{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:QSJ375FM5TOARRSRQELOHTRTXB","short_pith_number":"pith:QSJ375FM","canonical_record":{"source":{"id":"2412.07689","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-10T17:27:32Z","cross_cats_sorted":["cs.MM","cs.RO"],"title_canon_sha256":"2b70daf61731454a3ad55373c520d284a01cd67959ebc023580b5005ac34ecb6","abstract_canon_sha256":"4c055d9d1d5c92bc3ba7738ed78d1c4bcabc7bff3d0c4126b466172532677ff8"},"schema_version":"1.0"},"canonical_sha256":"8493bff4acecdc08c6518116e3ce33b841880000422ccc2606d100716fe993bc","source":{"kind":"arxiv","id":"2412.07689","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.07689","created_at":"2026-07-05T11:49:48Z"},{"alias_kind":"arxiv_version","alias_value":"2412.07689v5","created_at":"2026-07-05T11:49:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.07689","created_at":"2026-07-05T11:49:48Z"},{"alias_kind":"pith_short_12","alias_value":"QSJ375FM5TOA","created_at":"2026-07-05T11:49:48Z"},{"alias_kind":"pith_short_16","alias_value":"QSJ375FM5TOARRSR","created_at":"2026-07-05T11:49:48Z"},{"alias_kind":"pith_short_8","alias_value":"QSJ375FM","created_at":"2026-07-05T11:49:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:QSJ375FM5TOARRSRQELOHTRTXB","target":"record","payload":{"canonical_record":{"source":{"id":"2412.07689","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-10T17:27:32Z","cross_cats_sorted":["cs.MM","cs.RO"],"title_canon_sha256":"2b70daf61731454a3ad55373c520d284a01cd67959ebc023580b5005ac34ecb6","abstract_canon_sha256":"4c055d9d1d5c92bc3ba7738ed78d1c4bcabc7bff3d0c4126b466172532677ff8"},"schema_version":"1.0"},"canonical_sha256":"8493bff4acecdc08c6518116e3ce33b841880000422ccc2606d100716fe993bc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:49:48.733618Z","signature_b64":"xP4aeuRCb4ipBZr4KRJHpNHkqn10Au68RVYT71zsTwOfZOnbml8XczKLhx2qi/5F8rzM2q5A5knRIHbnddy2BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8493bff4acecdc08c6518116e3ce33b841880000422ccc2606d100716fe993bc","last_reissued_at":"2026-07-05T11:49:48.733090Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:49:48.733090Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.07689","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:49:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"30t9Xx+CFHIQfqGVQLqER3xLdRXPQTcIoxSZBIGlJwbbQ+ApdPvmIxojguGNzAiQfE4oAiyl+S/+NlL1YH5hDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T22:29:38.649395Z"},"content_sha256":"5e9237a5b4442816ebbdf8100bd56ce54a3d745b002e15f920a000af8f258022","schema_version":"1.0","event_id":"sha256:5e9237a5b4442816ebbdf8100bd56ce54a3d745b002e15f920a000af8f258022"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:QSJ375FM5TOARRSRQELOHTRTXB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RoboTron-Drive: All-in-One Large Multimodal Model for Autonomous Driving","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.MM","cs.RO"],"primary_cat":"cs.CV","authors_text":"Baihui Xiao, Chengjian Feng, Feng Yan, Lin Ma, Xiaodan Liang, Yujie Zhong, Zequn Jie, Zhijian Huang","submitted_at":"2024-12-10T17:27:32Z","abstract_excerpt":"Large Multimodal Models (LMMs) have demonstrated exceptional comprehension and interpretation capabilities in Autonomous Driving (AD) by incorporating large language models. Despite the advancements, current data-driven AD approaches tend to concentrate on a single dataset and specific tasks, neglecting their overall capabilities and ability to generalize. To bridge these gaps, we propose RoboTron-Drive, a general large multimodal model designed to process diverse data inputs, such as images and multi-view videos, while performing a broad spectrum of AD tasks, including perception, prediction,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.07689","kind":"arxiv","version":5},"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/2412.07689/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":"2026-07-05T11:49:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TYzZ4327uZKne/MFDQJEj86oeNWahurLfRoqvFYz4un3mBT3QVoM2ETx+qactiZza2gVmj7PaA+aNivuEONmCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T22:29:38.649913Z"},"content_sha256":"a172db6d490152894345df92229dbe6d6fd4b7d291b7630265e0d001fa14e702","schema_version":"1.0","event_id":"sha256:a172db6d490152894345df92229dbe6d6fd4b7d291b7630265e0d001fa14e702"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QSJ375FM5TOARRSRQELOHTRTXB/bundle.json","state_url":"https://pith.science