{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:E7QWSAOEXZT7GVKIHEIYTQEMRJ","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":"2ef90ac3b8006979a3bbf273ec44b5058dccc841671e614fbf73bde45e89c538","cross_cats_sorted":["cs.LG","cs.SD","eess.SP"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.AS","submitted_at":"2019-09-29T22:26:06Z","title_canon_sha256":"64f5cbbe38a7751eca08e3c1ae962674e8e9a4915a26c4d158f4c81fc656b1e3"},"schema_version":"1.0","source":{"id":"1909.13387","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1909.13387","created_at":"2026-07-05T00:08:41Z"},{"alias_kind":"arxiv_version","alias_value":"1909.13387v2","created_at":"2026-07-05T00:08:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1909.13387","created_at":"2026-07-05T00:08:41Z"},{"alias_kind":"pith_short_12","alias_value":"E7QWSAOEXZT7","created_at":"2026-07-05T00:08:41Z"},{"alias_kind":"pith_short_16","alias_value":"E7QWSAOEXZT7GVKI","created_at":"2026-07-05T00:08:41Z"},{"alias_kind":"pith_short_8","alias_value":"E7QWSAOE","created_at":"2026-07-05T00:08:41Z"}],"graph_snapshots":[{"event_id":"sha256:1ed78e01fc631285d4c9c7242701cf1b352d31cbc212b19b509905694da93b03","target":"graph","created_at":"2026-07-05T00:08:41Z","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/1909.13387/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Beamforming has been extensively investigated for multi-channel audio processing tasks. Recently, learning-based beamforming methods, sometimes called \\textit{neural beamformers}, have achieved significant improvements in both signal quality (e.g. signal-to-noise ratio (SNR)) and speech recognition (e.g. word error rate (WER)). Such systems are generally non-causal and require a large context for robust estimation of inter-channel features, which is impractical in applications requiring low-latency responses. In this paper, we propose filter-and-sum network (FaSNet), a time-domain, filter-base","authors_text":"Cong Han, Enea Ceolini, Nima Mesgarani, Shih-Chii Liu, Yi Luo","cross_cats":["cs.LG","cs.SD","eess.SP"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.AS","submitted_at":"2019-09-29T22:26:06Z","title":"FaSNet: Low-latency Adaptive Beamforming for Multi-microphone Audio Processing"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1909.13387","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":"sha256:96f415eff349fa53ce9417fd5fbb2fa1e605d84669e7e3ce5730a13c7c6bfe42","target":"record","created_at":"2026-07-05T00:08:41Z","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":"2ef90ac3b8006979a3bbf273ec44b5058dccc841671e614fbf73bde45e89c538","cross_cats_sorted":["cs.LG","cs.SD","eess.SP"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.AS","submitted_at":"2019-09-29T22:26:06Z","title_canon_sha256":"64f5cbbe38a7751eca08e3c1ae962674e8e9a4915a26c4d158f4c81fc656b1e3"},"schema_version":"1.0","source":{"id":"1909.13387","kind":"arxiv","version":2}},"canonical_sha256":"27e16901c4be67f35548391189c08c8a77a65bcbf9495d2ca63c40cc151a81f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"27e16901c4be67f35548391189c08c8a77a65bcbf9495d2ca63c40cc151a81f3","first_computed_at":"2026-07-05T00:08:41.412463Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:08:41.412463Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"s8l1vtz6rKqzWHCM27eR9PdN+McsyoC53VV0r7YiKoTMlhfARvaNPqEL+vkcLWrbHG1ihnC95dJhf9S62T0EAA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:08:41.413011Z","signed_message":"canonical_sha256_bytes"},"source_id":"1909.13387","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:96f415eff349fa53ce9417fd5fbb2fa1e605d84669e7e3ce5730a13c7c6bfe42","sha256:1ed78e01fc631285d4c9c7242701cf1b352d31cbc212b19b509905694da93b03"],"state_sha256":"36183d2b22f17d1257a23fd8894177e64a419a2e9363d6e266f120a915c79f30"}