{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:QJ7F2GHJUSABKNVGYABH6JDRAY","short_pith_number":"pith:QJ7F2GHJ","canonical_record":{"source":{"id":"2502.04593","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-07T01:00:16Z","cross_cats_sorted":["cs.AI","cs.NE","stat.ML"],"title_canon_sha256":"bed59555b54a354e5391dd61b8714495ed34068f0298693e23c98fd9bf6ea03c","abstract_canon_sha256":"e6689d87079ff3cc9578c69ff1079c86e02dec5a6394438f32e59f8ad9666e04"},"schema_version":"1.0"},"canonical_sha256":"827e5d18e9a4801536a6c0027f2471060c988ab40a303c3b79faa7bf5e1fdd25","source":{"kind":"arxiv","id":"2502.04593","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.04593","created_at":"2026-07-05T11:08:15Z"},{"alias_kind":"arxiv_version","alias_value":"2502.04593v2","created_at":"2026-07-05T11:08:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.04593","created_at":"2026-07-05T11:08:15Z"},{"alias_kind":"pith_short_12","alias_value":"QJ7F2GHJUSAB","created_at":"2026-07-05T11:08:15Z"},{"alias_kind":"pith_short_16","alias_value":"QJ7F2GHJUSABKNVG","created_at":"2026-07-05T11:08:15Z"},{"alias_kind":"pith_short_8","alias_value":"QJ7F2GHJ","created_at":"2026-07-05T11:08:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:QJ7F2GHJUSABKNVGYABH6JDRAY","target":"record","payload":{"canonical_record":{"source":{"id":"2502.04593","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-07T01:00:16Z","cross_cats_sorted":["cs.AI","cs.NE","stat.ML"],"title_canon_sha256":"bed59555b54a354e5391dd61b8714495ed34068f0298693e23c98fd9bf6ea03c","abstract_canon_sha256":"e6689d87079ff3cc9578c69ff1079c86e02dec5a6394438f32e59f8ad9666e04"},"schema_version":"1.0"},"canonical_sha256":"827e5d18e9a4801536a6c0027f2471060c988ab40a303c3b79faa7bf5e1fdd25","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:08:15.938915Z","signature_b64":"/pnNDrL6u/OviI45VX267lxNpUgf/KAu4xN4AvP9ofVQFEnfjmAS/dxKCJ9bTV8XKKmUOk3jhYHt4A8XygDRCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"827e5d18e9a4801536a6c0027f2471060c988ab40a303c3b79faa7bf5e1fdd25","last_reissued_at":"2026-07-05T11:08:15.938372Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:08:15.938372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.04593","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":"2026-07-05T11:08:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gQxco0Te691DmLD78LFmMk3/Df/NcAq4mZI7f+g+ZoK+zDiavd2UC6golxpJj5BKikbYDY93V2SJfCPYeyeDAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T22:24:28.641431Z"},"content_sha256":"0630a06d6800f7199b251cf84af1a5a31b367fde1dfca9d9c41786bb3c25f2e8","schema_version":"1.0","event_id":"sha256:0630a06d6800f7199b251cf84af1a5a31b367fde1dfca9d9c41786bb3c25f2e8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:QJ7F2GHJUSABKNVGYABH6JDRAY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Alpha-Alternator: Dynamic Adaptation To Varying Noise Levels In Sequences Using The Vendi Score For Improved Robustness and Performance","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.NE","stat.ML"],"primary_cat":"cs.LG","authors_text":"Adji Bousso Dieng, Mohammad Reza Rezaei","submitted_at":"2025-02-07T01:00:16Z","abstract_excerpt":"Current state-of-the-art dynamical models, such as Mamba, assume the same level of noisiness for all elements of a given sequence, which limits their performance on noisy temporal data. In this paper, we introduce the $\\alpha$-Alternator, a novel generative model for time-dependent data that dynamically adapts to the complexity introduced by varying noise levels in sequences. The $\\alpha$-Alternator leverages the Vendi Score (VS), a flexible similarity-based diversity metric, to adjust, at each time step $t$, the influence of the sequence element at time $t$ and the latent representation of th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.04593","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/2502.04593/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":"2026-07-05T11:08:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cFO3N6QsIpjleuosO93QFZhdufo+URh+pu1xDKkxIMDY2Kr7USYzji7CFtBDQWN3bCmtozbFBqWKkif/VP/IBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T22:24:28.642023Z"},"content_sha256":"954647e930d52c4a92ca48b8e24dadd36d17bf728ffc16ef265fe5ef6f93171c","schema_version":"1.0","event_id":"sha256:954647e930d52c4a92ca48b8e24dadd36d17bf728ffc16ef265fe5ef6f93171c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QJ7F2GHJUSABKNVGYABH6JDRAY/bundle.json","state_url":"https://pith.science