{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:EPRAPUBQMJWT3TUOFACXKEMBQA","short_pith_number":"pith:EPRAPUBQ","canonical_record":{"source":{"id":"2106.08062","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-06-15T11:40:23Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"c7f8ed31eb4a5f543120f78cd39989a464475f3da45463c6f415310d132c4b97","abstract_canon_sha256":"b1b23bb0b0f90035cee784d66c7fbe2a4ceb3d70a1333d41a3bcc347ef8d1ed8"},"schema_version":"1.0"},"canonical_sha256":"23e207d030626d3dce8e2805751181800e8b83bb3cc8f7d717ac3e5fca2deaa9","source":{"kind":"arxiv","id":"2106.08062","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.08062","created_at":"2026-07-05T02:49:37Z"},{"alias_kind":"arxiv_version","alias_value":"2106.08062v1","created_at":"2026-07-05T02:49:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.08062","created_at":"2026-07-05T02:49:37Z"},{"alias_kind":"pith_short_12","alias_value":"EPRAPUBQMJWT","created_at":"2026-07-05T02:49:37Z"},{"alias_kind":"pith_short_16","alias_value":"EPRAPUBQMJWT3TUO","created_at":"2026-07-05T02:49:37Z"},{"alias_kind":"pith_short_8","alias_value":"EPRAPUBQ","created_at":"2026-07-05T02:49:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:EPRAPUBQMJWT3TUOFACXKEMBQA","target":"record","payload":{"canonical_record":{"source":{"id":"2106.08062","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-06-15T11:40:23Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"c7f8ed31eb4a5f543120f78cd39989a464475f3da45463c6f415310d132c4b97","abstract_canon_sha256":"b1b23bb0b0f90035cee784d66c7fbe2a4ceb3d70a1333d41a3bcc347ef8d1ed8"},"schema_version":"1.0"},"canonical_sha256":"23e207d030626d3dce8e2805751181800e8b83bb3cc8f7d717ac3e5fca2deaa9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:49:37.405787Z","signature_b64":"/yE3+cB2UevZm+T+NeaDJ06tIK8u4ra6nr/HPzyYj92JtKytHcLwF38jiv5CFkcJvQHjP/EmpdPmbOj9TmYIAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"23e207d030626d3dce8e2805751181800e8b83bb3cc8f7d717ac3e5fca2deaa9","last_reissued_at":"2026-07-05T02:49:37.405293Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:49:37.405293Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.08062","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":"2026-07-05T02:49:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2pYp4s8eKcn9H6pW3t3d47VdrKqx1MrtgVQMN6SavB1rCp5C4HdpF2hTXnCHAfz0EOpbRPCuE/qe3ZnSURZ6CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T06:41:43.446859Z"},"content_sha256":"edefb27cce529f8d43e836f28b2d7fcea32f2e279de5cf3b9073fc7f401e5bff","schema_version":"1.0","event_id":"sha256:edefb27cce529f8d43e836f28b2d7fcea32f2e279de5cf3b9073fc7f401e5bff"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:EPRAPUBQMJWT3TUOFACXKEMBQA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SSMix: Saliency-Based Span Mixup for Text Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Gyuwan Kim, Kyumin Park, Soyoung Yoon","submitted_at":"2021-06-15T11:40:23Z","abstract_excerpt":"Data augmentation with mixup has shown to be effective on various computer vision tasks. Despite its great success, there has been a hurdle to apply mixup to NLP tasks since text consists of discrete tokens with variable length. In this work, we propose SSMix, a novel mixup method where the operation is performed on input text rather than on hidden vectors like previous approaches. SSMix synthesizes a sentence while preserving the locality of two original texts by span-based mixing and keeping more tokens related to the prediction relying on saliency information. With extensive experiments, we"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.08062","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/2106.08062/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":"2026-07-05T02:49:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"c/b0Mv/XKMw9H131T30F8ZkMFf8ez2vHaeZRSQXYMRr6mQ1G51xsYqnn6w/ly/B6q9YUNrkJdxQ7Y43qrkx5BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T06:41:43.447353Z"},"content_sha256":"b395d6ef804c2c9ab0bd855f0ad23f0eb755584e10bf8d1fb571e5d0e8f6c8b3","schema_version":"1.0","event_id":"sha256:b395d6ef804c2c9ab0bd855f0ad23f0eb755584e10bf8d1fb571e5d0e8f6c8b3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EPRAPUBQMJWT3TUOFACXKEMBQA/bundle.json","state_url":"https://pith