{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:4KGNETC5YQDJVMB5XYYOHOKFM7","short_pith_number":"pith:4KGNETC5","canonical_record":{"source":{"id":"2502.12119","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-17T18:43:41Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"afce0decb259b459b87746e9b155a3143905dd07a329ead08758e9151fd3ea66","abstract_canon_sha256":"17dae95bde8fb207e7cbbbd095fe0d3978b653ea0703b202614c7b205e82e915"},"schema_version":"1.0"},"canonical_sha256":"e28cd24c5dc4069ab03dbe30e3b94567c7d1fd383ec9183109ae3aafd16410f3","source":{"kind":"arxiv","id":"2502.12119","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.12119","created_at":"2026-06-01T01:03:39Z"},{"alias_kind":"arxiv_version","alias_value":"2502.12119v4","created_at":"2026-06-01T01:03:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.12119","created_at":"2026-06-01T01:03:39Z"},{"alias_kind":"pith_short_12","alias_value":"4KGNETC5YQDJ","created_at":"2026-06-01T01:03:39Z"},{"alias_kind":"pith_short_16","alias_value":"4KGNETC5YQDJVMB5","created_at":"2026-06-01T01:03:39Z"},{"alias_kind":"pith_short_8","alias_value":"4KGNETC5","created_at":"2026-06-01T01:03:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:4KGNETC5YQDJVMB5XYYOHOKFM7","target":"record","payload":{"canonical_record":{"source":{"id":"2502.12119","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-17T18:43:41Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"afce0decb259b459b87746e9b155a3143905dd07a329ead08758e9151fd3ea66","abstract_canon_sha256":"17dae95bde8fb207e7cbbbd095fe0d3978b653ea0703b202614c7b205e82e915"},"schema_version":"1.0"},"canonical_sha256":"e28cd24c5dc4069ab03dbe30e3b94567c7d1fd383ec9183109ae3aafd16410f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-01T01:03:39.615630Z","signature_b64":"UOU0zj+aqL9QyxjBWHpbxVrw/TwIxq2sz+wmTv5bHbp1BIVBwpJp+Mlhch3fE+Kq8OCt1cKkthVHaACBeY0wBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e28cd24c5dc4069ab03dbe30e3b94567c7d1fd383ec9183109ae3aafd16410f3","last_reissued_at":"2026-06-01T01:03:39.614807Z","signature_status":"signed_v1","first_computed_at":"2026-06-01T01:03:39.614807Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.12119","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-01T01:03:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JnRaJ5Si88BQLU3i5LL1nNE2fK6SCU8m7Et+yHzZ9AvEe3F5P7bSATnnIFIqyxi78Em+M5RTOMzlLL9K2gEhCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T21:48:33.671606Z"},"content_sha256":"f41c091b17666348859fc047d670afb3f478f9cfa9660acb5cbdfd0682be482f","schema_version":"1.0","event_id":"sha256:f41c091b17666348859fc047d670afb3f478f9cfa9660acb5cbdfd0682be482f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:4KGNETC5YQDJVMB5XYYOHOKFM7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.CV","authors_text":"Aniri, Artur Hecker, Danqi Yan, Hinrich Schuetze, Jinhe Bi, Mang Ye, Sikuan Yan, Volker Tresp, Wenke Huang, Xiaowen Ma, Xun Xiao, Yifan Wang, Yunpu Ma, Zengjie Jin","submitted_at":"2025-02-17T18:43:41Z","abstract_excerpt":"Visual instruction tuning adapts pre-trained Multimodal Large Language Models (MLLMs) to follow human instructions for real-world applications. However, the rapid growth of these datasets introduces significant redundancy, leading to increased computational costs. Existing methods for selecting instruction data aim to prune this redundancy, but predominantly rely on computationally demanding techniques such as proxy-based inference or training-based metrics. Consequently, the substantial computational costs incurred by these selection processes often exacerbate the very efficiency bottlenecks "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.12119","kind":"arxiv","version":4},"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/2502.12119/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":"2026-06-01T01:03:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hOCut+bYL+xApvAEmrHKgdxXY97EWBycu9TM8/Y3yoYOu0bMB/SvRUrXuBL4+SeSE+s6S7lWFc12oohH4FKeBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-01T21:48:33.671973Z"},"content_sha256":"816920c92dd9a4266c7871cc6f7185635c0820a55fcb3131f6ac78456f26a5ce","schema_version":"1.0","event_id":"sha256:816920c92dd9a4266c7871cc6f7185635c0820a55fcb3131f6ac78456f26a5ce"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4KGNETC5YQDJVMB5XYYOHOKFM7/bundle.json","state_url":"https://pith.science/pith/4KGNETC5YQDJVMB5XYYOHOKFM7