/pith/QJ7F2GHJUSABKNVGYABH6JDRAY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QJ7F2GHJUSABKNVGYABH6JDRAY/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":"2026-08-09T22:24:28Z","links":{"resolver":"https://pith.science/pith/QJ7F2GHJUSABKNVGYABH6JDRAY","bundle":"https://pith.science/pith/QJ7F2GHJUSABKNVGYABH6JDRAY/bundle.json","state":"https://pith.science/pith/QJ7F2GHJUSABKNVGYABH6JDRAY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QJ7F2GHJUSABKNVGYABH6JDRAY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:QJ7F2GHJUSABKNVGYABH6JDRAY","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":"e6689d87079ff3cc9578c69ff1079c86e02dec5a6394438f32e59f8ad9666e04","cross_cats_sorted":["cs.AI","cs.NE","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-07T01:00:16Z","title_canon_sha256":"bed59555b54a354e5391dd61b8714495ed34068f0298693e23c98fd9bf6ea03c"},"schema_version":"1.0","source":{"id":"2502.04593","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.04593","created_at":"2026-07-05T11:08:15Z"},{"alias_kind":"arxiv_version","alias_value":"2502.04593v2","created_at":"2026-07-05T11:08:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.04593","created_at":"2026-07-05T11:08:15Z"},{"alias_kind":"pith_short_12","alias_value":"QJ7F2GHJUSAB","created_at":"2026-07-05T11:08:15Z"},{"alias_kind":"pith_short_16","alias_value":"QJ7F2GHJUSABKNVG","created_at":"2026-07-05T11:08:15Z"},{"alias_kind":"pith_short_8","alias_value":"QJ7F2GHJ","created_at":"2026-07-05T11:08:15Z"}],"graph_snapshots":[{"event_id":"sha256:954647e930d52c4a92ca48b8e24dadd36d17bf728ffc16ef265fe5ef6f93171c","target":"graph","created_at":"2026-07-05T11:08:15Z","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/2502.04593/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current state-of-the-art dynamical models, such as Mamba, assume the same level of noisiness for all elements of a given sequence, which limits their performance on noisy temporal data. In this paper, we introduce the $\\alpha$-Alternator, a novel generative model for time-dependent data that dynamically adapts to the complexity introduced by varying noise levels in sequences. The $\\alpha$-Alternator leverages the Vendi Score (VS), a flexible similarity-based diversity metric, to adjust, at each time step $t$, the influence of the sequence element at time $t$ and the latent representation of th","authors_text":"Adji Bousso Dieng, Mohammad Reza Rezaei","cross_cats":["cs.AI","cs.NE","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-07T01:00:16Z","title":"The Alpha-Alternator: Dynamic Adaptation To Varying Noise Levels In Sequences Using The Vendi Score For Improved Robustness and Performance"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.04593","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":"sha256:0630a06d6800f7199b251cf84af1a5a31b367fde1dfca9d9c41786bb3c25f2e8","target":"record","created_at":"2026-07-05T11:08:15Z","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":"e6689d87079ff3cc9578c69ff1079c86e02dec5a6394438f32e59f8ad9666e04","cross_cats_sorted":["cs.AI","cs.NE","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-02-07T01:00:16Z","title_canon_sha256":"bed59555b54a354e5391dd61b8714495ed34068f0298693e23c98fd9bf6ea03c"},"schema_version":"1.0","source":{"id":"2502.04593","kind":"arxiv","version":2}},"canonical_sha256":"827e5d18e9a4801536a6c0027f2471060c988ab40a303c3b79faa7bf5e1fdd25","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"827e5d18e9a4801536a6c0027f2471060c988ab40a303c3b79faa7bf5e1fdd25","first_computed_at":"2026-07-05T11:08:15.938372Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:08:15.938372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/pnNDrL6u/OviI45VX267lxNpUgf/KAu4xN4AvP9ofVQFEnfjmAS/dxKCJ9bTV8XKKmUOk3jhYHt4A8XygDRCg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:08:15.938915Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.04593","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0630a06d6800f7199b251cf84af1a5a31b367fde1dfca9d9c41786bb3c25f2e8","sha256:954647e930d52c4a92ca48b8e24dadd36d17bf728ffc16ef265fe5ef6f93171c"],"state_sha256":"f82eba31bc9d960bdf44275787cab30a2a29834aa01aadeadb123baa954038c1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ymua4+Lg6hzaQFr9SBapDN9OQTvyUnS8PI2k2/Q+5zmihDOaW5iqrRFG1uLp6KEqSEdlb3nigR5z0a6vLQn1BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T22:24:28.646044Z","bundle_sha256":"7f5819852c3929841395f8ec87155ee8e95f8f2951cfc0d1141b68f015b5474f"}}