{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OCNZYXRI22BDBH3RHACEO3HFNM","short_pith_number":"pith:OCNZYXRI","canonical_record":{"source":{"id":"2410.20916","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-28T10:53:22Z","cross_cats_sorted":[],"title_canon_sha256":"cd0f696735fb82cdee1efc93512fbc31947f3050fb5389fab6bcc4974b2bd878","abstract_canon_sha256":"190c0b69cedeb1e16c0e385663518eb20f4fdf1c393649d02bce8ee274d8184d"},"schema_version":"1.0"},"canonical_sha256":"709b9c5e28d682309f713804476ce56b07d8c174d2a5d0e71b8a4a05e28d10cc","source":{"kind":"arxiv","id":"2410.20916","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.20916","created_at":"2026-07-05T09:27:13Z"},{"alias_kind":"arxiv_version","alias_value":"2410.20916v1","created_at":"2026-07-05T09:27:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.20916","created_at":"2026-07-05T09:27:13Z"},{"alias_kind":"pith_short_12","alias_value":"OCNZYXRI22BD","created_at":"2026-07-05T09:27:13Z"},{"alias_kind":"pith_short_16","alias_value":"OCNZYXRI22BDBH3R","created_at":"2026-07-05T09:27:13Z"},{"alias_kind":"pith_short_8","alias_value":"OCNZYXRI","created_at":"2026-07-05T09:27:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OCNZYXRI22BDBH3RHACEO3HFNM","target":"record","payload":{"canonical_record":{"source":{"id":"2410.20916","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-28T10:53:22Z","cross_cats_sorted":[],"title_canon_sha256":"cd0f696735fb82cdee1efc93512fbc31947f3050fb5389fab6bcc4974b2bd878","abstract_canon_sha256":"190c0b69cedeb1e16c0e385663518eb20f4fdf1c393649d02bce8ee274d8184d"},"schema_version":"1.0"},"canonical_sha256":"709b9c5e28d682309f713804476ce56b07d8c174d2a5d0e71b8a4a05e28d10cc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:27:13.111896Z","signature_b64":"hg2rnnSxNat+Sc07OnUmuYxYRDKIwnfpyrnb+MeifBZ9QVsgjtyXQSKtkSfb1te4oT1xCx1noROcEClreQE2AA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"709b9c5e28d682309f713804476ce56b07d8c174d2a5d0e71b8a4a05e28d10cc","last_reissued_at":"2026-07-05T09:27:13.111472Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:27:13.111472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.20916","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":"2026-07-05T09:27:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ye/kDOb6TprnxQm8l6ujuQi+b9NvGEq62n2bs3TF3mf+7JrEFHBVLlrurwFJ7apgwgCs6cEienFarS+TBC36Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T09:33:05.756044Z"},"content_sha256":"bc091915c7b9a659d654fe2d6336eec1ad16f5cad0a2315289249056f42f1ebc","schema_version":"1.0","event_id":"sha256:bc091915c7b9a659d654fe2d6336eec1ad16f5cad0a2315289249056f42f1ebc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OCNZYXRI22BDBH3RHACEO3HFNM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"NeuGPT: Unified multi-modal Neural GPT","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Chin-Teng Lin, Hui Xiong, Hyejeong Jo, Oiwi Parker Jones, Qiang Zhang, Renjing Xu, Xuming Hu, Yiqian Yang, Yiqun Duan","submitted_at":"2024-10-28T10:53:22Z","abstract_excerpt":"This paper introduces NeuGPT, a groundbreaking multi-modal language generation model designed to harmonize the fragmented landscape of neural recording research. Traditionally, studies in the field have been compartmentalized by signal type, with EEG, MEG, ECoG, SEEG, fMRI, and fNIRS data being analyzed in isolation. Recognizing the untapped potential for cross-pollination and the adaptability of neural signals across varying experimental conditions, we set out to develop a unified model capable of interfacing with multiple modalities. Drawing inspiration from the success of pre-trained large "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.20916","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/2410.20916/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":"2026-07-05T09:27:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9f3VFDXzMSKxZT5OJLCBbSzY2+LdFXKtQ7ZRxu78IEXHImfbWE+n2fBK/egrXOtjBkRdmXmNGEG8lL5nAgFzCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T09:33:05.756513Z"},"content_sha256":"20cfc6a69e584280ed5f3d28218b78225404f4c52ba6fb37c4a55712f8060ede","schema_version":"1.0","event_id":"sha256:20cfc6a69e584280ed5f3d28218b78225404f4c52ba6fb37c4a55712f8060ede"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OCNZYXRI22BDBH3RHACEO3HFNM/bundle.json","state_url":"https