{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OM3Q2XVQRGWXALREYDI77VHYS6","short_pith_number":"pith:OM3Q2XVQ","canonical_record":{"source":{"id":"2403.13840","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-15T04:02:24Z","cross_cats_sorted":["cs.AI","cs.SI"],"title_canon_sha256":"b5d340fb0361ae8f87e44e351a26cf8d4efc6a2e712f33a500a2116879041420","abstract_canon_sha256":"9b415ce5d74115fbf2d71ebb99bc84596da37e19f27053cb6b12f78a5b3caecc"},"schema_version":"1.0"},"canonical_sha256":"73370d5eb089ad702e24c0d1ffd4f897977bcc347c1ab70c3e96adc8d518c172","source":{"kind":"arxiv","id":"2403.13840","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.13840","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"arxiv_version","alias_value":"2403.13840v1","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.13840","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"pith_short_12","alias_value":"OM3Q2XVQRGWX","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"pith_short_16","alias_value":"OM3Q2XVQRGWXALRE","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"pith_short_8","alias_value":"OM3Q2XVQ","created_at":"2026-07-05T07:58:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OM3Q2XVQRGWXALREYDI77VHYS6","target":"record","payload":{"canonical_record":{"source":{"id":"2403.13840","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-15T04:02:24Z","cross_cats_sorted":["cs.AI","cs.SI"],"title_canon_sha256":"b5d340fb0361ae8f87e44e351a26cf8d4efc6a2e712f33a500a2116879041420","abstract_canon_sha256":"9b415ce5d74115fbf2d71ebb99bc84596da37e19f27053cb6b12f78a5b3caecc"},"schema_version":"1.0"},"canonical_sha256":"73370d5eb089ad702e24c0d1ffd4f897977bcc347c1ab70c3e96adc8d518c172","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:58:50.865255Z","signature_b64":"W7NnM0rtv+yWZRG8oLIc+FOt5+YQf9YpOxhmXyG8RkR2hDpvPcKEaJLKWpYQ/CRe6qAgTd801fIe+A/rqi0mCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"73370d5eb089ad702e24c0d1ffd4f897977bcc347c1ab70c3e96adc8d518c172","last_reissued_at":"2026-07-05T07:58:50.864753Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:58:50.864753Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.13840","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:58:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0TiUL0ORNlkHttMdofupLW2zCK537NumXF6xtt0zuqJaYpMSgVroBqHgiMglJTWnf2Zgq/TpjF0aANgeMLi7Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T01:11:19.935265Z"},"content_sha256":"70c3480b5169c840f2ff5bae2865c09caa8fe0f389238ba2b726ac5ad0b68923","schema_version":"1.0","event_id":"sha256:70c3480b5169c840f2ff5bae2865c09caa8fe0f389238ba2b726ac5ad0b68923"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OM3Q2XVQRGWXALREYDI77VHYS6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Whose Side Are You On? Investigating the Political Stance of Large Language Models","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.SI"],"primary_cat":"cs.CL","authors_text":"Henry Pit, James Bailey, Mike Conway, Pagnarasmey Pit, Putrasmey Keo, Qingyu Chen, Watey Diep, Xingjun Ma, Yu-Gang Jiang","submitted_at":"2024-03-15T04:02:24Z","abstract_excerpt":"Large Language Models (LLMs) have gained significant popularity for their application in various everyday tasks such as text generation, summarization, and information retrieval. As the widespread adoption of LLMs continues to surge, it becomes increasingly crucial to ensure that these models yield responses that are politically impartial, with the aim of preventing information bubbles, upholding fairness in representation, and mitigating confirmation bias. In this paper, we propose a quantitative framework and pipeline designed to systematically investigate the political orientation of LLMs. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.13840","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/2403.13840/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":"2026-07-05T07:58:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nu7PREJQvb/GY1IDnKfsoNn6cq+/ANhMG0Cm4jBUqttNNIarR1Eexva1LulX+4YTrI/vOnaZ8MoG6n6OaHCrBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T01:11:19.935838Z"},"content_sha256":"a0077ce088f239a98a866b42670c17e0a66bb8a9e585f2cd487c157ea0f9bc8c","schema_version":"1.0","event_id":"sha256:a0077ce088f239a98a866b42670c17e0a66bb8a9e585f2cd487c157ea0f9bc8c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OM3Q2XVQRGWXALREYDI77VHYS6/bundle.json","state_url":"https://pith.science/pith/OM3Q2XVQRGWXALREYDI77VHYS6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OM3Q2XVQRGWXALREYDI77VHYS6/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":"2026-08-09T01:11:19Z","links":{"resolver":"https://pith.science/pith/OM3Q2XVQRGWXALREYDI77VHYS6","bundle":"https://pith.science/pith/OM3Q2XVQRGWXALREYDI77VHYS6/bundle.json","state":"https://pith.science/pith/OM3Q2XVQRGWXALREYDI77VHYS6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OM3Q2XVQRGWXALREYDI77VHYS6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OM3Q2XVQRGWXALREYDI77VHYS6","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":"9b415ce5d74115fbf2d71ebb99bc84596da37e19f27053cb6b12f78a5b3caecc","cross_cats_sorted":["cs.AI","cs.SI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-15T04:02:24Z","title_canon_sha256":"b5d340fb0361ae8f87e44e351a26cf8d4efc6a2e712f33a500a2116879041420"},"schema_version":"1.0","source":{"id":"2403.13840","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.13840","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"arxiv_version","alias_value":"2403.13840v1","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.13840","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"pith_short_12","alias_value":"OM3Q2XVQRGWX","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"pith_short_16","alias_value":"OM3Q2XVQRGWXALRE","created_at":"2026-07-05T07:58:50Z"},{"alias_kind":"pith_short_8","alias_value":"OM3Q2XVQ","created_at":"2026-07-05T07:58:50Z"}],"graph_snapshots":[{"event_id":"sha256:a0077ce088f239a98a866b42670c17e0a66bb8a9e585f2cd487c157ea0f9bc8c","target":"graph","created_at":"2026-07-05T07:58:50Z","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/2403.13840/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have gained significant popularity for their application in various everyday tasks such as text generation, summarization, and information retrieval. As the widespread adoption of LLMs continues to surge, it becomes increasingly crucial to ensure that these models yield responses that are politically impartial, with the aim of preventing information bubbles, upholding fairness in representation, and mitigating confirmation bias. In this paper, we propose a quantitative framework and pipeline designed to systematically investigate the political orientation of LLMs. ","authors_text":"Henry Pit, James Bailey, Mike Conway, Pagnarasmey Pit, Putrasmey Keo, Qingyu Chen, Watey Diep, Xingjun Ma, Yu-Gang Jiang","cross_cats":["cs.AI","cs.SI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-15T04:02:24Z","title":"Whose Side Are You On? Investigating the Political Stance of Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.13840","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":"sha256:70c3480b5169c840f2ff5bae2865c09caa8fe0f389238ba2b726ac5ad0b68923","target":"record","created_at":"2026-07-05T07:58:50Z","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":"9b415ce5d74115fbf2d71ebb99bc84596da37e19f27053cb6b12f78a5b3caecc","cross_cats_sorted":["cs.AI","cs.SI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-15T04:02:24Z","title_canon_sha256":"b5d340fb0361ae8f87e44e351a26cf8d4efc6a2e712f33a500a2116879041420"},"schema_version":"1.0","source":{"id":"2403.13840","kind":"arxiv","version":1}},"canonical_sha256":"73370d5eb089ad702e24c0d1ffd4f897977bcc347c1ab70c3e96adc8d518c172","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"73370d5eb089ad702e24c0d1ffd4f897977bcc347c1ab70c3e96adc8d518c172","first_computed_at":"2026-07-05T07:58:50.864753Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:58:50.864753Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"W7NnM0rtv+yWZRG8oLIc+FOt5+YQf9YpOxhmXyG8RkR2hDpvPcKEaJLKWpYQ/CRe6qAgTd801fIe+A/rqi0mCw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:58:50.865255Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.13840","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:70c3480b5169c840f2ff5bae2865c09caa8fe0f389238ba2b726ac5ad0b68923","sha256:a0077ce088f239a98a866b42670c17e0a66bb8a9e585f2cd487c157ea0f9bc8c"],"state_sha256":"329a3f7dab9eb30b42a67abd65f7b96d8fa23327417ddb125498f275eb543190"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yw/DMMlWbECsGWjhDlvbOB2TYcxd2jwKtC3Tpw94hCpoSLPWxp045aV+1WWy3u6g/A74SCm02hVSXf6D+pMtAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T01:11:19.940781Z","bundle_sha256":"cb913a528e340690dba28da89a806523a75dd6c8267f4122e1fe6070220595a4"}}