{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:4ULKVTBSD5FZPWHHS2PI3HGJLL","short_pith_number":"pith:4ULKVTBS","canonical_record":{"source":{"id":"2305.11000","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-05-18T14:23:25Z","cross_cats_sorted":[],"title_canon_sha256":"e72cb6e1dedcbe796f99c1cf12c1199865b6c0a29de6162303dd7273b5d44fba","abstract_canon_sha256":"6164e2c792484793ace88d3435b9552649525d230c850dc5da73623ecd436cb3"},"schema_version":"1.0"},"canonical_sha256":"e516aacc321f4b97d8e7969e8d9cc95acd3a46bb31e65a6f332a91d8498892d2","source":{"kind":"arxiv","id":"2305.11000","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.11000","created_at":"2026-07-05T06:11:46Z"},{"alias_kind":"arxiv_version","alias_value":"2305.11000v2","created_at":"2026-07-05T06:11:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.11000","created_at":"2026-07-05T06:11:46Z"},{"alias_kind":"pith_short_12","alias_value":"4ULKVTBSD5FZ","created_at":"2026-07-05T06:11:46Z"},{"alias_kind":"pith_short_16","alias_value":"4ULKVTBSD5FZPWHH","created_at":"2026-07-05T06:11:46Z"},{"alias_kind":"pith_short_8","alias_value":"4ULKVTBS","created_at":"2026-07-05T06:11:46Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:4ULKVTBSD5FZPWHHS2PI3HGJLL","target":"record","payload":{"canonical_record":{"source":{"id":"2305.11000","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-05-18T14:23:25Z","cross_cats_sorted":[],"title_canon_sha256":"e72cb6e1dedcbe796f99c1cf12c1199865b6c0a29de6162303dd7273b5d44fba","abstract_canon_sha256":"6164e2c792484793ace88d3435b9552649525d230c850dc5da73623ecd436cb3"},"schema_version":"1.0"},"canonical_sha256":"e516aacc321f4b97d8e7969e8d9cc95acd3a46bb31e65a6f332a91d8498892d2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:11:46.417189Z","signature_b64":"Yul18DKrHukgpCc1J8a1mC2Ua8jd9RbyDk8cVOMpUBBDi8rguHRqtKmyAhmfzHaO20PMz66Z+G0gXpH4EhM/Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e516aacc321f4b97d8e7969e8d9cc95acd3a46bb31e65a6f332a91d8498892d2","last_reissued_at":"2026-07-05T06:11:46.416771Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:11:46.416771Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.11000","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":"2026-07-05T06:11:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZtqO5zMs4CC0ZIB9YUGM/u/TUPQCBeZPRzovX4cvrCM28/PSGXAYOwTcbxVcpUVyG7YD+52N+f+2CYuGytLVAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T15:23:33.739181Z"},"content_sha256":"ac59ad85ab1c3dbc215c9099212ccfa9fd33b7cdc216fa403a7104b530d07ebb","schema_version":"1.0","event_id":"sha256:ac59ad85ab1c3dbc215c9099212ccfa9fd33b7cdc216fa403a7104b530d07ebb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:4ULKVTBSD5FZPWHHS2PI3HGJLL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dong Zhang, Jun Zhan, Pengyu Wang, Shimin Li, Xin Zhang, Xipeng Qiu, Yaqian Zhou","submitted_at":"2023-05-18T14:23:25Z","abstract_excerpt":"Multi-modal large language models are regarded as a crucial step towards Artificial General Intelligence (AGI) and have garnered significant interest with the emergence of ChatGPT. However, current speech-language models typically adopt the cascade paradigm, preventing inter-modal knowledge transfer. In this paper, we propose SpeechGPT, a large language model with intrinsic cross-modal conversational abilities, capable of perceiving and generating multi-model content. With discrete speech representations, we first construct SpeechInstruct, a large-scale cross-modal speech instruction dataset. "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.11000","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/2305.11000/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":"2026-07-05T06:11:46Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Z5h9xMse/omWRhTGyF3ooT5mDdAZsjRSvnMmpTJ7Wk1gPphZWNo0TV6H/khQHMGjUzcQBmJuxlYQeRHbF72YBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T15:23:33.739610Z"},"content_sha256":"a8ff6631b3a0dd2efffe037a0c338dc0632cb77c3a702baad27d993e7c3b8554","schema_version":"1.0","event_id":"sha256:a8ff6631b3a0dd2efffe037a0c338dc0632cb77c3a702baad27d993e7c3b8554"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4ULKVTBSD5FZPWHHS2PI3HGJLL/bundle.json","state_url":"https://pith.science/pith/4ULKVTBSD5FZPWHHS2PI3HGJLL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4ULKVTBSD5FZPWHHS2PI3HGJLL/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":"2026-07-06T15:23:33Z","links":{"resolver":"https://pith.science/pith/4ULKVTBSD5FZPWHHS2PI3HGJLL","bundle":"https://pith.science/pith/4ULKVTBSD5FZPWHHS2PI3HGJLL/bundle.json","state":"https://pith.science/pith/4ULKVTBSD5FZPWHHS2PI3HGJLL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4ULKVTBSD5FZPWHHS2PI3HGJLL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:4ULKVTBSD5FZPWHHS2PI3HGJLL","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":"6164e2c792484793ace88d3435b9552649525d230c850dc5da73623ecd436cb3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-05-18T14:23:25Z","title_canon_sha256":"e72cb6e1dedcbe796f99c1cf12c1199865b6c0a29de6162303dd7273b5d44fba"},"schema_version":"1.0","source":{"id":"2305.11000","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.11000","created_at":"2026-07-05T06:11:46Z"},{"alias_kind":"arxiv_version","alias_value":"2305.11000v2","created_at":"2026-07-05T06:11:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.11000","created_at":"2026-07-05T06:11:46Z"},{"alias_kind":"pith_short_12","alias_value":"4ULKVTBSD5FZ","created_at":"2026-07-05T06:11:46Z"},{"alias_kind":"pith_short_16","alias_value":"4ULKVTBSD5FZPWHH","created_at":"2026-07-05T06:11:46Z"},{"alias_kind":"pith_short_8","alias_value":"4ULKVTBS","created_at":"2026-07-05T06:11:46Z"}],"graph_snapshots":[{"event_id":"sha256:a8ff6631b3a0dd2efffe037a0c338dc0632cb77c3a702baad27d993e7c3b8554","target":"graph","created_at":"2026-07-05T06:11:46Z","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/2305.11000/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-modal large language models are regarded as a crucial step towards Artificial General Intelligence (AGI) and have garnered significant interest with the emergence of ChatGPT. However, current speech-language models typically adopt the cascade paradigm, preventing inter-modal knowledge transfer. In this paper, we propose SpeechGPT, a large language model with intrinsic cross-modal conversational abilities, capable of perceiving and generating multi-model content. With discrete speech representations, we first construct SpeechInstruct, a large-scale cross-modal speech instruction dataset. ","authors_text":"Dong Zhang, Jun Zhan, Pengyu Wang, Shimin Li, Xin Zhang, Xipeng Qiu, Yaqian Zhou","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-05-18T14:23:25Z","title":"SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.11000","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:ac59ad85ab1c3dbc215c9099212ccfa9fd33b7cdc216fa403a7104b530d07ebb","target":"record","created_at":"2026-07-05T06:11:46Z","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":"6164e2c792484793ace88d3435b9552649525d230c850dc5da73623ecd436cb3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-05-18T14:23:25Z","title_canon_sha256":"e72cb6e1dedcbe796f99c1cf12c1199865b6c0a29de6162303dd7273b5d44fba"},"schema_version":"1.0","source":{"id":"2305.11000","kind":"arxiv","version":2}},"canonical_sha256":"e516aacc321f4b97d8e7969e8d9cc95acd3a46bb31e65a6f332a91d8498892d2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e516aacc321f4b97d8e7969e8d9cc95acd3a46bb31e65a6f332a91d8498892d2","first_computed_at":"2026-07-05T06:11:46.416771Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:11:46.416771Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Yul18DKrHukgpCc1J8a1mC2Ua8jd9RbyDk8cVOMpUBBDi8rguHRqtKmyAhmfzHaO20PMz66Z+G0gXpH4EhM/Bg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:11:46.417189Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.11000","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ac59ad85ab1c3dbc215c9099212ccfa9fd33b7cdc216fa403a7104b530d07ebb","sha256:a8ff6631b3a0dd2efffe037a0c338dc0632cb77c3a702baad27d993e7c3b8554"],"state_sha256":"f2cdd0dc6a02b251d06051d36a20be1be281932479f8b834b8fff952e86523c3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"02ykOu1rePmz03Ds58n+7QgVfkGmZ4bG7silozIDlZkgqpI+Ixw5Ho4VoM3kQeaQ4qvqs9LC4C/Xd2Y5cAkVCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T15:23:33.741670Z","bundle_sha256":"dc583e91a986f7b1b3e69e869220d60bd9b16bdc546e3fe7a7a5c226559cd964"}}