://pith.science/pith/OCNZYXRI22BDBH3RHACEO3HFNM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OCNZYXRI22BDBH3RHACEO3HFNM/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":"2026-08-06T09:33:05Z","links":{"resolver":"https://pith.science/pith/OCNZYXRI22BDBH3RHACEO3HFNM","bundle":"https://pith.science/pith/OCNZYXRI22BDBH3RHACEO3HFNM/bundle.json","state":"https://pith.science/pith/OCNZYXRI22BDBH3RHACEO3HFNM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OCNZYXRI22BDBH3RHACEO3HFNM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OCNZYXRI22BDBH3RHACEO3HFNM","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":"190c0b69cedeb1e16c0e385663518eb20f4fdf1c393649d02bce8ee274d8184d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-28T10:53:22Z","title_canon_sha256":"cd0f696735fb82cdee1efc93512fbc31947f3050fb5389fab6bcc4974b2bd878"},"schema_version":"1.0","source":{"id":"2410.20916","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.20916","created_at":"2026-07-05T09:27:13Z"},{"alias_kind":"arxiv_version","alias_value":"2410.20916v1","created_at":"2026-07-05T09:27:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.20916","created_at":"2026-07-05T09:27:13Z"},{"alias_kind":"pith_short_12","alias_value":"OCNZYXRI22BD","created_at":"2026-07-05T09:27:13Z"},{"alias_kind":"pith_short_16","alias_value":"OCNZYXRI22BDBH3R","created_at":"2026-07-05T09:27:13Z"},{"alias_kind":"pith_short_8","alias_value":"OCNZYXRI","created_at":"2026-07-05T09:27:13Z"}],"graph_snapshots":[{"event_id":"sha256:20cfc6a69e584280ed5f3d28218b78225404f4c52ba6fb37c4a55712f8060ede","target":"graph","created_at":"2026-07-05T09:27:13Z","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/2410.20916/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper introduces NeuGPT, a groundbreaking multi-modal language generation model designed to harmonize the fragmented landscape of neural recording research. Traditionally, studies in the field have been compartmentalized by signal type, with EEG, MEG, ECoG, SEEG, fMRI, and fNIRS data being analyzed in isolation. Recognizing the untapped potential for cross-pollination and the adaptability of neural signals across varying experimental conditions, we set out to develop a unified model capable of interfacing with multiple modalities. Drawing inspiration from the success of pre-trained large ","authors_text":"Chin-Teng Lin, Hui Xiong, Hyejeong Jo, Oiwi Parker Jones, Qiang Zhang, Renjing Xu, Xuming Hu, Yiqian Yang, Yiqun Duan","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-28T10:53:22Z","title":"NeuGPT: Unified multi-modal Neural GPT"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.20916","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:bc091915c7b9a659d654fe2d6336eec1ad16f5cad0a2315289249056f42f1ebc","target":"record","created_at":"2026-07-05T09:27:13Z","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":"190c0b69cedeb1e16c0e385663518eb20f4fdf1c393649d02bce8ee274d8184d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-28T10:53:22Z","title_canon_sha256":"cd0f696735fb82cdee1efc93512fbc31947f3050fb5389fab6bcc4974b2bd878"},"schema_version":"1.0","source":{"id":"2410.20916","kind":"arxiv","version":1}},"canonical_sha256":"709b9c5e28d682309f713804476ce56b07d8c174d2a5d0e71b8a4a05e28d10cc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"709b9c5e28d682309f713804476ce56b07d8c174d2a5d0e71b8a4a05e28d10cc","first_computed_at":"2026-07-05T09:27:13.111472Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:27:13.111472Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hg2rnnSxNat+Sc07OnUmuYxYRDKIwnfpyrnb+MeifBZ9QVsgjtyXQSKtkSfb1te4oT1xCx1noROcEClreQE2AA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:27:13.111896Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.20916","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bc091915c7b9a659d654fe2d6336eec1ad16f5cad0a2315289249056f42f1ebc","sha256:20cfc6a69e584280ed5f3d28218b78225404f4c52ba6fb37c4a55712f8060ede"],"state_sha256":"5b454c54f0e4b54c8dffdf2d0cbfe350ca00abc0f1ea76ea152720a8a5adb5f5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QJmnWIjU3w7CXVUgIUr/6j+qp/DiLrhRtBAXMJCDSQM91nqF7KDrG0NMZ8Y4a2E2AT+TmsBylGTqaSQYRkAkBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T09:33:05.759905Z","bundle_sha256":"c4830841ba9ade7b09c872e73a0bd49ea9e5c9a6d295f2c36eb2842edf4a79e7"}}