{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:WB2EJXRHGDEHQ3GHQ7JYEV7VCR","short_pith_number":"pith:WB2EJXRH","canonical_record":{"source":{"id":"2403.00818","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T09:21:59Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"7b27f5522ba3f62aa58f8fa368059e6e9c45a9d1b6e9e2c1e327344768f9c951","abstract_canon_sha256":"3dcce3e6dae101f301f0a3ac3af57d3fd257547aa8cbf2a8184961767063c966"},"schema_version":"1.0"},"canonical_sha256":"b07444de2730c8786cc787d38257f51457963a890541b19ff896c0b3c0283a62","source":{"kind":"arxiv","id":"2403.00818","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.00818","created_at":"2026-07-05T07:52:16Z"},{"alias_kind":"arxiv_version","alias_value":"2403.00818v2","created_at":"2026-07-05T07:52:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.00818","created_at":"2026-07-05T07:52:16Z"},{"alias_kind":"pith_short_12","alias_value":"WB2EJXRHGDEH","created_at":"2026-07-05T07:52:16Z"},{"alias_kind":"pith_short_16","alias_value":"WB2EJXRHGDEHQ3GH","created_at":"2026-07-05T07:52:16Z"},{"alias_kind":"pith_short_8","alias_value":"WB2EJXRH","created_at":"2026-07-05T07:52:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:WB2EJXRHGDEHQ3GHQ7JYEV7VCR","target":"record","payload":{"canonical_record":{"source":{"id":"2403.00818","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T09:21:59Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"7b27f5522ba3f62aa58f8fa368059e6e9c45a9d1b6e9e2c1e327344768f9c951","abstract_canon_sha256":"3dcce3e6dae101f301f0a3ac3af57d3fd257547aa8cbf2a8184961767063c966"},"schema_version":"1.0"},"canonical_sha256":"b07444de2730c8786cc787d38257f51457963a890541b19ff896c0b3c0283a62","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:52:16.962895Z","signature_b64":"axi/rz9XEQhYIu9LwgP0TDN3QqEJfMH+P2CYtDByOPBt3CmPbZDLxCG4Rtck0Mu2c4Vzya6ONMLLhqzXLH9oBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b07444de2730c8786cc787d38257f51457963a890541b19ff896c0b3c0283a62","last_reissued_at":"2026-07-05T07:52:16.962461Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:52:16.962461Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.00818","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":"2026-07-05T07:52:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ef0OqsL6soSYJlywe68PVieVC5dJspPFskLTGPHs5UGmvJPLDBnzBMUBxXW9AA9syNwJ2zQjswe7ponrRa5jBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T12:33:20.389441Z"},"content_sha256":"e54a2a6757ef881817f783ab4afd8d73f08a105539e9f898b7767a6489046206","schema_version":"1.0","event_id":"sha256:e54a2a6757ef881817f783ab4afd8d73f08a105539e9f898b7767a6489046206"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:WB2EJXRHGDEHQ3GHQ7JYEV7VCR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Chengcheng Wang, Kai Han, Tianyu Guo, Wei He, Yehui Tang, Yujie Yang, Yunhe Wang","submitted_at":"2024-02-26T09:21:59Z","abstract_excerpt":"Large language models (LLMs) face a daunting challenge due to the excessive computational and memory requirements of the commonly used Transformer architecture. While state space model (SSM) is a new type of foundational network architecture offering lower computational complexity, their performance has yet to fully rival that of Transformers. This paper introduces DenseSSM, a novel approach to enhance the flow of hidden information between layers in SSMs. By selectively integrating shallowlayer hidden states into deeper layers, DenseSSM retains fine-grained information crucial for the final o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.00818","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/2403.00818/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":"2026-07-05T07:52:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nsEWOIQsSeKwDGKu+JDhAIWzf9+ox8aKALB4E+ZyFXsPzBgwdp7Lea7S+qYts1r8Lw1u1eIQMElfEV8UIbobAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T12:33:20.389964Z"},"content_sha256":"e90f0486fc2fe48cafbfdaa3ff4e9e287845dca325c684e0727dd0d25d0c3601","schema_version":"1.0","event_id":"sha256:e90f0486fc2fe48cafbfdaa3ff4e9e287845dca325c684e0727dd0d25d0c3601"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WB2EJXRHGDEHQ3GHQ7JYEV7VCR/bundle.json","state_url":"https://pith.science