{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:ODSGZVJNOFPDP6KIALVBYZXZFF","short_pith_number":"pith:ODSGZVJN","canonical_record":{"source":{"id":"2403.05365","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-08T14:55:05Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e6e00b3392f02dd4cea00d3cdf3827c3ea3219665fd54397098eda755befe40a","abstract_canon_sha256":"6b845ac01a60d8e86c424ab1c58505ae1b1fb205497593ed7f101b8fbca5c92b"},"schema_version":"1.0"},"canonical_sha256":"70e46cd52d715e37f94802ea1c66f9297ee0b0a01beec87804073b2a2c3bcc2b","source":{"kind":"arxiv","id":"2403.05365","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.05365","created_at":"2026-07-05T07:53:54Z"},{"alias_kind":"arxiv_version","alias_value":"2403.05365v1","created_at":"2026-07-05T07:53:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.05365","created_at":"2026-07-05T07:53:54Z"},{"alias_kind":"pith_short_12","alias_value":"ODSGZVJNOFPD","created_at":"2026-07-05T07:53:54Z"},{"alias_kind":"pith_short_16","alias_value":"ODSGZVJNOFPDP6KI","created_at":"2026-07-05T07:53:54Z"},{"alias_kind":"pith_short_8","alias_value":"ODSGZVJN","created_at":"2026-07-05T07:53:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:ODSGZVJNOFPDP6KIALVBYZXZFF","target":"record","payload":{"canonical_record":{"source":{"id":"2403.05365","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-08T14:55:05Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e6e00b3392f02dd4cea00d3cdf3827c3ea3219665fd54397098eda755befe40a","abstract_canon_sha256":"6b845ac01a60d8e86c424ab1c58505ae1b1fb205497593ed7f101b8fbca5c92b"},"schema_version":"1.0"},"canonical_sha256":"70e46cd52d715e37f94802ea1c66f9297ee0b0a01beec87804073b2a2c3bcc2b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:53:54.424407Z","signature_b64":"slDvvXfqgiJxDYcJkSDNczJgygjS+35Wmok9npM6jfWLYO4nJDHct55LLjiKEXHWaYiG7AYWj+T5OUYfwDKSDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"70e46cd52d715e37f94802ea1c66f9297ee0b0a01beec87804073b2a2c3bcc2b","last_reissued_at":"2026-07-05T07:53:54.423842Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:53:54.423842Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.05365","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":"2026-07-05T07:53:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/hJ991rzZvlwuyE57soudLZ2bMHYLexgFjcgYnFejvl/AfPckSa5/OylSVaCbveOpqES5SChHJYyZStWLps4AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T13:51:08.989217Z"},"content_sha256":"d8e59b958719e74cc31e168eddc21c921e98a6eb4c3e16364d2e3d9de943fb34","schema_version":"1.0","event_id":"sha256:d8e59b958719e74cc31e168eddc21c921e98a6eb4c3e16364d2e3d9de943fb34"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:ODSGZVJNOFPDP6KIALVBYZXZFF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Impact of Quantization on the Robustness of Transformer-based Text Classifiers","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Gholamreza Ghassem-Sani, Seyed Abolghasem Mirroshandel, Seyed Parsa Neshaei, Yasaman Boreshban","submitted_at":"2024-03-08T14:55:05Z","abstract_excerpt":"Transformer-based models have made remarkable advancements in various NLP areas. Nevertheless, these models often exhibit vulnerabilities when confronted with adversarial attacks. In this paper, we explore the effect of quantization on the robustness of Transformer-based models. Quantization usually involves mapping a high-precision real number to a lower-precision value, aiming at reducing the size of the model at hand. To the best of our knowledge, this work is the first application of quantization on the robustness of NLP models. In our experiments, we evaluate the impact of quantization on"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.05365","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/2403.05365/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":"2026-07-05T07:53:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tWLn4JDPVYsI4EldTpaGsI27fbpa/apw0C3ycZh1YWhogYU8sY/kFWSyJGYcggHedl7mLE/Tg5eml1Wg1q8DDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T13:51:08.989607Z"},"content_sha256":"5e66f224f6c5157ead513839cf3c4421dfb8078d280e2a92faa4115652583123","schema_version":"1.0","event_id":"sha256:5e66f224f6c5157ead513839cf3c4421dfb8078d280e2a92faa4115652583123"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ODSGZVJNOFPDP6KIALVBYZXZFF/bundle.json","state_url":"https://