{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:TRK2AYCJLSTUCT3DORFXMO5NCT","short_pith_number":"pith:TRK2AYCJ","canonical_record":{"source":{"id":"2506.21898","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2025-06-27T04:35:52Z","cross_cats_sorted":[],"title_canon_sha256":"c4c82d79ef3f8c370bddcbcc1bf0be8a29aee39d6e4ec071fc3b10b704488ba1","abstract_canon_sha256":"48ddf36a2937567be8e318f9eda3920abde270daff10f5065e38ab7f237103dc"},"schema_version":"1.0"},"canonical_sha256":"9c55a060495ca7414f63744b763bad14dfd3501c01174d0132f3e2ea332d4d9b","source":{"kind":"arxiv","id":"2506.21898","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.21898","created_at":"2026-07-05T11:33:52Z"},{"alias_kind":"arxiv_version","alias_value":"2506.21898v2","created_at":"2026-07-05T11:33:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.21898","created_at":"2026-07-05T11:33:52Z"},{"alias_kind":"pith_short_12","alias_value":"TRK2AYCJLSTU","created_at":"2026-07-05T11:33:52Z"},{"alias_kind":"pith_short_16","alias_value":"TRK2AYCJLSTUCT3D","created_at":"2026-07-05T11:33:52Z"},{"alias_kind":"pith_short_8","alias_value":"TRK2AYCJ","created_at":"2026-07-05T11:33:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:TRK2AYCJLSTUCT3DORFXMO5NCT","target":"record","payload":{"canonical_record":{"source":{"id":"2506.21898","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2025-06-27T04:35:52Z","cross_cats_sorted":[],"title_canon_sha256":"c4c82d79ef3f8c370bddcbcc1bf0be8a29aee39d6e4ec071fc3b10b704488ba1","abstract_canon_sha256":"48ddf36a2937567be8e318f9eda3920abde270daff10f5065e38ab7f237103dc"},"schema_version":"1.0"},"canonical_sha256":"9c55a060495ca7414f63744b763bad14dfd3501c01174d0132f3e2ea332d4d9b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:33:52.589814Z","signature_b64":"RW3r6FlKc+X5ttFxhKN3XTPuL1W0dbx35zzkHUqgKcEF19ANJgtjO0ZSxvZ8oTnEk7LmSqM2zF0gAE+/NOzIAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9c55a060495ca7414f63744b763bad14dfd3501c01174d0132f3e2ea332d4d9b","last_reissued_at":"2026-07-05T11:33:52.589371Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:33:52.589371Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.21898","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":"2026-07-05T11:33:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/BeBGBoQeca8kJWPbr3t5/WeM1C8qi6eZaViCXX+G6glTDLtxyALetnaOm5Hd/H5JkVDsKgH/4oHWXsAm9kCCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T11:33:48.286925Z"},"content_sha256":"f371ad3caeafd7b60c34480f013f8a2988a7863780d20196bd3e96e159b6d611","schema_version":"1.0","event_id":"sha256:f371ad3caeafd7b60c34480f013f8a2988a7863780d20196bd3e96e159b6d611"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:TRK2AYCJLSTUCT3DORFXMO5NCT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bias, Accuracy, and Trust: Gender-Diverse Perspectives on Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Aimen Gaba, Cindy Xiong Bearfield, Emily Wall, Kyle Hall, Tejas Ramkumar Babu, Yuriy Brun","submitted_at":"2025-06-27T04:35:52Z","abstract_excerpt":"Large language models (LLMs) are becoming increasingly ubiquitous in our daily lives, but numerous concerns about bias in LLMs exist. This study examines how gender-diverse populations perceive bias, accuracy, and trustworthiness in LLMs, specifically ChatGPT. Through 25 in-depth interviews with non-binary/transgender, male, and female participants, we investigate how gendered and neutral prompts influence model responses and how users evaluate these responses. Our findings reveal that gendered prompts elicit more identity-specific responses, with non-binary participants particularly susceptib"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.21898","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/2506.21898/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":"2026-07-05T11:33:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xLoWZ+/lqm+uAW40sHsLAFI+rybMDjRMhNhJluXYmvv9qJqTV795IinZyhN5d7mfp3W3Xz9+81hFWxMVnQK4AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T11:33:48.287793Z"},"content_sha256":"b9815fa8be3b9052437c6c0eeb2eb231b5c273d85cdaa932acf338e47ec91316","schema_version":"1.0","event_id":"sha256:b9815fa8be3b9052437c6c0eeb2eb231b5c273d85cdaa932acf338e47ec91316"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TRK2AYCJLSTUCT3DORFXMO5NCT/bundle.json","state_url":"https://pith.science/pith/TRK2AYCJLSTUCT3DORFXMO5NCT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TRK2AYCJLSTUCT3DORFXMO5NCT/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":"2026-08-05T11:33:48Z","links":{"resolver":"https://pith.science/pith/TRK2AYCJLSTUCT3DORFXMO5NCT","bundle":"https://pith.science/pith/TRK2AYCJLSTUCT3DORFXMO5NCT/bundle.json","state":"https://pith.science/pith/TRK2AYCJLSTUCT3DORFXMO5NCT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TRK2AYCJLSTUCT3DORFXMO5NCT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:TRK2AYCJLSTUCT3DORFXMO5NCT","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":"48ddf36a2937567be8e318f9eda3920abde270daff10f5065e38ab7f237103dc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2025-06-27T04:35:52Z","title_canon_sha256":"c4c82d79ef3f8c370bddcbcc1bf0be8a29aee39d6e4ec071fc3b10b704488ba1"},"schema_version":"1.0","source":{"id":"2506.21898","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.21898","created_at":"2026-07-05T11:33:52Z"},{"alias_kind":"arxiv_version","alias_value":"2506.21898v2","created_at":"2026-07-05T11:33:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.21898","created_at":"2026-07-05T11:33:52Z"},{"alias_kind":"pith_short_12","alias_value":"TRK2AYCJLSTU","created_at":"2026-07-05T11:33:52Z"},{"alias_kind":"pith_short_16","alias_value":"TRK2AYCJLSTUCT3D","created_at":"2026-07-05T11:33:52Z"},{"alias_kind":"pith_short_8","alias_value":"TRK2AYCJ","created_at":"2026-07-05T11:33:52Z"}],"graph_snapshots":[{"event_id":"sha256:b9815fa8be3b9052437c6c0eeb2eb231b5c273d85cdaa932acf338e47ec91316","target":"graph","created_at":"2026-07-05T11:33:52Z","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/2506.21898/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) are becoming increasingly ubiquitous in our daily lives, but numerous concerns about bias in LLMs exist. This study examines how gender-diverse populations perceive bias, accuracy, and trustworthiness in LLMs, specifically ChatGPT. Through 25 in-depth interviews with non-binary/transgender, male, and female participants, we investigate how gendered and neutral prompts influence model responses and how users evaluate these responses. Our findings reveal that gendered prompts elicit more identity-specific responses, with non-binary participants particularly susceptib","authors_text":"Aimen Gaba, Cindy Xiong Bearfield, Emily Wall, Kyle Hall, Tejas Ramkumar Babu, Yuriy Brun","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2025-06-27T04:35:52Z","title":"Bias, Accuracy, and Trust: Gender-Diverse Perspectives on Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.21898","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:f371ad3caeafd7b60c34480f013f8a2988a7863780d20196bd3e96e159b6d611","target":"record","created_at":"2026-07-05T11:33:52Z","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":"48ddf36a2937567be8e318f9eda3920abde270daff10f5065e38ab7f237103dc","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.HC","submitted_at":"2025-06-27T04:35:52Z","title_canon_sha256":"c4c82d79ef3f8c370bddcbcc1bf0be8a29aee39d6e4ec071fc3b10b704488ba1"},"schema_version":"1.0","source":{"id":"2506.21898","kind":"arxiv","version":2}},"canonical_sha256":"9c55a060495ca7414f63744b763bad14dfd3501c01174d0132f3e2ea332d4d9b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9c55a060495ca7414f63744b763bad14dfd3501c01174d0132f3e2ea332d4d9b","first_computed_at":"2026-07-05T11:33:52.589371Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:33:52.589371Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RW3r6FlKc+X5ttFxhKN3XTPuL1W0dbx35zzkHUqgKcEF19ANJgtjO0ZSxvZ8oTnEk7LmSqM2zF0gAE+/NOzIAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:33:52.589814Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.21898","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f371ad3caeafd7b60c34480f013f8a2988a7863780d20196bd3e96e159b6d611","sha256:b9815fa8be3b9052437c6c0eeb2eb231b5c273d85cdaa932acf338e47ec91316"],"state_sha256":"fc907e95afe663be8b4e5ced29d59a91227170a9228f87950daeb3f6cd00a471"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n/ovBfvLH5MFwIHBl/kB1jf70NRT44RiEYitmobBFil+sZUwXVCtpgvkTH/p7MOCQDM4Gu9D6yd8TtWqA/QpCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T11:33:48.294477Z","bundle_sha256":"d1b25515a5983015602db45d0b94344ade213cf6f8f17ccf91e48d0540d8b645"}}