{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:D6U2JGA74PVODC7R3KFYPTLNYN","short_pith_number":"pith:D6U2JGA7","canonical_record":{"source":{"id":"2410.15234","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-19T22:53:27Z","cross_cats_sorted":[],"title_canon_sha256":"94996b77bbb81249d1c2320cc573af3ba5b1c41d1f474e03affe29bc534fc9a3","abstract_canon_sha256":"3ac5c5ec459033acc51209c595d6bfe23e475803119c1c2e58bf062d8c6f875e"},"schema_version":"1.0"},"canonical_sha256":"1fa9a4981fe3eae18bf1da8b87cd6dc3797cb0d93c3c96058a7ea0907fe14777","source":{"kind":"arxiv","id":"2410.15234","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.15234","created_at":"2026-07-05T11:07:15Z"},{"alias_kind":"arxiv_version","alias_value":"2410.15234v3","created_at":"2026-07-05T11:07:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.15234","created_at":"2026-07-05T11:07:15Z"},{"alias_kind":"pith_short_12","alias_value":"D6U2JGA74PVO","created_at":"2026-07-05T11:07:15Z"},{"alias_kind":"pith_short_16","alias_value":"D6U2JGA74PVODC7R","created_at":"2026-07-05T11:07:15Z"},{"alias_kind":"pith_short_8","alias_value":"D6U2JGA7","created_at":"2026-07-05T11:07:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:D6U2JGA74PVODC7R3KFYPTLNYN","target":"record","payload":{"canonical_record":{"source":{"id":"2410.15234","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-19T22:53:27Z","cross_cats_sorted":[],"title_canon_sha256":"94996b77bbb81249d1c2320cc573af3ba5b1c41d1f474e03affe29bc534fc9a3","abstract_canon_sha256":"3ac5c5ec459033acc51209c595d6bfe23e475803119c1c2e58bf062d8c6f875e"},"schema_version":"1.0"},"canonical_sha256":"1fa9a4981fe3eae18bf1da8b87cd6dc3797cb0d93c3c96058a7ea0907fe14777","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:07:15.778735Z","signature_b64":"P/0UN8ZNQMKMABcpsOYBMYqwdUNLOK+jy2v5DIqEuLOus/QFLokGN10J9q9k9ja5DRBtlarX/+sXGDuiVJU8Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1fa9a4981fe3eae18bf1da8b87cd6dc3797cb0d93c3c96058a7ea0907fe14777","last_reissued_at":"2026-07-05T11:07:15.778234Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:07:15.778234Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.15234","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:07:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bQoJk8Ln4TGN2t0lZh9lQQNrljYTl93NV0AuxCFisAvkVBAxyiuEm4vOAbCpdiqT9W4O2H8CbOfbiMdsv5lYCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T18:34:45.016876Z"},"content_sha256":"cd0d8645a103437cf17493f9a87157fc25d56fb0b9a10f828a7ec00ab9d1ca74","schema_version":"1.0","event_id":"sha256:cd0d8645a103437cf17493f9a87157fc25d56fb0b9a10f828a7ec00ab9d1ca74"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:D6U2JGA74PVODC7R3KFYPTLNYN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bias Amplification: Large Language Models as Increasingly Biased Media","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Adriano Koshiyama, Jeremy Zhang, Navya Jain, Saloni Gupta, Skylar Lu, Xin Guan, Zekun Wu, Ze Wang","submitted_at":"2024-10-19T22:53:27Z","abstract_excerpt":"Model collapse, a phenomenon characterized by performance degradation due to iterative training on synthetic data, has been widely studied. However, its implications for bias amplification, the progressive intensification of pre-existing societal biases in Large Language Models (LLMs), remain significantly underexplored, despite the growing influence of LLMs in shaping online discourse. In this paper, we introduce a open, generational, and long-context benchmark specifically designed to measure political bias amplification in LLMs, leveraging sentence continuation tasks derived from a comprehe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.15234","kind":"arxiv","version":3},"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/2410.15234/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":"2026-07-05T11:07:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/xuobJ4jybwbor1fEWp7/g6MWwf1GdZBIr7TNMOfb04yp9FpA2x6/S/j7p//7AgIw5iPxAB67TcJa2R6PGDrBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T18:34:45.017396Z"},"content_sha256":"20b4dd85c76d3a12e7af3381a8db5fbb658f5c0e228df7da191d6ffbc95f6d94","schema_version":"1.0","event_id":"sha256:20b4dd85c76d3a12e7af3381a8db5fbb658f5c0e228df7da191d6ffbc95f6d94"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/D6U2JGA74PVODC7R3KFYPTLNYN/bundle.json","state_url":"https://pith