{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:XSXNQ4JP66AUTGM376LMI4AVK7","short_pith_number":"pith:XSXNQ4JP","canonical_record":{"source":{"id":"2502.13145","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-18T18:59:57Z","cross_cats_sorted":[],"title_canon_sha256":"52dff5f5f9536fecfc6cbd90ac6a6fea5d9157d9d4798e18b9c600b341880db1","abstract_canon_sha256":"924a07e896d36c03176a092e7a0842980df462983f61d6e19f8363d213b2d229"},"schema_version":"1.0"},"canonical_sha256":"bcaed8712ff78149999bff96c4701557d3d42af0bcf2105fd00eca50e90193be","source":{"kind":"arxiv","id":"2502.13145","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.13145","created_at":"2026-07-05T10:33:45Z"},{"alias_kind":"arxiv_version","alias_value":"2502.13145v2","created_at":"2026-07-05T10:33:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.13145","created_at":"2026-07-05T10:33:45Z"},{"alias_kind":"pith_short_12","alias_value":"XSXNQ4JP66AU","created_at":"2026-07-05T10:33:45Z"},{"alias_kind":"pith_short_16","alias_value":"XSXNQ4JP66AUTGM3","created_at":"2026-07-05T10:33:45Z"},{"alias_kind":"pith_short_8","alias_value":"XSXNQ4JP","created_at":"2026-07-05T10:33:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:XSXNQ4JP66AUTGM376LMI4AVK7","target":"record","payload":{"canonical_record":{"source":{"id":"2502.13145","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-18T18:59:57Z","cross_cats_sorted":[],"title_canon_sha256":"52dff5f5f9536fecfc6cbd90ac6a6fea5d9157d9d4798e18b9c600b341880db1","abstract_canon_sha256":"924a07e896d36c03176a092e7a0842980df462983f61d6e19f8363d213b2d229"},"schema_version":"1.0"},"canonical_sha256":"bcaed8712ff78149999bff96c4701557d3d42af0bcf2105fd00eca50e90193be","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:33:45.230580Z","signature_b64":"bpwTg1ERpge1c2KMyM4iuR9hS5Mgy/89yQRWNhnQz8iqJCKvEvdfb80EU8KBEyWzdlSput73ZA2fN/jhUfmCCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bcaed8712ff78149999bff96c4701557d3d42af0bcf2105fd00eca50e90193be","last_reissued_at":"2026-07-05T10:33:45.229558Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:33:45.229558Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.13145","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":"2026-07-05T10:33:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kGR5l3/F5ARN1kBpZXrzMAzBZuTPzTQqEYQpARtYqjB/F+8alxo+XjP2UVXmCzeu/CtwCG1l1VHLDc2J5uOwDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T06:25:56.521016Z"},"content_sha256":"d71f255f248515146510f29edf90f24abe208db09e3b6c3222d3e2fc2eacb0cf","schema_version":"1.0","event_id":"sha256:d71f255f248515146510f29edf90f24abe208db09e3b6c3222d3e2fc2eacb0cf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:XSXNQ4JP66AUTGM376LMI4AVK7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multimodal Mamba: Decoder-only Multimodal State Space Model via Quadratic to Linear Distillation","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bencheng Liao, Haoran Yin, Hongyuan Tao, Qian Zhang, Tianheng Cheng, Wenyu Liu, Xinggang Wang, Yingyue Li","submitted_at":"2025-02-18T18:59:57Z","abstract_excerpt":"Recent Multimodal Large Language Models (MLLMs) have achieved remarkable performance but face deployment challenges due to their quadratic computational complexity, growing Key-Value cache requirements, and reliance on separate vision encoders. We propose mmMamba, a framework for developing linear-complexity native multimodal state space models through progressive distillation from existing MLLMs using moderate academic computational resources. Our approach enables the direct conversion of trained decoder-only MLLMs to linear-complexity architectures without requiring pre-trained RNN-based LLM"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.13145","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/2502.13145/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":"2026-07-05T10:33:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NWWjTB8EY2ZZ2bXY3uen3d0Lc/tiX4y7ZEFOHBWPPElgHL+v6i4RmxakNX/UAfkDvolQbAAxRyYwvQgNp+D0DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T06:25:56.521500Z"},"content_sha256":"d530613ac8992fff48af04e65d4a4a2af6d5a07ff394c338931fbd73e0cb25ab","schema_version":"1.0","event_id":"sha256:d530613ac8992fff48af04e65d4a4a2af6d5a07ff394c338931fbd73e0cb25ab"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XSXNQ4JP66AUTGM376LMI4AVK7/bundle.json","state_url":"https://