{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:XSECNHBJ6BZFA5G4E2MS54F44O","short_pith_number":"pith:XSECNHBJ","canonical_record":{"source":{"id":"2111.12293","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-11-24T06:23:06Z","cross_cats_sorted":[],"title_canon_sha256":"b768c4484d9820c257de39a7ab3508b11d0698a4c11d770b9d8c84aa45843326","abstract_canon_sha256":"96de2f1f3e5bce88e64e79f0471ab49e4ee554f9ebf694e6df07421b2e76bd4a"},"schema_version":"1.0"},"canonical_sha256":"bc88269c29f0725074dc26992ef0bce3ab0fd6aaee7a26e8a1f0bfcd5dee85b6","source":{"kind":"arxiv","id":"2111.12293","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.12293","created_at":"2026-07-05T08:35:32Z"},{"alias_kind":"arxiv_version","alias_value":"2111.12293v3","created_at":"2026-07-05T08:35:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.12293","created_at":"2026-07-05T08:35:32Z"},{"alias_kind":"pith_short_12","alias_value":"XSECNHBJ6BZF","created_at":"2026-07-05T08:35:32Z"},{"alias_kind":"pith_short_16","alias_value":"XSECNHBJ6BZFA5G4","created_at":"2026-07-05T08:35:32Z"},{"alias_kind":"pith_short_8","alias_value":"XSECNHBJ","created_at":"2026-07-05T08:35:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:XSECNHBJ6BZFA5G4E2MS54F44O","target":"record","payload":{"canonical_record":{"source":{"id":"2111.12293","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-11-24T06:23:06Z","cross_cats_sorted":[],"title_canon_sha256":"b768c4484d9820c257de39a7ab3508b11d0698a4c11d770b9d8c84aa45843326","abstract_canon_sha256":"96de2f1f3e5bce88e64e79f0471ab49e4ee554f9ebf694e6df07421b2e76bd4a"},"schema_version":"1.0"},"canonical_sha256":"bc88269c29f0725074dc26992ef0bce3ab0fd6aaee7a26e8a1f0bfcd5dee85b6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:35:32.976837Z","signature_b64":"gDzRYiLr/TYaGI18ANyDoydra6y5HSySsOTNmNADfRflrF2N849nM7EuNwk4xMNLj/utLdD5QSXpi193ZYjdAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bc88269c29f0725074dc26992ef0bce3ab0fd6aaee7a26e8a1f0bfcd5dee85b6","last_reissued_at":"2026-07-05T08:35:32.976398Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:35:32.976398Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2111.12293","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:35:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"b/HMv8D7R44TNOOItkwYL63/uEJ97bQjSzVirVjIvrx+EFnjw3/xxJTq/I96VjCKmoUqJcBe69zhcCxUIYsnAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T13:57:37.346767Z"},"content_sha256":"c0a2fc718c3e3a3053c6cb62ffd17ac602c7608ba4f99145a42fb4dbf7a61fe8","schema_version":"1.0","event_id":"sha256:c0a2fc718c3e3a3053c6cb62ffd17ac602c7608ba4f99145a42fb4dbf7a61fe8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:XSECNHBJ6BZFA5G4E2MS54F44O","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PTQ4ViT: Post-training quantization for vision transformers with twin uniform quantization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chenhao Xue, Guangyu Sun, Qiang Wu, Yiqi Chen, Zhihang Yuan","submitted_at":"2021-11-24T06:23:06Z","abstract_excerpt":"Quantization is one of the most effective methods to compress neural networks, which has achieved great success on convolutional neural networks (CNNs). Recently, vision transformers have demonstrated great potential in computer vision. However, previous post-training quantization methods performed not well on vision transformer, resulting in more than 1% accuracy drop even in 8-bit quantization. Therefore, we analyze the problems of quantization on vision transformers. We observe the distributions of activation values after softmax and GELU functions are quite different from the Gaussian dist"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.12293","kind":"arxiv","version":3},"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/2111.12293/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":"2026-07-05T08:35:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kXFhB8R+q87BhI7I1FBGsmEuE+UwzjayC3YCTe6NnN11JO9gQJeRGVDr7vkxuXd4y8MIO4RGH8bTNIM0uKdCDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T13:57:37.347254Z"},"content_sha256":"be76217aeeda2f236f6f0378641f905294c27e40fe1a230868aa94623c0f62e0","schema_version":"1.0","event_id":"sha256:be76217aeeda2f236f6f0378641f905294c27e40fe1a230868aa94623c0f62e0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XSECNHBJ6BZFA5G4E2MS54F44O/bundle.json","state_url":"https://pith.science