{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:YF7N7USOHSVPZMY3KXC4XZBH3P","short_pith_number":"pith:YF7N7USO","canonical_record":{"source":{"id":"2409.11182","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-16T05:31:01Z","cross_cats_sorted":[],"title_canon_sha256":"30428e9adff7e960875f4a9713a8b68f5df69fc6e5c8f8373e89b1a0bdc04e78","abstract_canon_sha256":"f538b8f62d35254d2c869f6ee4fe5bb0c9a5d09ad1e635cdbb84189d59169aea"},"schema_version":"1.0"},"canonical_sha256":"c17edfd24e3caafcb31b55c5cbe427dbd6515c656fe9457171a5905cf4420014","source":{"kind":"arxiv","id":"2409.11182","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.11182","created_at":"2026-07-05T09:08:02Z"},{"alias_kind":"arxiv_version","alias_value":"2409.11182v1","created_at":"2026-07-05T09:08:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.11182","created_at":"2026-07-05T09:08:02Z"},{"alias_kind":"pith_short_12","alias_value":"YF7N7USOHSVP","created_at":"2026-07-05T09:08:02Z"},{"alias_kind":"pith_short_16","alias_value":"YF7N7USOHSVPZMY3","created_at":"2026-07-05T09:08:02Z"},{"alias_kind":"pith_short_8","alias_value":"YF7N7USO","created_at":"2026-07-05T09:08:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:YF7N7USOHSVPZMY3KXC4XZBH3P","target":"record","payload":{"canonical_record":{"source":{"id":"2409.11182","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-16T05:31:01Z","cross_cats_sorted":[],"title_canon_sha256":"30428e9adff7e960875f4a9713a8b68f5df69fc6e5c8f8373e89b1a0bdc04e78","abstract_canon_sha256":"f538b8f62d35254d2c869f6ee4fe5bb0c9a5d09ad1e635cdbb84189d59169aea"},"schema_version":"1.0"},"canonical_sha256":"c17edfd24e3caafcb31b55c5cbe427dbd6515c656fe9457171a5905cf4420014","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:08:02.799049Z","signature_b64":"qlJgHNbuyF2xqFhz+DNLWcwy9pC/+6Bo6Un47Pxp2iujxGmtEkokrZ8fbfQ3hGLHngFU2JWyYNcJ1LQaNyJTBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c17edfd24e3caafcb31b55c5cbe427dbd6515c656fe9457171a5905cf4420014","last_reissued_at":"2026-07-05T09:08:02.798487Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:08:02.798487Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.11182","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":"2026-07-05T09:08:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WOGIAl8laAzyh8n9mxGamZO+Pye/jXgGm3wHnODj2LN1v+WCrt+mRlOC09IuWelk/YoCLVGthXsyidUKcVN8DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T17:09:13.639179Z"},"content_sha256":"7c940291d60b879973d40c1459714d30278154193603c89f281d804a924fd6d0","schema_version":"1.0","event_id":"sha256:7c940291d60b879973d40c1459714d30278154193603c89f281d804a924fd6d0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:YF7N7USOHSVPZMY3KXC4XZBH3P","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Video Token Sparsification for Efficient Multimodal LLMs in Autonomous Driving","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Amr Abdelraouf, Kyungtae Han, Rohit Gupta, Yunsheng Ma, Ziran Wang","submitted_at":"2024-09-16T05:31:01Z","abstract_excerpt":"Multimodal large language models (MLLMs) have demonstrated remarkable potential for enhancing scene understanding in autonomous driving systems through powerful logical reasoning capabilities. However, the deployment of these models faces significant challenges due to their substantial parameter sizes and computational demands, which often exceed the constraints of onboard computation. One major limitation arises from the large number of visual tokens required to capture fine-grained and long-context visual information, leading to increased latency and memory consumption. To address this issue"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.11182","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/2409.11182/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":"2026-07-05T09:08:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6FWppcJeVmHyvlI+m6GRhrT8r6aeDB7KwvRJNHGODzYY9ksdiCfsS/qXj96zklppOSHRYsNJdcIW/BFdVYQICw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T17:09:13.639713Z"},"content_sha256":"30e531c27a90131942e4054bc4477cfd2eb4895ea4f816a2a432a04c7b6ee447","schema_version":"1.0","event_id":"sha256:30e531c27a90131942e4054bc4477cfd2eb4895ea4f816a2a432a04c7b6ee447"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YF7N7USOHSVPZMY3KXC4XZBH3P/bundle.json","state_url":"https://pith