{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:H44ZHFLCG2D3AFGWLWTHOOMKHB","short_pith_number":"pith:H44ZHFLC","canonical_record":{"source":{"id":"2407.06957","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.AS","submitted_at":"2024-07-09T15:35:43Z","cross_cats_sorted":["cs.CL","cs.CY"],"title_canon_sha256":"ce9f67944308c424bd53dad466d3c71b6a02a551cc0ae31aff4f51477c70445e","abstract_canon_sha256":"87bfdbab470b566f6e0a44ca0a2c72be6ea154a3640069539d9c9f3f7d7e1222"},"schema_version":"1.0"},"canonical_sha256":"3f399395623687b014d65da677398a384497efd46ac8115c74f598219beb5fc8","source":{"kind":"arxiv","id":"2407.06957","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.06957","created_at":"2026-07-05T11:06:54Z"},{"alias_kind":"arxiv_version","alias_value":"2407.06957v1","created_at":"2026-07-05T11:06:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.06957","created_at":"2026-07-05T11:06:54Z"},{"alias_kind":"pith_short_12","alias_value":"H44ZHFLCG2D3","created_at":"2026-07-05T11:06:54Z"},{"alias_kind":"pith_short_16","alias_value":"H44ZHFLCG2D3AFGW","created_at":"2026-07-05T11:06:54Z"},{"alias_kind":"pith_short_8","alias_value":"H44ZHFLC","created_at":"2026-07-05T11:06:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:H44ZHFLCG2D3AFGWLWTHOOMKHB","target":"record","payload":{"canonical_record":{"source":{"id":"2407.06957","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.AS","submitted_at":"2024-07-09T15:35:43Z","cross_cats_sorted":["cs.CL","cs.CY"],"title_canon_sha256":"ce9f67944308c424bd53dad466d3c71b6a02a551cc0ae31aff4f51477c70445e","abstract_canon_sha256":"87bfdbab470b566f6e0a44ca0a2c72be6ea154a3640069539d9c9f3f7d7e1222"},"schema_version":"1.0"},"canonical_sha256":"3f399395623687b014d65da677398a384497efd46ac8115c74f598219beb5fc8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:06:54.172734Z","signature_b64":"qRiPhMwChgrikaeAcw+PgHkkkQSUkwV0mx1PITFvprBBN4h/mk9hD5mVrA6yV/VoooFxZZUcfytiGeiRI0bYDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3f399395623687b014d65da677398a384497efd46ac8115c74f598219beb5fc8","last_reissued_at":"2026-07-05T11:06:54.172211Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:06:54.172211Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.06957","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":"2026-07-05T11:06:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LgLyUTLHDxBu2YgTHYzk0+UVyh+3Zs9YgFXAfPMKJPw6RfX0T2WT7c9Gay/MKnbq+J2Ifx10pfMregnS9CXsBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T04:05:51.094930Z"},"content_sha256":"f5396fe4f53ce4fdccc02234aecb45a91d0d26a2e9c3d6e8ab70e188ab9621dd","schema_version":"1.0","event_id":"sha256:f5396fe4f53ce4fdccc02234aecb45a91d0d26a2e9c3d6e8ab70e188ab9621dd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:H44ZHFLCG2D3AFGWLWTHOOMKHB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Listen and Speak Fairly: A Study on Semantic Gender Bias in Speech Integrated Large Language Models","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.CL","cs.CY"],"primary_cat":"eess.AS","authors_text":"Chih-Kai Yang, Chun-Yi Kuan, Hung-yi Lee, Ke-Han Lu, Tzu-Quan Lin, Wei-Chih Chen, Yi-Cheng Lin","submitted_at":"2024-07-09T15:35:43Z","abstract_excerpt":"Speech Integrated Large Language Models (SILLMs) combine large language models with speech perception to perform diverse tasks, such as emotion recognition to speaker verification, demonstrating universal audio understanding capability. However, these models may amplify biases present in training data, potentially leading to biased access to information for marginalized groups. This work introduces a curated spoken bias evaluation toolkit and corresponding dataset. We evaluate gender bias in SILLMs across four semantic-related tasks: speech-to-text translation (STT), spoken coreference resolut"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.06957","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/2407.06957/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":"2026-07-05T11:06:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"L9DqR1YEiwc6CgJMcRRlxaOCseRpjSt43HJZzET8/G2GQ4IX5WYUU0jO8UbH82sX+QFz+ja2hrfExNrb/qrZBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T04:05:51.095577Z"},"content_sha256":"64966f13d54d0a67d5abdbd79be073703fa12074e468b60dde49b09a45a6eaca","schema_version":"1.0","event_id":"sha256:64966f13d54d0a67d5abdbd79be073703fa12074e468b60dde49b09a45a6eaca"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/H44ZHFLCG2D3AFGWLWTHOOMKHB/bundle.json","state_url":"https://pith.science/pith/H44ZHFLCG2D3AFGWLWTHOOMKHB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/H44ZHFLCG2D3AFGWLWTHOOMKHB/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":"2026-08-04T04:05:51Z","links":{"resolver":"https://pith.science/pith/H44ZHFLCG2D3AFGWLWTHOOMKHB","bundle":"https://pith.science/pith/H44ZHFLCG2D3AFGWLWTHOOMKHB/bundle.json","state":"https://pith.science/pith/H44ZHFLCG2D3AFGWLWTHOOMKHB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/H44ZHFLCG2D3AFGWLWTHOOMKHB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:H44ZHFLCG2D3AFGWLWTHOOMKHB","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":"87bfdbab470b566f6e0a44ca0a2c72be6ea154a3640069539d9c9f3f7d7e1222","cross_cats_sorted":["cs.CL","cs.CY"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.AS","submitted_at":"2024-07-09T15:35:43Z","title_canon_sha256":"ce9f67944308c424bd53dad466d3c71b6a02a551cc0ae31aff4f51477c70445e"},"schema_version":"1.0","source":{"id":"2407.06957","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.06957","created_at":"2026-07-05T11:06:54Z"},{"alias_kind":"arxiv_version","alias_value":"2407.06957v1","created_at":"2026-07-05T11:06:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.06957","created_at":"2026-07-05T11:06:54Z"},{"alias_kind":"pith_short_12","alias_value":"H44ZHFLCG2D3","created_at":"2026-07-05T11:06:54Z"},{"alias_kind":"pith_short_16","alias_value":"H44ZHFLCG2D3AFGW","created_at":"2026-07-05T11:06:54Z"},{"alias_kind":"pith_short_8","alias_value":"H44ZHFLC","created_at":"2026-07-05T11:06:54Z"}],"graph_snapshots":[{"event_id":"sha256:64966f13d54d0a67d5abdbd79be073703fa12074e468b60dde49b09a45a6eaca","target":"graph","created_at":"2026-07-05T11:06:54Z","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/2407.06957/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Speech Integrated Large Language Models (SILLMs) combine large language models with speech perception to perform diverse tasks, such as emotion recognition to speaker verification, demonstrating universal audio understanding capability. However, these models may amplify biases present in training data, potentially leading to biased access to information for marginalized groups. This work introduces a curated spoken bias evaluation toolkit and corresponding dataset. We evaluate gender bias in SILLMs across four semantic-related tasks: speech-to-text translation (STT), spoken coreference resolut","authors_text":"Chih-Kai Yang, Chun-Yi Kuan, Hung-yi Lee, Ke-Han Lu, Tzu-Quan Lin, Wei-Chih Chen, Yi-Cheng Lin","cross_cats":["cs.CL","cs.CY"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.AS","submitted_at":"2024-07-09T15:35:43Z","title":"Listen and Speak Fairly: A Study on Semantic Gender Bias in Speech Integrated Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.06957","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:f5396fe4f53ce4fdccc02234aecb45a91d0d26a2e9c3d6e8ab70e188ab9621dd","target":"record","created_at":"2026-07-05T11:06:54Z","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":"87bfdbab470b566f6e0a44ca0a2c72be6ea154a3640069539d9c9f3f7d7e1222","cross_cats_sorted":["cs.CL","cs.CY"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"eess.AS","submitted_at":"2024-07-09T15:35:43Z","title_canon_sha256":"ce9f67944308c424bd53dad466d3c71b6a02a551cc0ae31aff4f51477c70445e"},"schema_version":"1.0","source":{"id":"2407.06957","kind":"arxiv","version":1}},"canonical_sha256":"3f399395623687b014d65da677398a384497efd46ac8115c74f598219beb5fc8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3f399395623687b014d65da677398a384497efd46ac8115c74f598219beb5fc8","first_computed_at":"2026-07-05T11:06:54.172211Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:06:54.172211Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qRiPhMwChgrikaeAcw+PgHkkkQSUkwV0mx1PITFvprBBN4h/mk9hD5mVrA6yV/VoooFxZZUcfytiGeiRI0bYDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:06:54.172734Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.06957","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f5396fe4f53ce4fdccc02234aecb45a91d0d26a2e9c3d6e8ab70e188ab9621dd","sha256:64966f13d54d0a67d5abdbd79be073703fa12074e468b60dde49b09a45a6eaca"],"state_sha256":"34af3119670173ef569db4ed4c5cb65accc6140dc4bd4347ff9c1e9a82e8a959"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/wpzneekRKyrfKBkjyUOO6E9da4UGDthDAd8XMTPHW4eEan/61Cm/F4VuqNw/rEGbD6EO0QummfD6xwl9xaaBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T04:05:51.107054Z","bundle_sha256":"428b44684ce921ace0a6d5b7418c5fa14fb97eb3c7b46ff3f56fb75bd2a21316"}}