{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:URURTD65RNUENR2KUPT4W3U5YW","short_pith_number":"pith:URURTD65","canonical_record":{"source":{"id":"2411.08872","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2024-11-13T18:51:10Z","cross_cats_sorted":["eess.SP","math.IT"],"title_canon_sha256":"632a728470ee1bb4211e7c2773bbdf045adfea1f0cc30c6cdb99818b8470909d","abstract_canon_sha256":"a8688d5a80be352c1ed7fda2a5beac0b0534dc562e0758981c8c39ca120d8557"},"schema_version":"1.0"},"canonical_sha256":"a469198fdd8b6846c74aa3e7cb6e9dc58b64958ff3c897449dfc34965419821b","source":{"kind":"arxiv","id":"2411.08872","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.08872","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"arxiv_version","alias_value":"2411.08872v2","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.08872","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"pith_short_12","alias_value":"URURTD65RNUE","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"pith_short_16","alias_value":"URURTD65RNUENR2K","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"pith_short_8","alias_value":"URURTD65","created_at":"2026-07-05T10:45:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:URURTD65RNUENR2KUPT4W3U5YW","target":"record","payload":{"canonical_record":{"source":{"id":"2411.08872","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2024-11-13T18:51:10Z","cross_cats_sorted":["eess.SP","math.IT"],"title_canon_sha256":"632a728470ee1bb4211e7c2773bbdf045adfea1f0cc30c6cdb99818b8470909d","abstract_canon_sha256":"a8688d5a80be352c1ed7fda2a5beac0b0534dc562e0758981c8c39ca120d8557"},"schema_version":"1.0"},"canonical_sha256":"a469198fdd8b6846c74aa3e7cb6e9dc58b64958ff3c897449dfc34965419821b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:45:38.438645Z","signature_b64":"bDEHKjx6jVQ2MYbCxzrDQYEK2uV4MDytRbwAzLpkL/nrh6PAUTLOWUdCQSN3k4sCRkj7o475mDJXlyExTsm8DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a469198fdd8b6846c74aa3e7cb6e9dc58b64958ff3c897449dfc34965419821b","last_reissued_at":"2026-07-05T10:45:38.438088Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:45:38.438088Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.08872","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:45:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y3RkNxMQF9u8bkHlNAFBg2cLQNv8A7B4b4bhVhGVCFjRT2QpxgMmAPoWweU3CaE99CGD4if0iLvxSm7wDu7XCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T03:22:29.196423Z"},"content_sha256":"82b6d1b9988788d49df84e8bbff807d6057789f19aedad7b27c8141ee2044f66","schema_version":"1.0","event_id":"sha256:82b6d1b9988788d49df84e8bbff807d6057789f19aedad7b27c8141ee2044f66"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:URURTD65RNUENR2KUPT4W3U5YW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Large Wireless Model (LWM): A Foundation Model for Wireless Channels","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["eess.SP","math.IT"],"primary_cat":"cs.IT","authors_text":"Ahmed Alkhateeb, Gouranga Charan, Sadjad Alikhani","submitted_at":"2024-11-13T18:51:10Z","abstract_excerpt":"This paper presents Large Wireless Model (LWM) -- the world's first foundation model for wireless channels. Designed as a task-agnostic model, LWM generates universal, rich, contextualized channel embeddings (features) that potentially enhance performance across a wide range of downstream tasks in wireless communication and sensing systems. Towards this objective, LWM, which has a transformer-based architecture, was pre-trained in a self-supervised manner on large-scale wireless channel datasets. Our results show consistent improvements in downstream tasks when using the LWM embeddings compare"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.08872","kind":"arxiv","version":2},"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/2411.08872/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:45:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Couiw8z4huylZF/Ct6nCKwo/a0wRTPaLfIWgSCypnls2Gsg9a57hQE++ISYZIftJs7xc+pwHukmAHrA7YB2JAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T03:22:29.197072Z"},"content_sha256":"880497d934cb30bb3f96f3ba67e7aabc6c0a2f7da9a14125119685a7c10e0c2f","schema_version":"1.0","event_id":"sha256:880497d934cb30bb3f96f3ba67e7aabc6c0a2f7da9a14125119685a7c10e0c2f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/URURTD65RNUENR2KUPT4W3U5YW/bundle.json","state_url":"https://pith.science/pith