.science/pith/D6U2JGA74PVODC7R3KFYPTLNYN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/D6U2JGA74PVODC7R3KFYPTLNYN/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":"2026-08-17T18:34:45Z","links":{"resolver":"https://pith.science/pith/D6U2JGA74PVODC7R3KFYPTLNYN","bundle":"https://pith.science/pith/D6U2JGA74PVODC7R3KFYPTLNYN/bundle.json","state":"https://pith.science/pith/D6U2JGA74PVODC7R3KFYPTLNYN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/D6U2JGA74PVODC7R3KFYPTLNYN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:D6U2JGA74PVODC7R3KFYPTLNYN","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":"3ac5c5ec459033acc51209c595d6bfe23e475803119c1c2e58bf062d8c6f875e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-19T22:53:27Z","title_canon_sha256":"94996b77bbb81249d1c2320cc573af3ba5b1c41d1f474e03affe29bc534fc9a3"},"schema_version":"1.0","source":{"id":"2410.15234","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.15234","created_at":"2026-07-05T11:07:15Z"},{"alias_kind":"arxiv_version","alias_value":"2410.15234v3","created_at":"2026-07-05T11:07:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.15234","created_at":"2026-07-05T11:07:15Z"},{"alias_kind":"pith_short_12","alias_value":"D6U2JGA74PVO","created_at":"2026-07-05T11:07:15Z"},{"alias_kind":"pith_short_16","alias_value":"D6U2JGA74PVODC7R","created_at":"2026-07-05T11:07:15Z"},{"alias_kind":"pith_short_8","alias_value":"D6U2JGA7","created_at":"2026-07-05T11:07:15Z"}],"graph_snapshots":[{"event_id":"sha256:20b4dd85c76d3a12e7af3381a8db5fbb658f5c0e228df7da191d6ffbc95f6d94","target":"graph","created_at":"2026-07-05T11:07:15Z","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/2410.15234/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Model collapse, a phenomenon characterized by performance degradation due to iterative training on synthetic data, has been widely studied. However, its implications for bias amplification, the progressive intensification of pre-existing societal biases in Large Language Models (LLMs), remain significantly underexplored, despite the growing influence of LLMs in shaping online discourse. In this paper, we introduce a open, generational, and long-context benchmark specifically designed to measure political bias amplification in LLMs, leveraging sentence continuation tasks derived from a comprehe","authors_text":"Adriano Koshiyama, Jeremy Zhang, Navya Jain, Saloni Gupta, Skylar Lu, Xin Guan, Zekun Wu, Ze Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-19T22:53:27Z","title":"Bias Amplification: Large Language Models as Increasingly Biased Media"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.15234","kind":"arxiv","version":3},"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:cd0d8645a103437cf17493f9a87157fc25d56fb0b9a10f828a7ec00ab9d1ca74","target":"record","created_at":"2026-07-05T11:07:15Z","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":"3ac5c5ec459033acc51209c595d6bfe23e475803119c1c2e58bf062d8c6f875e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-19T22:53:27Z","title_canon_sha256":"94996b77bbb81249d1c2320cc573af3ba5b1c41d1f474e03affe29bc534fc9a3"},"schema_version":"1.0","source":{"id":"2410.15234","kind":"arxiv","version":3}},"canonical_sha256":"1fa9a4981fe3eae18bf1da8b87cd6dc3797cb0d93c3c96058a7ea0907fe14777","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1fa9a4981fe3eae18bf1da8b87cd6dc3797cb0d93c3c96058a7ea0907fe14777","first_computed_at":"2026-07-05T11:07:15.778234Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:07:15.778234Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"P/0UN8ZNQMKMABcpsOYBMYqwdUNLOK+jy2v5DIqEuLOus/QFLokGN10J9q9k9ja5DRBtlarX/+sXGDuiVJU8Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:07:15.778735Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.15234","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cd0d8645a103437cf17493f9a87157fc25d56fb0b9a10f828a7ec00ab9d1ca74","sha256:20b4dd85c76d3a12e7af3381a8db5fbb658f5c0e228df7da191d6ffbc95f6d94"],"state_sha256":"db521ccd91f677a82d01aabbcb06c974347d5d161daa241e3469cba461397c98"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JpKrYxAbkN4t+oL2hOHftGmWOJkMW8OMNdJXSm3RhzVcPoNgdBZ7UVoSAVvorFw8Mkqt2ILExB6/tc0aQ/fIBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T18:34:45.032808Z","bundle_sha256":"479a065fdf13cafeb77b8ae951a6a9e9d82ad0740e8e60a20edb5231c205ed3d"}}