pith.science/pith/ODSGZVJNOFPDP6KIALVBYZXZFF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ODSGZVJNOFPDP6KIALVBYZXZFF/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":"2026-07-06T13:51:08Z","links":{"resolver":"https://pith.science/pith/ODSGZVJNOFPDP6KIALVBYZXZFF","bundle":"https://pith.science/pith/ODSGZVJNOFPDP6KIALVBYZXZFF/bundle.json","state":"https://pith.science/pith/ODSGZVJNOFPDP6KIALVBYZXZFF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ODSGZVJNOFPDP6KIALVBYZXZFF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ODSGZVJNOFPDP6KIALVBYZXZFF","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":"6b845ac01a60d8e86c424ab1c58505ae1b1fb205497593ed7f101b8fbca5c92b","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-08T14:55:05Z","title_canon_sha256":"e6e00b3392f02dd4cea00d3cdf3827c3ea3219665fd54397098eda755befe40a"},"schema_version":"1.0","source":{"id":"2403.05365","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.05365","created_at":"2026-07-05T07:53:54Z"},{"alias_kind":"arxiv_version","alias_value":"2403.05365v1","created_at":"2026-07-05T07:53:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.05365","created_at":"2026-07-05T07:53:54Z"},{"alias_kind":"pith_short_12","alias_value":"ODSGZVJNOFPD","created_at":"2026-07-05T07:53:54Z"},{"alias_kind":"pith_short_16","alias_value":"ODSGZVJNOFPDP6KI","created_at":"2026-07-05T07:53:54Z"},{"alias_kind":"pith_short_8","alias_value":"ODSGZVJN","created_at":"2026-07-05T07:53:54Z"}],"graph_snapshots":[{"event_id":"sha256:5e66f224f6c5157ead513839cf3c4421dfb8078d280e2a92faa4115652583123","target":"graph","created_at":"2026-07-05T07:53:54Z","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/2403.05365/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Transformer-based models have made remarkable advancements in various NLP areas. Nevertheless, these models often exhibit vulnerabilities when confronted with adversarial attacks. In this paper, we explore the effect of quantization on the robustness of Transformer-based models. Quantization usually involves mapping a high-precision real number to a lower-precision value, aiming at reducing the size of the model at hand. To the best of our knowledge, this work is the first application of quantization on the robustness of NLP models. In our experiments, we evaluate the impact of quantization on","authors_text":"Gholamreza Ghassem-Sani, Seyed Abolghasem Mirroshandel, Seyed Parsa Neshaei, Yasaman Boreshban","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-08T14:55:05Z","title":"The Impact of Quantization on the Robustness of Transformer-based Text Classifiers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.05365","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:d8e59b958719e74cc31e168eddc21c921e98a6eb4c3e16364d2e3d9de943fb34","target":"record","created_at":"2026-07-05T07:53:54Z","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":"6b845ac01a60d8e86c424ab1c58505ae1b1fb205497593ed7f101b8fbca5c92b","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-08T14:55:05Z","title_canon_sha256":"e6e00b3392f02dd4cea00d3cdf3827c3ea3219665fd54397098eda755befe40a"},"schema_version":"1.0","source":{"id":"2403.05365","kind":"arxiv","version":1}},"canonical_sha256":"70e46cd52d715e37f94802ea1c66f9297ee0b0a01beec87804073b2a2c3bcc2b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"70e46cd52d715e37f94802ea1c66f9297ee0b0a01beec87804073b2a2c3bcc2b","first_computed_at":"2026-07-05T07:53:54.423842Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:53:54.423842Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"slDvvXfqgiJxDYcJkSDNczJgygjS+35Wmok9npM6jfWLYO4nJDHct55LLjiKEXHWaYiG7AYWj+T5OUYfwDKSDA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:53:54.424407Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.05365","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d8e59b958719e74cc31e168eddc21c921e98a6eb4c3e16364d2e3d9de943fb34","sha256:5e66f224f6c5157ead513839cf3c4421dfb8078d280e2a92faa4115652583123"],"state_sha256":"a9e482ae9e492154a81f524294d11b30e713a6e173b7bd1d3198c5d374b7a181"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IDfQgCXIxWiZS/gbYJ7USTrd0Y7diHvIAUs0LrRqWx4WoI04DiGEOHBlPwAvDOlGdtSSIh2u9iyn3kkndPm+DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T13:51:08.991598Z","bundle_sha256":"d0540ce320415d502a2025a8157b8abff13005030be97440035ad7262f9d3a0d"}}