pith.science/pith/XSXNQ4JP66AUTGM376LMI4AVK7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XSXNQ4JP66AUTGM376LMI4AVK7/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":"2026-08-10T06:25:56Z","links":{"resolver":"https://pith.science/pith/XSXNQ4JP66AUTGM376LMI4AVK7","bundle":"https://pith.science/pith/XSXNQ4JP66AUTGM376LMI4AVK7/bundle.json","state":"https://pith.science/pith/XSXNQ4JP66AUTGM376LMI4AVK7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XSXNQ4JP66AUTGM376LMI4AVK7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:XSXNQ4JP66AUTGM376LMI4AVK7","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":"924a07e896d36c03176a092e7a0842980df462983f61d6e19f8363d213b2d229","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-18T18:59:57Z","title_canon_sha256":"52dff5f5f9536fecfc6cbd90ac6a6fea5d9157d9d4798e18b9c600b341880db1"},"schema_version":"1.0","source":{"id":"2502.13145","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.13145","created_at":"2026-07-05T10:33:45Z"},{"alias_kind":"arxiv_version","alias_value":"2502.13145v2","created_at":"2026-07-05T10:33:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.13145","created_at":"2026-07-05T10:33:45Z"},{"alias_kind":"pith_short_12","alias_value":"XSXNQ4JP66AU","created_at":"2026-07-05T10:33:45Z"},{"alias_kind":"pith_short_16","alias_value":"XSXNQ4JP66AUTGM3","created_at":"2026-07-05T10:33:45Z"},{"alias_kind":"pith_short_8","alias_value":"XSXNQ4JP","created_at":"2026-07-05T10:33:45Z"}],"graph_snapshots":[{"event_id":"sha256:d530613ac8992fff48af04e65d4a4a2af6d5a07ff394c338931fbd73e0cb25ab","target":"graph","created_at":"2026-07-05T10:33:45Z","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/2502.13145/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent Multimodal Large Language Models (MLLMs) have achieved remarkable performance but face deployment challenges due to their quadratic computational complexity, growing Key-Value cache requirements, and reliance on separate vision encoders. We propose mmMamba, a framework for developing linear-complexity native multimodal state space models through progressive distillation from existing MLLMs using moderate academic computational resources. Our approach enables the direct conversion of trained decoder-only MLLMs to linear-complexity architectures without requiring pre-trained RNN-based LLM","authors_text":"Bencheng Liao, Haoran Yin, Hongyuan Tao, Qian Zhang, Tianheng Cheng, Wenyu Liu, Xinggang Wang, Yingyue Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-18T18:59:57Z","title":"Multimodal Mamba: Decoder-only Multimodal State Space Model via Quadratic to Linear Distillation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.13145","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:d71f255f248515146510f29edf90f24abe208db09e3b6c3222d3e2fc2eacb0cf","target":"record","created_at":"2026-07-05T10:33:45Z","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":"924a07e896d36c03176a092e7a0842980df462983f61d6e19f8363d213b2d229","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2025-02-18T18:59:57Z","title_canon_sha256":"52dff5f5f9536fecfc6cbd90ac6a6fea5d9157d9d4798e18b9c600b341880db1"},"schema_version":"1.0","source":{"id":"2502.13145","kind":"arxiv","version":2}},"canonical_sha256":"bcaed8712ff78149999bff96c4701557d3d42af0bcf2105fd00eca50e90193be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bcaed8712ff78149999bff96c4701557d3d42af0bcf2105fd00eca50e90193be","first_computed_at":"2026-07-05T10:33:45.229558Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:33:45.229558Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"bpwTg1ERpge1c2KMyM4iuR9hS5Mgy/89yQRWNhnQz8iqJCKvEvdfb80EU8KBEyWzdlSput73ZA2fN/jhUfmCCA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:33:45.230580Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.13145","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d71f255f248515146510f29edf90f24abe208db09e3b6c3222d3e2fc2eacb0cf","sha256:d530613ac8992fff48af04e65d4a4a2af6d5a07ff394c338931fbd73e0cb25ab"],"state_sha256":"45f5fbde6ee3debb98c59744a2cf854509edb818f63e53c038c4156fe6e64f8c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DT2RER7rethnkhYtpZBd7TXln/ryBFEaIX+4Z+ccFRuvBM1QBC3KLCko6uOeXaJ+gD9MywZxtvJ0qKG+gTIUDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T06:25:56.525015Z","bundle_sha256":"1a49b1556b880eaa412c0ce42be7c116a4c8853daafd59b1e18d0d02345dab4a"}}