{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:YMPNMKCQWTXYWQTKZMHZQYGJPO","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":"513c05a8af49ea97932ec4df0423fc92c24bf00945ef03e7a6b51c1bfd8a063a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-09T13:02:35Z","title_canon_sha256":"7b971fdfd8277069e1e5ba7fdce34ad9e69c545ce3990090bb77dc00a3c3dd87"},"schema_version":"1.0","source":{"id":"2412.06458","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.06458","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"arxiv_version","alias_value":"2412.06458v2","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.06458","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"pith_short_12","alias_value":"YMPNMKCQWTXY","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"pith_short_16","alias_value":"YMPNMKCQWTXYWQTK","created_at":"2026-07-05T11:45:54Z"},{"alias_kind":"pith_short_8","alias_value":"YMPNMKCQ","created_at":"2026-07-05T11:45:54Z"}],"graph_snapshots":[{"event_id":"sha256:267dff914921486a2486eb6ae3f22a0214f6b27f207843a07c39bb973862bb87","target":"graph","created_at":"2026-07-05T11:45:54Z","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/2412.06458/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Although Large Vision-Language Models (LVLMs) have achieved impressive results, their high computational costs pose a significant barrier to wide application. To enhance inference efficiency, most existing approaches can be categorized as parameter-dependent or token-dependent strategies to reduce computational demands. However, parameter-dependent methods require retraining LVLMs to recover performance while token-dependent strategies struggle to consistently select the most relevant tokens. In this paper, we systematically analyze the above challenges and provide a series of valuable insight","authors_text":"Ji Ma, Lin Yuanbo Wu, Mengyang Sun, Peng Wang, Wei Suo, Yanning Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-09T13:02:35Z","title":"Pruning All-Rounder: Rethinking and Improving Inference Efficiency for Large Vision Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.06458","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:f944f9b10fe9bbf624bd656b3be77345be91bdf096d1c08a1d15778e8ee482c8","target":"record","created_at":"2026-07-05T11:45:54Z","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":"513c05a8af49ea97932ec4df0423fc92c24bf00945ef03e7a6b51c1bfd8a063a","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-09T13:02:35Z","title_canon_sha256":"7b971fdfd8277069e1e5ba7fdce34ad9e69c545ce3990090bb77dc00a3c3dd87"},"schema_version":"1.0","source":{"id":"2412.06458","kind":"arxiv","version":2}},"canonical_sha256":"c31ed62850b4ef8b426acb0f9860c97b851ec739f2f6ef5d639c24b8b9e92586","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c31ed62850b4ef8b426acb0f9860c97b851ec739f2f6ef5d639c24b8b9e92586","first_computed_at":"2026-07-05T11:45:54.714200Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:45:54.714200Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DxXfIDxU9+8pZMLvV5BSuPDkUcIBsUHOPIUwY8KSRhwKgR9ENRMP426UsB4TXSsHt4t5UPpJRBJ+hrrbeCm4AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:45:54.714764Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.06458","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f944f9b10fe9bbf624bd656b3be77345be91bdf096d1c08a1d15778e8ee482c8","sha256:267dff914921486a2486eb6ae3f22a0214f6b27f207843a07c39bb973862bb87"],"state_sha256":"1206b294a8d8ce48f243b0312cc5b9cc1c095e18700ce46f56977ed8acabcd48"}