/URURTD65RNUENR2KUPT4W3U5YW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/URURTD65RNUENR2KUPT4W3U5YW/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-05T03:22:29Z","links":{"resolver":"https://pith.science/pith/URURTD65RNUENR2KUPT4W3U5YW","bundle":"https://pith.science/pith/URURTD65RNUENR2KUPT4W3U5YW/bundle.json","state":"https://pith.science/pith/URURTD65RNUENR2KUPT4W3U5YW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/URURTD65RNUENR2KUPT4W3U5YW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:URURTD65RNUENR2KUPT4W3U5YW","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":"a8688d5a80be352c1ed7fda2a5beac0b0534dc562e0758981c8c39ca120d8557","cross_cats_sorted":["eess.SP","math.IT"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2024-11-13T18:51:10Z","title_canon_sha256":"632a728470ee1bb4211e7c2773bbdf045adfea1f0cc30c6cdb99818b8470909d"},"schema_version":"1.0","source":{"id":"2411.08872","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.08872","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"arxiv_version","alias_value":"2411.08872v2","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.08872","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"pith_short_12","alias_value":"URURTD65RNUE","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"pith_short_16","alias_value":"URURTD65RNUENR2K","created_at":"2026-07-05T10:45:38Z"},{"alias_kind":"pith_short_8","alias_value":"URURTD65","created_at":"2026-07-05T10:45:38Z"}],"graph_snapshots":[{"event_id":"sha256:880497d934cb30bb3f96f3ba67e7aabc6c0a2f7da9a14125119685a7c10e0c2f","target":"graph","created_at":"2026-07-05T10:45:38Z","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/2411.08872/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper presents Large Wireless Model (LWM) -- the world's first foundation model for wireless channels. Designed as a task-agnostic model, LWM generates universal, rich, contextualized channel embeddings (features) that potentially enhance performance across a wide range of downstream tasks in wireless communication and sensing systems. Towards this objective, LWM, which has a transformer-based architecture, was pre-trained in a self-supervised manner on large-scale wireless channel datasets. Our results show consistent improvements in downstream tasks when using the LWM embeddings compare","authors_text":"Ahmed Alkhateeb, Gouranga Charan, Sadjad Alikhani","cross_cats":["eess.SP","math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2024-11-13T18:51:10Z","title":"Large Wireless Model (LWM): A Foundation Model for Wireless Channels"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.08872","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":"sha256:82b6d1b9988788d49df84e8bbff807d6057789f19aedad7b27c8141ee2044f66","target":"record","created_at":"2026-07-05T10:45:38Z","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":"a8688d5a80be352c1ed7fda2a5beac0b0534dc562e0758981c8c39ca120d8557","cross_cats_sorted":["eess.SP","math.IT"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.IT","submitted_at":"2024-11-13T18:51:10Z","title_canon_sha256":"632a728470ee1bb4211e7c2773bbdf045adfea1f0cc30c6cdb99818b8470909d"},"schema_version":"1.0","source":{"id":"2411.08872","kind":"arxiv","version":2}},"canonical_sha256":"a469198fdd8b6846c74aa3e7cb6e9dc58b64958ff3c897449dfc34965419821b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a469198fdd8b6846c74aa3e7cb6e9dc58b64958ff3c897449dfc34965419821b","first_computed_at":"2026-07-05T10:45:38.438088Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:45:38.438088Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bDEHKjx6jVQ2MYbCxzrDQYEK2uV4MDytRbwAzLpkL/nrh6PAUTLOWUdCQSN3k4sCRkj7o475mDJXlyExTsm8DA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:45:38.438645Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.08872","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82b6d1b9988788d49df84e8bbff807d6057789f19aedad7b27c8141ee2044f66","sha256:880497d934cb30bb3f96f3ba67e7aabc6c0a2f7da9a14125119685a7c10e0c2f"],"state_sha256":"f0134f3c14c11680b2f7534cb2370fb42c2df556204d8026f02710723ab0095e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2yUiJ/br5MqH75Y9X2glvbS4QAL1UPC/B8k7TDtnptkkCoeTMTu038D/ED0ZOgK51RhxERlgPYQHRuMjioyHBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T03:22:29.200670Z","bundle_sha256":"2a847fa950ce1a025df6d6e59d3571d0375f5abcd202a659c0d4d96eab2730df"}}