.science/pith/YF7N7USOHSVPZMY3KXC4XZBH3P/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YF7N7USOHSVPZMY3KXC4XZBH3P/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":"2026-08-10T17:09:13Z","links":{"resolver":"https://pith.science/pith/YF7N7USOHSVPZMY3KXC4XZBH3P","bundle":"https://pith.science/pith/YF7N7USOHSVPZMY3KXC4XZBH3P/bundle.json","state":"https://pith.science/pith/YF7N7USOHSVPZMY3KXC4XZBH3P/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YF7N7USOHSVPZMY3KXC4XZBH3P/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:YF7N7USOHSVPZMY3KXC4XZBH3P","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":"f538b8f62d35254d2c869f6ee4fe5bb0c9a5d09ad1e635cdbb84189d59169aea","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-16T05:31:01Z","title_canon_sha256":"30428e9adff7e960875f4a9713a8b68f5df69fc6e5c8f8373e89b1a0bdc04e78"},"schema_version":"1.0","source":{"id":"2409.11182","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.11182","created_at":"2026-07-05T09:08:02Z"},{"alias_kind":"arxiv_version","alias_value":"2409.11182v1","created_at":"2026-07-05T09:08:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.11182","created_at":"2026-07-05T09:08:02Z"},{"alias_kind":"pith_short_12","alias_value":"YF7N7USOHSVP","created_at":"2026-07-05T09:08:02Z"},{"alias_kind":"pith_short_16","alias_value":"YF7N7USOHSVPZMY3","created_at":"2026-07-05T09:08:02Z"},{"alias_kind":"pith_short_8","alias_value":"YF7N7USO","created_at":"2026-07-05T09:08:02Z"}],"graph_snapshots":[{"event_id":"sha256:30e531c27a90131942e4054bc4477cfd2eb4895ea4f816a2a432a04c7b6ee447","target":"graph","created_at":"2026-07-05T09:08:02Z","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/2409.11182/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multimodal large language models (MLLMs) have demonstrated remarkable potential for enhancing scene understanding in autonomous driving systems through powerful logical reasoning capabilities. However, the deployment of these models faces significant challenges due to their substantial parameter sizes and computational demands, which often exceed the constraints of onboard computation. One major limitation arises from the large number of visual tokens required to capture fine-grained and long-context visual information, leading to increased latency and memory consumption. To address this issue","authors_text":"Amr Abdelraouf, Kyungtae Han, Rohit Gupta, Yunsheng Ma, Ziran Wang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-16T05:31:01Z","title":"Video Token Sparsification for Efficient Multimodal LLMs in Autonomous Driving"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.11182","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":"sha256:7c940291d60b879973d40c1459714d30278154193603c89f281d804a924fd6d0","target":"record","created_at":"2026-07-05T09:08:02Z","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":"f538b8f62d35254d2c869f6ee4fe5bb0c9a5d09ad1e635cdbb84189d59169aea","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-16T05:31:01Z","title_canon_sha256":"30428e9adff7e960875f4a9713a8b68f5df69fc6e5c8f8373e89b1a0bdc04e78"},"schema_version":"1.0","source":{"id":"2409.11182","kind":"arxiv","version":1}},"canonical_sha256":"c17edfd24e3caafcb31b55c5cbe427dbd6515c656fe9457171a5905cf4420014","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c17edfd24e3caafcb31b55c5cbe427dbd6515c656fe9457171a5905cf4420014","first_computed_at":"2026-07-05T09:08:02.798487Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:08:02.798487Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qlJgHNbuyF2xqFhz+DNLWcwy9pC/+6Bo6Un47Pxp2iujxGmtEkokrZ8fbfQ3hGLHngFU2JWyYNcJ1LQaNyJTBA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:08:02.799049Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.11182","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7c940291d60b879973d40c1459714d30278154193603c89f281d804a924fd6d0","sha256:30e531c27a90131942e4054bc4477cfd2eb4895ea4f816a2a432a04c7b6ee447"],"state_sha256":"78f4e30019327e546f8440641146263b7bc6630ad58d5b559e33d6a450f8af80"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CAn2sxPcogfkMeOa9JIs8z43GJrVzcN9v/vJlKnFpi4BApriPCa+BVy33NtRcH9PydIbWAiJS8Y2FrciEJeIAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T17:09:13.645023Z","bundle_sha256":"d7c593a561ce637bb4f4f4598fdc8fed32af0ff55b128978923c17297d5b35a0"}}