/pith/WB2EJXRHGDEHQ3GHQ7JYEV7VCR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WB2EJXRHGDEHQ3GHQ7JYEV7VCR/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":"2026-08-22T12:33:20Z","links":{"resolver":"https://pith.science/pith/WB2EJXRHGDEHQ3GHQ7JYEV7VCR","bundle":"https://pith.science/pith/WB2EJXRHGDEHQ3GHQ7JYEV7VCR/bundle.json","state":"https://pith.science/pith/WB2EJXRHGDEHQ3GHQ7JYEV7VCR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WB2EJXRHGDEHQ3GHQ7JYEV7VCR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:WB2EJXRHGDEHQ3GHQ7JYEV7VCR","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":"3dcce3e6dae101f301f0a3ac3af57d3fd257547aa8cbf2a8184961767063c966","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T09:21:59Z","title_canon_sha256":"7b27f5522ba3f62aa58f8fa368059e6e9c45a9d1b6e9e2c1e327344768f9c951"},"schema_version":"1.0","source":{"id":"2403.00818","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.00818","created_at":"2026-07-05T07:52:16Z"},{"alias_kind":"arxiv_version","alias_value":"2403.00818v2","created_at":"2026-07-05T07:52:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.00818","created_at":"2026-07-05T07:52:16Z"},{"alias_kind":"pith_short_12","alias_value":"WB2EJXRHGDEH","created_at":"2026-07-05T07:52:16Z"},{"alias_kind":"pith_short_16","alias_value":"WB2EJXRHGDEHQ3GH","created_at":"2026-07-05T07:52:16Z"},{"alias_kind":"pith_short_8","alias_value":"WB2EJXRH","created_at":"2026-07-05T07:52:16Z"}],"graph_snapshots":[{"event_id":"sha256:e90f0486fc2fe48cafbfdaa3ff4e9e287845dca325c684e0727dd0d25d0c3601","target":"graph","created_at":"2026-07-05T07:52:16Z","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/2403.00818/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) face a daunting challenge due to the excessive computational and memory requirements of the commonly used Transformer architecture. While state space model (SSM) is a new type of foundational network architecture offering lower computational complexity, their performance has yet to fully rival that of Transformers. This paper introduces DenseSSM, a novel approach to enhance the flow of hidden information between layers in SSMs. By selectively integrating shallowlayer hidden states into deeper layers, DenseSSM retains fine-grained information crucial for the final o","authors_text":"Chengcheng Wang, Kai Han, Tianyu Guo, Wei He, Yehui Tang, Yujie Yang, Yunhe Wang","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T09:21:59Z","title":"DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.00818","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:e54a2a6757ef881817f783ab4afd8d73f08a105539e9f898b7767a6489046206","target":"record","created_at":"2026-07-05T07:52:16Z","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":"3dcce3e6dae101f301f0a3ac3af57d3fd257547aa8cbf2a8184961767063c966","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-26T09:21:59Z","title_canon_sha256":"7b27f5522ba3f62aa58f8fa368059e6e9c45a9d1b6e9e2c1e327344768f9c951"},"schema_version":"1.0","source":{"id":"2403.00818","kind":"arxiv","version":2}},"canonical_sha256":"b07444de2730c8786cc787d38257f51457963a890541b19ff896c0b3c0283a62","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b07444de2730c8786cc787d38257f51457963a890541b19ff896c0b3c0283a62","first_computed_at":"2026-07-05T07:52:16.962461Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:52:16.962461Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"axi/rz9XEQhYIu9LwgP0TDN3QqEJfMH+P2CYtDByOPBt3CmPbZDLxCG4Rtck0Mu2c4Vzya6ONMLLhqzXLH9oBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:52:16.962895Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.00818","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e54a2a6757ef881817f783ab4afd8d73f08a105539e9f898b7767a6489046206","sha256:e90f0486fc2fe48cafbfdaa3ff4e9e287845dca325c684e0727dd0d25d0c3601"],"state_sha256":"fd61902d0a6270577e7ab156333a7eac6f4185064d2c618473e299848ce3117a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"od/qcB1plrGsWoHZoIaFgbypHG2wQgBlIRqgPIOITVLRoJtdsr9Vu3NnH/+tIyIV/AdSS9BK9/Nuris9N406AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T12:33:20.393724Z","bundle_sha256":"cce87b01b896439fbdc23025393304b8efc371eebc93026c399fbaac54d1413b"}}