{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:WMRPMVEHTWVS4MJYWLWQNI3VW2","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":"fb9c89cb9953497a61441167ca1b1fc71f7fd7824e4520d2ca457c459bd9c344","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2021-06-10T15:41:53Z","title_canon_sha256":"88225ebe0f92bdb5e69b2d4d3314f02cc907995c271eb76488e239c0aaf1e9e6"},"schema_version":"1.0","source":{"id":"2106.05822","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.05822","created_at":"2026-07-05T02:48:13Z"},{"alias_kind":"arxiv_version","alias_value":"2106.05822v1","created_at":"2026-07-05T02:48:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.05822","created_at":"2026-07-05T02:48:13Z"},{"alias_kind":"pith_short_12","alias_value":"WMRPMVEHTWVS","created_at":"2026-07-05T02:48:13Z"},{"alias_kind":"pith_short_16","alias_value":"WMRPMVEHTWVS4MJY","created_at":"2026-07-05T02:48:13Z"},{"alias_kind":"pith_short_8","alias_value":"WMRPMVEH","created_at":"2026-07-05T02:48:13Z"}],"graph_snapshots":[{"event_id":"sha256:5cfba857ce208d9a44d0c3f8fdb8f1e72191b79c9ae9f6a2f5c9b3ae3d905624","target":"graph","created_at":"2026-07-05T02:48:13Z","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/2106.05822/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Attention based language models have become a critical component in state-of-the-art natural language processing systems. However, these models have significant computational requirements, due to long training times, dense operations and large parameter count. In this work we demonstrate a set of modifications to the structure of a Transformer layer, producing a more efficient architecture. First, we add a convolutional module to complement the self-attention module, decoupling the learning of local and global interactions. Secondly, we rely on grouped transformations to reduce the computation","authors_text":"Alexandros Koliousis, Anastasia Dietrich, Carlo Luschi, Daniel Justus, Douglas Orr, Frithjof Gressmann, Ivan Chelombiev","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2021-06-10T15:41:53Z","title":"GroupBERT: Enhanced Transformer Architecture with Efficient Grouped Structures"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.05822","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:e67ccb1c4960f75c3e99f78b8aaa74e208f00130f7b2ddcf50476e5e7e1d5b1e","target":"record","created_at":"2026-07-05T02:48:13Z","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":"fb9c89cb9953497a61441167ca1b1fc71f7fd7824e4520d2ca457c459bd9c344","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2021-06-10T15:41:53Z","title_canon_sha256":"88225ebe0f92bdb5e69b2d4d3314f02cc907995c271eb76488e239c0aaf1e9e6"},"schema_version":"1.0","source":{"id":"2106.05822","kind":"arxiv","version":1}},"canonical_sha256":"b322f654879dab2e3138b2ed06a375b68701bea400146eade3149c162cc7b8e1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b322f654879dab2e3138b2ed06a375b68701bea400146eade3149c162cc7b8e1","first_computed_at":"2026-07-05T02:48:13.406910Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:48:13.406910Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LqfWRtTuySh67FFfpgMeDvP/JG6z4yMuy2a9a7XBgFvdjf6xANCBawg9LL7ZQTsi41qsKVZIs67V35F764bkAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:48:13.407392Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.05822","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e67ccb1c4960f75c3e99f78b8aaa74e208f00130f7b2ddcf50476e5e7e1d5b1e","sha256:5cfba857ce208d9a44d0c3f8fdb8f1e72191b79c9ae9f6a2f5c9b3ae3d905624"],"state_sha256":"052233e6350f7412a44e3588388d12c792fa5ebc53f8019a76e32ab9fbc6144b"}