{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:GG2ISNBPN7C4OOK6O4HJ2NKOVJ","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":"0defb17dcdf773bf92e288c87125b9796df1ae7c8173fdbb3bd3f88d65511ad9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-06-08T06:32:41Z","title_canon_sha256":"72d3253a6eca83971d7b75845fe6bdf284293e18fa707a4fd3823b565ca5b528"},"schema_version":"1.0","source":{"id":"2606.09085","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.09085","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"arxiv_version","alias_value":"2606.09085v1","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.09085","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"pith_short_12","alias_value":"GG2ISNBPN7C4","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"pith_short_16","alias_value":"GG2ISNBPN7C4OOK6","created_at":"2026-06-09T02:07:58Z"},{"alias_kind":"pith_short_8","alias_value":"GG2ISNBP","created_at":"2026-06-09T02:07:58Z"}],"graph_snapshots":[{"event_id":"sha256:3ac95a913996192ab76157003dcf4a5925c93501df3acceed9f3e277ba55723c","target":"graph","created_at":"2026-06-09T02:07:58Z","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/2606.09085/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Automatic Modulation Recognition (AMR) is a key enabling technology for cognitive radio and intelligent spectrum management in next-generation wireless systems. However, current deep learning-based AMR methods predominantly rely on static multi-scale fusion strategies, which lack the flexibility to adapt to the highly dynamic temporal variations of modulation signals. To address this limitation, we propose MoEformer, an adaptive Multi-Scale Mixture-of-Experts Transformer network that directly processes I/Q signals to preserve their temporal and phase structures. Specifically, MoEformer constru","authors_text":"Jiale Wang, Jingwei Zhang, Wupeng Xie, Xin Liu, Yaxin Mu, Zhilong Zhao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-06-08T06:32:41Z","title":"Mixture-of-Experts Transformer for Automatic Modulation Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.09085","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":"sha256:3f7892f4d5b62d9d7775137e6bbddb0a19a4479538845778654889543bff0916","target":"record","created_at":"2026-06-09T02:07:58Z","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":"0defb17dcdf773bf92e288c87125b9796df1ae7c8173fdbb3bd3f88d65511ad9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-06-08T06:32:41Z","title_canon_sha256":"72d3253a6eca83971d7b75845fe6bdf284293e18fa707a4fd3823b565ca5b528"},"schema_version":"1.0","source":{"id":"2606.09085","kind":"arxiv","version":1}},"canonical_sha256":"31b489342f6fc5c7395e770e9d354eaa7f04835344d3f1da42f308dcfed16d7c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"31b489342f6fc5c7395e770e9d354eaa7f04835344d3f1da42f308dcfed16d7c","first_computed_at":"2026-06-09T02:07:58.117128Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-09T02:07:58.117128Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KoDLScARV3kerZALlOhKOAhcH+LkTx/IV8rrDZyUI/lF3r7+olXI6zlv0R6YwYY2WkIORfNV5KKxWzlURYDqAA==","signature_status":"signed_v1","signed_at":"2026-06-09T02:07:58.118024Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.09085","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3f7892f4d5b62d9d7775137e6bbddb0a19a4479538845778654889543bff0916","sha256:3ac95a913996192ab76157003dcf4a5925c93501df3acceed9f3e277ba55723c"],"state_sha256":"1ae725c98ef5c0168f41a1fe1e8ea71a418f8e897277590673764ef9943c9e9a"}