.science/pith/EPRAPUBQMJWT3TUOFACXKEMBQA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EPRAPUBQMJWT3TUOFACXKEMBQA/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":"2026-08-20T06:41:43Z","links":{"resolver":"https://pith.science/pith/EPRAPUBQMJWT3TUOFACXKEMBQA","bundle":"https://pith.science/pith/EPRAPUBQMJWT3TUOFACXKEMBQA/bundle.json","state":"https://pith.science/pith/EPRAPUBQMJWT3TUOFACXKEMBQA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EPRAPUBQMJWT3TUOFACXKEMBQA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:EPRAPUBQMJWT3TUOFACXKEMBQA","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":"b1b23bb0b0f90035cee784d66c7fbe2a4ceb3d70a1333d41a3bcc347ef8d1ed8","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-06-15T11:40:23Z","title_canon_sha256":"c7f8ed31eb4a5f543120f78cd39989a464475f3da45463c6f415310d132c4b97"},"schema_version":"1.0","source":{"id":"2106.08062","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.08062","created_at":"2026-07-05T02:49:37Z"},{"alias_kind":"arxiv_version","alias_value":"2106.08062v1","created_at":"2026-07-05T02:49:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.08062","created_at":"2026-07-05T02:49:37Z"},{"alias_kind":"pith_short_12","alias_value":"EPRAPUBQMJWT","created_at":"2026-07-05T02:49:37Z"},{"alias_kind":"pith_short_16","alias_value":"EPRAPUBQMJWT3TUO","created_at":"2026-07-05T02:49:37Z"},{"alias_kind":"pith_short_8","alias_value":"EPRAPUBQ","created_at":"2026-07-05T02:49:37Z"}],"graph_snapshots":[{"event_id":"sha256:b395d6ef804c2c9ab0bd855f0ad23f0eb755584e10bf8d1fb571e5d0e8f6c8b3","target":"graph","created_at":"2026-07-05T02:49:37Z","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/2106.08062/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Data augmentation with mixup has shown to be effective on various computer vision tasks. Despite its great success, there has been a hurdle to apply mixup to NLP tasks since text consists of discrete tokens with variable length. In this work, we propose SSMix, a novel mixup method where the operation is performed on input text rather than on hidden vectors like previous approaches. SSMix synthesizes a sentence while preserving the locality of two original texts by span-based mixing and keeping more tokens related to the prediction relying on saliency information. With extensive experiments, we","authors_text":"Gyuwan Kim, Kyumin Park, Soyoung Yoon","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-06-15T11:40:23Z","title":"SSMix: Saliency-Based Span Mixup for Text Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.08062","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:edefb27cce529f8d43e836f28b2d7fcea32f2e279de5cf3b9073fc7f401e5bff","target":"record","created_at":"2026-07-05T02:49:37Z","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":"b1b23bb0b0f90035cee784d66c7fbe2a4ceb3d70a1333d41a3bcc347ef8d1ed8","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-06-15T11:40:23Z","title_canon_sha256":"c7f8ed31eb4a5f543120f78cd39989a464475f3da45463c6f415310d132c4b97"},"schema_version":"1.0","source":{"id":"2106.08062","kind":"arxiv","version":1}},"canonical_sha256":"23e207d030626d3dce8e2805751181800e8b83bb3cc8f7d717ac3e5fca2deaa9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"23e207d030626d3dce8e2805751181800e8b83bb3cc8f7d717ac3e5fca2deaa9","first_computed_at":"2026-07-05T02:49:37.405293Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:49:37.405293Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/yE3+cB2UevZm+T+NeaDJ06tIK8u4ra6nr/HPzyYj92JtKytHcLwF38jiv5CFkcJvQHjP/EmpdPmbOj9TmYIAw==","signature_status":"signed_v1","signed_at":"2026-07-05T02:49:37.405787Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.08062","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:edefb27cce529f8d43e836f28b2d7fcea32f2e279de5cf3b9073fc7f401e5bff","sha256:b395d6ef804c2c9ab0bd855f0ad23f0eb755584e10bf8d1fb571e5d0e8f6c8b3"],"state_sha256":"0eea4150349956abd01199bde49d2a53e1ac03a711aabdb0300cae1c565a3481"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/sZze//whsxhDApCQCKMjy+jDM2eX15ji7r1izPHg8tm/0cWwrKsp9M9Vx7mxutRxsFnzlxWFu/AkKDNsZqqAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T06:41:43.451108Z","bundle_sha256":"2269e1aca3946bb9c4ead9191368bb1485225caff56c3dafc5ff0a7ed4b119f1"}}