{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:27FVDDJ6AJHXOYGSTABRD2BYM6","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":"3a8e41d201637ccce821bf1bf3ed3973cd763dd1f676e246fad81399fd27c4bf","cross_cats_sorted":["cs.CL","cs.SD","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-14T22:13:11Z","title_canon_sha256":"85f883105fbd7a28b2761eace9c000c2fb77e8b83a57f86ddb8033026b9c7c9a"},"schema_version":"1.0","source":{"id":"2212.07525","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2212.07525","created_at":"2026-07-05T06:21:05Z"},{"alias_kind":"arxiv_version","alias_value":"2212.07525v2","created_at":"2026-07-05T06:21:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.07525","created_at":"2026-07-05T06:21:05Z"},{"alias_kind":"pith_short_12","alias_value":"27FVDDJ6AJHX","created_at":"2026-07-05T06:21:05Z"},{"alias_kind":"pith_short_16","alias_value":"27FVDDJ6AJHXOYGS","created_at":"2026-07-05T06:21:05Z"},{"alias_kind":"pith_short_8","alias_value":"27FVDDJ6","created_at":"2026-07-05T06:21:05Z"}],"graph_snapshots":[{"event_id":"sha256:473312b5a0ea37a87f437bd79966e72ee2aeaa83c8e055c7eb0e716d10ca43fb","target":"graph","created_at":"2026-07-05T06:21:05Z","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/2212.07525/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current self-supervised learning algorithms are often modality-specific and require large amounts of computational resources. To address these issues, we increase the training efficiency of data2vec, a learning objective that generalizes across several modalities. We do not encode masked tokens, use a fast convolutional decoder and amortize the effort to build teacher representations. data2vec 2.0 benefits from the rich contextualized target representations introduced in data2vec which enable a fast self-supervised learner. Experiments on ImageNet-1K image classification show that data2vec 2.0","authors_text":"Alexei Baevski, Arun Babu, Michael Auli, Wei-Ning Hsu","cross_cats":["cs.CL","cs.SD","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-14T22:13:11Z","title":"Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and Language"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.07525","kind":"arxiv","version":2},"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:bcafe086771bd1882d8cb59652d514be20bc19a1f30212fd25cdc9737dda5940","target":"record","created_at":"2026-07-05T06:21:05Z","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":"3a8e41d201637ccce821bf1bf3ed3973cd763dd1f676e246fad81399fd27c4bf","cross_cats_sorted":["cs.CL","cs.SD","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-12-14T22:13:11Z","title_canon_sha256":"85f883105fbd7a28b2761eace9c000c2fb77e8b83a57f86ddb8033026b9c7c9a"},"schema_version":"1.0","source":{"id":"2212.07525","kind":"arxiv","version":2}},"canonical_sha256":"d7cb518d3e024f7760d2980311e83867915aecd531ec6a734164b18df8d825d4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d7cb518d3e024f7760d2980311e83867915aecd531ec6a734164b18df8d825d4","first_computed_at":"2026-07-05T06:21:05.246745Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:21:05.246745Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hCqrLHzWTYza+vi/arzGWbHhbu08JtBfp5NWn2G/4mfGmtJF0m9T4LHDMLv5eFm0Lpa6TP9MdwJ7UL5oMvEYBA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:21:05.247226Z","signed_message":"canonical_sha256_bytes"},"source_id":"2212.07525","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bcafe086771bd1882d8cb59652d514be20bc19a1f30212fd25cdc9737dda5940","sha256:473312b5a0ea37a87f437bd79966e72ee2aeaa83c8e055c7eb0e716d10ca43fb"],"state_sha256":"e34a62c56139d374661562a5f2de1c51dc00cc2a579fe7b5ebedeb69cd89e037"}