/pith/QSJ375FM5TOARRSRQELOHTRTXB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QSJ375FM5TOARRSRQELOHTRTXB/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":"2026-08-04T22:29:38Z","links":{"resolver":"https://pith.science/pith/QSJ375FM5TOARRSRQELOHTRTXB","bundle":"https://pith.science/pith/QSJ375FM5TOARRSRQELOHTRTXB/bundle.json","state":"https://pith.science/pith/QSJ375FM5TOARRSRQELOHTRTXB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QSJ375FM5TOARRSRQELOHTRTXB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QSJ375FM5TOARRSRQELOHTRTXB","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":"4c055d9d1d5c92bc3ba7738ed78d1c4bcabc7bff3d0c4126b466172532677ff8","cross_cats_sorted":["cs.MM","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-10T17:27:32Z","title_canon_sha256":"2b70daf61731454a3ad55373c520d284a01cd67959ebc023580b5005ac34ecb6"},"schema_version":"1.0","source":{"id":"2412.07689","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.07689","created_at":"2026-07-05T11:49:48Z"},{"alias_kind":"arxiv_version","alias_value":"2412.07689v5","created_at":"2026-07-05T11:49:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.07689","created_at":"2026-07-05T11:49:48Z"},{"alias_kind":"pith_short_12","alias_value":"QSJ375FM5TOA","created_at":"2026-07-05T11:49:48Z"},{"alias_kind":"pith_short_16","alias_value":"QSJ375FM5TOARRSR","created_at":"2026-07-05T11:49:48Z"},{"alias_kind":"pith_short_8","alias_value":"QSJ375FM","created_at":"2026-07-05T11:49:48Z"}],"graph_snapshots":[{"event_id":"sha256:a172db6d490152894345df92229dbe6d6fd4b7d291b7630265e0d001fa14e702","target":"graph","created_at":"2026-07-05T11:49:48Z","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/2412.07689/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Multimodal Models (LMMs) have demonstrated exceptional comprehension and interpretation capabilities in Autonomous Driving (AD) by incorporating large language models. Despite the advancements, current data-driven AD approaches tend to concentrate on a single dataset and specific tasks, neglecting their overall capabilities and ability to generalize. To bridge these gaps, we propose RoboTron-Drive, a general large multimodal model designed to process diverse data inputs, such as images and multi-view videos, while performing a broad spectrum of AD tasks, including perception, prediction,","authors_text":"Baihui Xiao, Chengjian Feng, Feng Yan, Lin Ma, Xiaodan Liang, Yujie Zhong, Zequn Jie, Zhijian Huang","cross_cats":["cs.MM","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-10T17:27:32Z","title":"RoboTron-Drive: All-in-One Large Multimodal Model for Autonomous Driving"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.07689","kind":"arxiv","version":5},"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":"sha256:5e9237a5b4442816ebbdf8100bd56ce54a3d745b002e15f920a000af8f258022","target":"record","created_at":"2026-07-05T11:49:48Z","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":"4c055d9d1d5c92bc3ba7738ed78d1c4bcabc7bff3d0c4126b466172532677ff8","cross_cats_sorted":["cs.MM","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-10T17:27:32Z","title_canon_sha256":"2b70daf61731454a3ad55373c520d284a01cd67959ebc023580b5005ac34ecb6"},"schema_version":"1.0","source":{"id":"2412.07689","kind":"arxiv","version":5}},"canonical_sha256":"8493bff4acecdc08c6518116e3ce33b841880000422ccc2606d100716fe993bc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8493bff4acecdc08c6518116e3ce33b841880000422ccc2606d100716fe993bc","first_computed_at":"2026-07-05T11:49:48.733090Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:49:48.733090Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xP4aeuRCb4ipBZr4KRJHpNHkqn10Au68RVYT71zsTwOfZOnbml8XczKLhx2qi/5F8rzM2q5A5knRIHbnddy2BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:49:48.733618Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.07689","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5e9237a5b4442816ebbdf8100bd56ce54a3d745b002e15f920a000af8f258022","sha256:a172db6d490152894345df92229dbe6d6fd4b7d291b7630265e0d001fa14e702"],"state_sha256":"5214784190d4afc3380bd09b0d5618b37d544387ae032dcad722089a544ffc99"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6bLrKqB0Dj+k5xsz9WGJQI4Yy2iwLQmB978uEJrzIh1ZrGfHNLfH/6zhTJ0MZDKW+iq6Wg4LzsAEGK+W6LVhBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T22:29:38.654809Z","bundle_sha256":"da112c8e3f10494b2ff34ffa11e6231cb9079e6c28a44135557f10399c5fb5eb"}}