{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:65TGQBRZONQT7GG5OESB7FI7SD","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":"02c86548b6e8f5c56e18dfc0dbebe9a93b62334b3a1434aa0b0b904e772b8230","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-13T19:19:23Z","title_canon_sha256":"133ab6398ed266797acf2ab87b4f2cc864e6c1d2ee2cbbed06e8aaaabaa94af9"},"schema_version":"1.0","source":{"id":"2302.06646","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.06646","created_at":"2026-07-05T05:41:42Z"},{"alias_kind":"arxiv_version","alias_value":"2302.06646v1","created_at":"2026-07-05T05:41:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.06646","created_at":"2026-07-05T05:41:42Z"},{"alias_kind":"pith_short_12","alias_value":"65TGQBRZONQT","created_at":"2026-07-05T05:41:42Z"},{"alias_kind":"pith_short_16","alias_value":"65TGQBRZONQT7GG5","created_at":"2026-07-05T05:41:42Z"},{"alias_kind":"pith_short_8","alias_value":"65TGQBRZ","created_at":"2026-07-05T05:41:42Z"}],"graph_snapshots":[{"event_id":"sha256:24ac40363204a2e3632af70b5d3f8a330609fc14be93b60b41323dedf72b7e8a","target":"graph","created_at":"2026-07-05T05:41:42Z","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/2302.06646/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"State space models (SSMs) have high performance on long sequence modeling but require sophisticated initialization techniques and specialized implementations for high quality and runtime performance. We study whether a simple alternative can match SSMs in performance and efficiency: directly learning long convolutions over the sequence. We find that a key requirement to achieving high performance is keeping the convolution kernels smooth. We find that simple interventions--such as squashing the kernel weights--result in smooth kernels and recover SSM performance on a range of tasks including t","authors_text":"Armin W. Thomas, Atri Rudra, Christopher R\\'e, Daniel Y. Fu, Elliot L. Epstein, Eric Nguyen, Michael Zhang, Tri Dao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-13T19:19:23Z","title":"Simple Hardware-Efficient Long Convolutions for Sequence Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.06646","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":"sha256:17aa31b41cf02b2a3df2f8c632c20ebd260f4858a676ecf3871d68c11aa1acfa","target":"record","created_at":"2026-07-05T05:41:42Z","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":"02c86548b6e8f5c56e18dfc0dbebe9a93b62334b3a1434aa0b0b904e772b8230","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-02-13T19:19:23Z","title_canon_sha256":"133ab6398ed266797acf2ab87b4f2cc864e6c1d2ee2cbbed06e8aaaabaa94af9"},"schema_version":"1.0","source":{"id":"2302.06646","kind":"arxiv","version":1}},"canonical_sha256":"f76668063973613f98dd71241f951f90d344246c6c43a109eb9a4bb5472a4f13","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f76668063973613f98dd71241f951f90d344246c6c43a109eb9a4bb5472a4f13","first_computed_at":"2026-07-05T05:41:42.335367Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:41:42.335367Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"d+oWivVqdGEamkLrEjosZhdeJ5GVUsoE+4uy/TdC9wYNXN0XQ1pseYb/Z786RCMJRINic+12O6+8NVblzL2gDw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:41:42.335852Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.06646","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:17aa31b41cf02b2a3df2f8c632c20ebd260f4858a676ecf3871d68c11aa1acfa","sha256:24ac40363204a2e3632af70b5d3f8a330609fc14be93b60b41323dedf72b7e8a"],"state_sha256":"952898c850ef1f93c9834ed6d5a2299a505b13f738b9cd6bee63a7c0e1bd04ff"}