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4KGNETC5YQDJVMB5XYYOHOKFM7/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":"2026-06-01T21:48:33Z","links":{"resolver":"https://pith.science/pith/4KGNETC5YQDJVMB5XYYOHOKFM7","bundle":"https://pith.science/pith/4KGNETC5YQDJVMB5XYYOHOKFM7/bundle.json","state":"https://pith.science/pith/4KGNETC5YQDJVMB5XYYOHOKFM7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4KGNETC5YQDJVMB5XYYOHOKFM7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4KGNETC5YQDJVMB5XYYOHOKFM7","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":"17dae95bde8fb207e7cbbbd095fe0d3978b653ea0703b202614c7b205e82e915","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-17T18:43:41Z","title_canon_sha256":"afce0decb259b459b87746e9b155a3143905dd07a329ead08758e9151fd3ea66"},"schema_version":"1.0","source":{"id":"2502.12119","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.12119","created_at":"2026-06-01T01:03:39Z"},{"alias_kind":"arxiv_version","alias_value":"2502.12119v4","created_at":"2026-06-01T01:03:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.12119","created_at":"2026-06-01T01:03:39Z"},{"alias_kind":"pith_short_12","alias_value":"4KGNETC5YQDJ","created_at":"2026-06-01T01:03:39Z"},{"alias_kind":"pith_short_16","alias_value":"4KGNETC5YQDJVMB5","created_at":"2026-06-01T01:03:39Z"},{"alias_kind":"pith_short_8","alias_value":"4KGNETC5","created_at":"2026-06-01T01:03:39Z"}],"graph_snapshots":[{"event_id":"sha256:816920c92dd9a4266c7871cc6f7185635c0820a55fcb3131f6ac78456f26a5ce","target":"graph","created_at":"2026-06-01T01:03:39Z","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/2502.12119/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Visual instruction tuning adapts pre-trained Multimodal Large Language Models (MLLMs) to follow human instructions for real-world applications. However, the rapid growth of these datasets introduces significant redundancy, leading to increased computational costs. Existing methods for selecting instruction data aim to prune this redundancy, but predominantly rely on computationally demanding techniques such as proxy-based inference or training-based metrics. Consequently, the substantial computational costs incurred by these selection processes often exacerbate the very efficiency bottlenecks ","authors_text":"Aniri, Artur Hecker, Danqi Yan, Hinrich Schuetze, Jinhe Bi, Mang Ye, Sikuan Yan, Volker Tresp, Wenke Huang, Xiaowen Ma, Xun Xiao, Yifan Wang, Yunpu Ma, Zengjie Jin","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-17T18:43:41Z","title":"PRISM: Self-Pruning Intrinsic Selection Method for Training-Free Multimodal Data Selection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.12119","kind":"arxiv","version":4},"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:f41c091b17666348859fc047d670afb3f478f9cfa9660acb5cbdfd0682be482f","target":"record","created_at":"2026-06-01T01:03:39Z","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":"17dae95bde8fb207e7cbbbd095fe0d3978b653ea0703b202614c7b205e82e915","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-02-17T18:43:41Z","title_canon_sha256":"afce0decb259b459b87746e9b155a3143905dd07a329ead08758e9151fd3ea66"},"schema_version":"1.0","source":{"id":"2502.12119","kind":"arxiv","version":4}},"canonical_sha256":"e28cd24c5dc4069ab03dbe30e3b94567c7d1fd383ec9183109ae3aafd16410f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e28cd24c5dc4069ab03dbe30e3b94567c7d1fd383ec9183109ae3aafd16410f3","first_computed_at":"2026-06-01T01:03:39.614807Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-01T01:03:39.614807Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UOU0zj+aqL9QyxjBWHpbxVrw/TwIxq2sz+wmTv5bHbp1BIVBwpJp+Mlhch3fE+Kq8OCt1cKkthVHaACBeY0wBA==","signature_status":"signed_v1","signed_at":"2026-06-01T01:03:39.615630Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.12119","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f41c091b17666348859fc047d670afb3f478f9cfa9660acb5cbdfd0682be482f","sha256:816920c92dd9a4266c7871cc6f7185635c0820a55fcb3131f6ac78456f26a5ce"],"state_sha256":"6435a52f5ddb71d91f4663be96614d1ebaf77d779f505ec8f7b0e75cfddc949e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lwzn3lnk0o3zrJ8Eysj7bhp+zVSlQ+KE51PHD8c5gwDGlrxGKy0tRAn0nMuXD9l4YOmSsuJu+35GQhO16qkQAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-01T21:48:33.674278Z","bundle_sha256":"4bbe20501c14d6ac98005a701e7671dd3b8ad44dcef2ebe78c12f701d1b483fa"}}