/pith/XSECNHBJ6BZFA5G4E2MS54F44O/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XSECNHBJ6BZFA5G4E2MS54F44O/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":"2026-08-08T13:57:37Z","links":{"resolver":"https://pith.science/pith/XSECNHBJ6BZFA5G4E2MS54F44O","bundle":"https://pith.science/pith/XSECNHBJ6BZFA5G4E2MS54F44O/bundle.json","state":"https://pith.science/pith/XSECNHBJ6BZFA5G4E2MS54F44O/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XSECNHBJ6BZFA5G4E2MS54F44O/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:XSECNHBJ6BZFA5G4E2MS54F44O","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":"96de2f1f3e5bce88e64e79f0471ab49e4ee554f9ebf694e6df07421b2e76bd4a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-11-24T06:23:06Z","title_canon_sha256":"b768c4484d9820c257de39a7ab3508b11d0698a4c11d770b9d8c84aa45843326"},"schema_version":"1.0","source":{"id":"2111.12293","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.12293","created_at":"2026-07-05T08:35:32Z"},{"alias_kind":"arxiv_version","alias_value":"2111.12293v3","created_at":"2026-07-05T08:35:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.12293","created_at":"2026-07-05T08:35:32Z"},{"alias_kind":"pith_short_12","alias_value":"XSECNHBJ6BZF","created_at":"2026-07-05T08:35:32Z"},{"alias_kind":"pith_short_16","alias_value":"XSECNHBJ6BZFA5G4","created_at":"2026-07-05T08:35:32Z"},{"alias_kind":"pith_short_8","alias_value":"XSECNHBJ","created_at":"2026-07-05T08:35:32Z"}],"graph_snapshots":[{"event_id":"sha256:be76217aeeda2f236f6f0378641f905294c27e40fe1a230868aa94623c0f62e0","target":"graph","created_at":"2026-07-05T08:35:32Z","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/2111.12293/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Quantization is one of the most effective methods to compress neural networks, which has achieved great success on convolutional neural networks (CNNs). Recently, vision transformers have demonstrated great potential in computer vision. However, previous post-training quantization methods performed not well on vision transformer, resulting in more than 1% accuracy drop even in 8-bit quantization. Therefore, we analyze the problems of quantization on vision transformers. We observe the distributions of activation values after softmax and GELU functions are quite different from the Gaussian dist","authors_text":"Chenhao Xue, Guangyu Sun, Qiang Wu, Yiqi Chen, Zhihang Yuan","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-11-24T06:23:06Z","title":"PTQ4ViT: Post-training quantization for vision transformers with twin uniform quantization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.12293","kind":"arxiv","version":3},"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:c0a2fc718c3e3a3053c6cb62ffd17ac602c7608ba4f99145a42fb4dbf7a61fe8","target":"record","created_at":"2026-07-05T08:35:32Z","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":"96de2f1f3e5bce88e64e79f0471ab49e4ee554f9ebf694e6df07421b2e76bd4a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-11-24T06:23:06Z","title_canon_sha256":"b768c4484d9820c257de39a7ab3508b11d0698a4c11d770b9d8c84aa45843326"},"schema_version":"1.0","source":{"id":"2111.12293","kind":"arxiv","version":3}},"canonical_sha256":"bc88269c29f0725074dc26992ef0bce3ab0fd6aaee7a26e8a1f0bfcd5dee85b6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bc88269c29f0725074dc26992ef0bce3ab0fd6aaee7a26e8a1f0bfcd5dee85b6","first_computed_at":"2026-07-05T08:35:32.976398Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:35:32.976398Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gDzRYiLr/TYaGI18ANyDoydra6y5HSySsOTNmNADfRflrF2N849nM7EuNwk4xMNLj/utLdD5QSXpi193ZYjdAw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:35:32.976837Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.12293","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c0a2fc718c3e3a3053c6cb62ffd17ac602c7608ba4f99145a42fb4dbf7a61fe8","sha256:be76217aeeda2f236f6f0378641f905294c27e40fe1a230868aa94623c0f62e0"],"state_sha256":"545a8b1f801c1a77f687fe276a7e1e1ccad8a2ade60137f52ab8970d458549c6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dXDTwnFiZuZtXKTEE8qOc/jQ5w5yqKO3/QvlEHFwJEsLlfDgeaEQrN+f2K2P81HGgTYEfV9VByLc4KedI/3VDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T13:57:37.351923Z","bundle_sha256":"8d6f5b8841bef2fb80dccd93083e34785d14a117df15ea4b4dd20106eed63c86"}}