{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:XWU6QESSEAHQRJGPB72UI6DEOK","short_pith_number":"pith:XWU6QESS","schema_version":"1.0","canonical_sha256":"bda9e81252200f08a4cf0ff544786472b2f15e834cd303fe53ce5b244436f3a4","source":{"kind":"arxiv","id":"2607.15404","version":1},"attestation_state":"computed","paper":{"title":"Closed-Loop Bayesian Bandit Encoder with GRAND Receiver for a Bursty Interference Channel","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.SP","math.IT"],"primary_cat":"cs.IT","authors_text":"Bhaskar Krishnamachari","submitted_at":"2026-07-16T19:14:28Z","abstract_excerpt":"Interleaving mitigates burst errors but introduces decoding delay and removes temporal error structure that a channel-aware decoder could exploit. We consider packet-level selection between a random linear code and the same code used with cross-codeword interleaving, over a channel with an unknown number of on/off interferers. The receiver uses Guessing Random Additive Noise Decoding (GRAND) with a replaceable noise model and feeds aggregate channel statistics back to a Bayesian estimator at the transmitter. Once the interference amplitudes and timing parameters are estimated, the receiver's n"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2607.15404","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2026-07-16T19:14:28Z","cross_cats_sorted":["cs.LG","eess.SP","math.IT"],"title_canon_sha256":"dc6ba28c8321dbd3eef76aa90204dc187895e0f2ba8b39116f5cd08b874e2508","abstract_canon_sha256":"978419bfd07a7c90ab21dff1ee78d877e5a74371ca861fc340640e2febd032b5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-20T00:18:31.907939Z","signature_b64":"tm2KlzCs4WsR43gpzQm5vIlR6EXPT2t7HA5qc1DMr3YWLk4FN538Rnxdml98ob26G5s6D4f/DxmnwE7VytSMAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bda9e81252200f08a4cf0ff544786472b2f15e834cd303fe53ce5b244436f3a4","last_reissued_at":"2026-07-20T00:18:31.907128Z","signature_status":"signed_v1","first_computed_at":"2026-07-20T00:18:31.907128Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Closed-Loop Bayesian Bandit Encoder with GRAND Receiver for a Bursty Interference Channel","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.SP","math.IT"],"primary_cat":"cs.IT","authors_text":"Bhaskar Krishnamachari","submitted_at":"2026-07-16T19:14:28Z","abstract_excerpt":"Interleaving mitigates burst errors but introduces decoding delay and removes temporal error structure that a channel-aware decoder could exploit. We consider packet-level selection between a random linear code and the same code used with cross-codeword interleaving, over a channel with an unknown number of on/off interferers. The receiver uses Guessing Random Additive Noise Decoding (GRAND) with a replaceable noise model and feeds aggregate channel statistics back to a Bayesian estimator at the transmitter. Once the interference amplitudes and timing parameters are estimated, the receiver's n"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.15404","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.15404/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2607.15404","created_at":"2026-07-20T00:18:31.907557+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.15404v1","created_at":"2026-07-20T00:18:31.907557+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.15404","created_at":"2026-07-20T00:18:31.907557+00:00"},{"alias_kind":"pith_short_12","alias_value":"XWU6QESSEAHQ","created_at":"2026-07-20T00:18:31.907557+00:00"},{"alias_kind":"pith_short_16","alias_value":"XWU6QESSEAHQRJGP","created_at":"2026-07-20T00:18:31.907557+00:00"},{"alias_kind":"pith_short_8","alias_value":"XWU6QESS","created_at":"2026-07-20T00:18:31.907557+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XWU6QESSEAHQRJGPB72UI6DEOK","json":"https://pith.science/pith/XWU6QESSEAHQRJGPB72UI6DEOK.json","graph_json":"https://pith.science/api/pith-number/XWU6QESSEAHQRJGPB72UI6DEOK/graph.json","events_json":"https://pith.science/api/pith-number/XWU6QESSEAHQRJGPB72UI6DEOK/events.json","paper":"https://pith.science/paper/XWU6QESS"},"agent_actions":{"view_html":"https://pith.science/pith/XWU6QESSEAHQRJGPB72UI6DEOK","download_json":"https://pith.science/pith/XWU6QESSEAHQRJGPB72UI6DEOK.json","view_paper":"https://pith.science/paper/XWU6QESS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.15404&json=true","fetch_graph":"https://pith.science/api/pith-number/XWU6QESSEAHQRJGPB72UI6DEOK/graph.json","fetch_events":"https://pith.science/api/pith-number/XWU6QESSEAHQRJGPB72UI6DEOK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XWU6QESSEAHQRJGPB72UI6DEOK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XWU6QESSEAHQRJGPB72UI6DEOK/action/storage_attestation","attest_author":"https://pith.science/pith/XWU6QESSEAHQRJGPB72UI6DEOK/action/author_attestation","sign_citation":"https://pith.science/pith/XWU6QESSEAHQRJGPB72UI6DEOK/action/citation_signature","submit_replication":"https://pith.science/pith/XWU6QESSEAHQRJGPB72UI6DEOK/action/replication_record"}},"created_at":"2026-07-20T00:18:31.907557+00:00","updated_at":"2026-07-20T00:18:31.907557+00:00"}