAJLIkxyFCawg9mBk4rCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T12:18:31.947281Z"},"content_sha256":"17c3f02442a5d007392f000ccbb24da88e6350d69dc0c194cf0bb66cefb2f3e8","schema_version":"1.0","event_id":"sha256:17c3f02442a5d007392f000ccbb24da88e6350d69dc0c194cf0bb66cefb2f3e8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2Z6JOGKKKCNA3UOZ3GSWLFFGT4/bundle.json","state_url":"https://pith.science/pith/2Z6JOGKKKCNA3UOZ3GSWLFFGT4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2Z6JOGKKKCNA3UOZ3GSWLFFGT4/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-07T12:18:31Z","links":{"resolver":"https://pith.science/pith/2Z6JOGKKKCNA3UOZ3GSWLFFGT4","bundle":"https://pith.science/pith/2Z6JOGKKKCNA3UOZ3GSWLFFGT4/bundle.json","state":"https://pith.science/pith/2Z6JOGKKKCNA3UOZ3GSWLFFGT4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2Z6JOGKKKCNA3UOZ3GSWLFFGT4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2Z6JOGKKKCNA3UOZ3GSWLFFGT4","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":"9ce2460615bdfd9877b6b6c29b40a3860c74645aa17c492ff5dfe3ef96d189ca","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T09:21:36Z","title_canon_sha256":"85d5eec9bea2f3ee9d4cfe60743995477f7b76e36022b5b7884dc223a68907d4"},"schema_version":"1.0","source":{"id":"2505.20932","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.20932","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"arxiv_version","alias_value":"2505.20932v1","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.20932","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"pith_short_12","alias_value":"2Z6JOGKKKCNA","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"pith_short_16","alias_value":"2Z6JOGKKKCNA3UOZ","created_at":"2026-07-05T11:10:21Z"},{"alias_kind":"pith_short_8","alias_value":"2Z6JOGKK","created_at":"2026-07-05T11:10:21Z"}],"graph_snapshots":[{"event_id":"sha256:17c3f02442a5d007392f000ccbb24da88e6350d69dc0c194cf0bb66cefb2f3e8","target":"graph","created_at":"2026-07-05T11:10:21Z","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/2505.20932/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Network quantization is arguably one of the most practical network compression approaches for reducing the enormous resource consumption of modern deep neural networks. They usually require diverse and subtle design choices for specific architecture and tasks. Instead, the QwT method is a simple and general approach which introduces lightweight additional structures to improve quantization. But QwT incurs extra parameters and latency. More importantly, QwT is not compatible with many hardware platforms. In this paper, we propose QwT-v2, which not only enjoys all advantages of but also resolves","authors_text":"Hao Yu, Jianxin Wu, Minghao Fu, Ningyuan Tang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T09:21:36Z","title":"QwT-v2: Practical, Effective and Efficient Post-Training Quantization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.20932","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":"sha256:0e3dca6db70759b0b8a044baad99713a363f9c691085613561d3d445fb10bcfa","target":"record","created_at":"2026-07-05T11:10:21Z","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":"9ce2460615bdfd9877b6b6c29b40a3860c74645aa17c492ff5dfe3ef96d189ca","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-27T09:21:36Z","title_canon_sha256":"85d5eec9bea2f3ee9d4cfe60743995477f7b76e36022b5b7884dc223a68907d4"},"schema_version":"1.0","source":{"id":"2505.20932","kind":"arxiv","version":1}},"canonical_sha256":"d67c97194a509a0dd1d9d9a56594a69f2bde7f6e9cf0c355d91101a853003d0e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d67c97194a509a0dd1d9d9a56594a69f2bde7f6e9cf0c355d91101a853003d0e","first_computed_at":"2026-07-05T11:10:21.212262Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:10:21.212262Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Bh3DV+Qt4wTg6SLLOjmYCfq07/xdbvadkDp5EJeF8WVUIG5Wxs3lesMzrh1iawUSDcSAsKqyQcwp/9z8ZyYBDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:10:21.212769Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.20932","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0e3dca6db70759b0b8a044baad99713a363f9c691085613561d3d445fb10bcfa","sha256:17c3f02442a5d007392f000ccbb24da88e6350d69dc0c194cf0bb66cefb2f3e8"],"state_sha256":"f6cbfcd661d66cec184566cef8c282648d445b960f350c7390929b33cffa7137"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Bvp9+4bmYXfg2MJfM7TnxV0XvV2QK1qX2XUcdZBB5IMiTksnGXLOFs5YIbUQQ2s81+WAL4DaPAFiaLKan1JRDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T12:18:31.951487Z","bundle_sha256":"54e021f5c9413e4c0f6620763f704995075ae4f64b7e1dc167b62b2e78980b0f"}}