{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:GNWLQJ73H2D3SIDFF22VP6DTRF","short_pith_number":"pith:GNWLQJ73","canonical_record":{"source":{"id":"2410.02637","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-03T16:23:13Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"68b609c319a624f93e2152f89ab125d0145c9c2c88ac0f26269f5719ef0e284b","abstract_canon_sha256":"6321df6a5879e39b1d21085ee500f0760563596be06f8913d9387530e45015ad"},"schema_version":"1.0"},"canonical_sha256":"336cb827fb3e87b920652eb557f873894ba77695be39deca7817cd866e658ef1","source":{"kind":"arxiv","id":"2410.02637","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.02637","created_at":"2026-07-05T09:41:42Z"},{"alias_kind":"arxiv_version","alias_value":"2410.02637v2","created_at":"2026-07-05T09:41:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.02637","created_at":"2026-07-05T09:41:42Z"},{"alias_kind":"pith_short_12","alias_value":"GNWLQJ73H2D3","created_at":"2026-07-05T09:41:42Z"},{"alias_kind":"pith_short_16","alias_value":"GNWLQJ73H2D3SIDF","created_at":"2026-07-05T09:41:42Z"},{"alias_kind":"pith_short_8","alias_value":"GNWLQJ73","created_at":"2026-07-05T09:41:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:GNWLQJ73H2D3SIDFF22VP6DTRF","target":"record","payload":{"canonical_record":{"source":{"id":"2410.02637","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-03T16:23:13Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"68b609c319a624f93e2152f89ab125d0145c9c2c88ac0f26269f5719ef0e284b","abstract_canon_sha256":"6321df6a5879e39b1d21085ee500f0760563596be06f8913d9387530e45015ad"},"schema_version":"1.0"},"canonical_sha256":"336cb827fb3e87b920652eb557f873894ba77695be39deca7817cd866e658ef1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:41:42.788586Z","signature_b64":"VagN6oZE2mlgxC9VNOUiimQALyB+He9n9xhReqXnkBz0np3G+3TzNGhc8Zz6DKLs4UJsBzLllA2tEBBJXkNODg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"336cb827fb3e87b920652eb557f873894ba77695be39deca7817cd866e658ef1","last_reissued_at":"2026-07-05T09:41:42.788084Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:41:42.788084Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.02637","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":"2026-07-05T09:41:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zTSbl/fvzQ6nuMN2g5Rhzik5SH3vy4I3QhMka40bnVkIoNmYlpYWVKSvNkebqQZsj6OrkpinSxM7X2WhUXOxDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-17T14:07:07.961417Z"},"content_sha256":"d1b3208fa42dde3e7e11a50f0d1e8804a47a88e04325c7b6dee59b841d104521","schema_version":"1.0","event_id":"sha256:d1b3208fa42dde3e7e11a50f0d1e8804a47a88e04325c7b6dee59b841d104521"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:GNWLQJ73H2D3SIDFF22VP6DTRF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Plots Unlock Time-Series Understanding in Multimodal Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.AI","authors_text":"Desislav Ivanov, Eva Schnider, Gabriela Botea, Jing Tang, Kay Lamerigts, Marc Wilson, Mathias M.J. Bellaiche, Mayank Daswani, Michael A. Sanchez, Mikhail Papkov, Shravya Shetty, Shruthi Prabhakara, Umesh Telang, Yojan Patel","submitted_at":"2024-10-03T16:23:13Z","abstract_excerpt":"While multimodal foundation models can now natively work with data beyond text, they remain underutilized in analyzing the considerable amounts of multi-dimensional time-series data in fields like healthcare, finance, and social sciences, representing a missed opportunity for richer, data-driven insights. This paper proposes a simple but effective method that leverages the existing vision encoders of these models to \"see\" time-series data via plots, avoiding the need for additional, potentially costly, model training. Our empirical evaluations show that this approach outperforms providing the "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.02637","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/2410.02637/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":"2026-07-05T09:41:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wAI/rjVIzUP93nXFZMV15XO2pl7AHmxub0vHkf8a8xq5ibeF7xiLvg26D+VGlzHeJ1Og2bKye/2zhKmp7v//Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-17T14:07:07.961819Z"},"content_sha256":"92e9dc18861f9102c24b64b26a530ae44cad0f0b18390a6d97bb1cbff175e8da","schema_version":"1.0","event_id":"sha256:92e9dc18861f9102c24b64b26a530ae44cad0f0b18390a6d97bb1cbff175e8da"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GNWLQJ73H2D3SIDFF22VP6DTRF/bundle.json","state_url":"https://pith.science/pith/GNWLQJ73H2D3SIDFF22VP6DTRF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GNWLQJ73H2D3SIDFF22VP6DTRF/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":"2026-07-17T14:07:07Z","links":{"resolver":"https://pith.science/pith/GNWLQJ73H2D3SIDFF22VP6DTRF","bundle":"https://pith.science/pith/GNWLQJ73H2D3SIDFF22VP6DTRF/bundle.json","state":"https://pith.science/pith/GNWLQJ73H2D3SIDFF22VP6DTRF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GNWLQJ73H2D3SIDFF22VP6DTRF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GNWLQJ73H2D3SIDFF22VP6DTRF","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":"6321df6a5879e39b1d21085ee500f0760563596be06f8913d9387530e45015ad","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-03T16:23:13Z","title_canon_sha256":"68b609c319a624f93e2152f89ab125d0145c9c2c88ac0f26269f5719ef0e284b"},"schema_version":"1.0","source":{"id":"2410.02637","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.02637","created_at":"2026-07-05T09:41:42Z"},{"alias_kind":"arxiv_version","alias_value":"2410.02637v2","created_at":"2026-07-05T09:41:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.02637","created_at":"2026-07-05T09:41:42Z"},{"alias_kind":"pith_short_12","alias_value":"GNWLQJ73H2D3","created_at":"2026-07-05T09:41:42Z"},{"alias_kind":"pith_short_16","alias_value":"GNWLQJ73H2D3SIDF","created_at":"2026-07-05T09:41:42Z"},{"alias_kind":"pith_short_8","alias_value":"GNWLQJ73","created_at":"2026-07-05T09:41:42Z"}],"graph_snapshots":[{"event_id":"sha256:92e9dc18861f9102c24b64b26a530ae44cad0f0b18390a6d97bb1cbff175e8da","target":"graph","created_at":"2026-07-05T09:41:42Z","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/2410.02637/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"While multimodal foundation models can now natively work with data beyond text, they remain underutilized in analyzing the considerable amounts of multi-dimensional time-series data in fields like healthcare, finance, and social sciences, representing a missed opportunity for richer, data-driven insights. This paper proposes a simple but effective method that leverages the existing vision encoders of these models to \"see\" time-series data via plots, avoiding the need for additional, potentially costly, model training. Our empirical evaluations show that this approach outperforms providing the ","authors_text":"Desislav Ivanov, Eva Schnider, Gabriela Botea, Jing Tang, Kay Lamerigts, Marc Wilson, Mathias M.J. Bellaiche, Mayank Daswani, Michael A. Sanchez, Mikhail Papkov, Shravya Shetty, Shruthi Prabhakara, Umesh Telang, Yojan Patel","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-03T16:23:13Z","title":"Plots Unlock Time-Series Understanding in Multimodal Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.02637","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:d1b3208fa42dde3e7e11a50f0d1e8804a47a88e04325c7b6dee59b841d104521","target":"record","created_at":"2026-07-05T09:41:42Z","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":"6321df6a5879e39b1d21085ee500f0760563596be06f8913d9387530e45015ad","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-03T16:23:13Z","title_canon_sha256":"68b609c319a624f93e2152f89ab125d0145c9c2c88ac0f26269f5719ef0e284b"},"schema_version":"1.0","source":{"id":"2410.02637","kind":"arxiv","version":2}},"canonical_sha256":"336cb827fb3e87b920652eb557f873894ba77695be39deca7817cd866e658ef1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"336cb827fb3e87b920652eb557f873894ba77695be39deca7817cd866e658ef1","first_computed_at":"2026-07-05T09:41:42.788084Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:41:42.788084Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VagN6oZE2mlgxC9VNOUiimQALyB+He9n9xhReqXnkBz0np3G+3TzNGhc8Zz6DKLs4UJsBzLllA2tEBBJXkNODg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:41:42.788586Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.02637","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d1b3208fa42dde3e7e11a50f0d1e8804a47a88e04325c7b6dee59b841d104521","sha256:92e9dc18861f9102c24b64b26a530ae44cad0f0b18390a6d97bb1cbff175e8da"],"state_sha256":"00105c405fbcaa32f6ff632193676a43fba0a54629313ebca5a72be64f4637e7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EU+TfO0s1qf+3BcxBKjg37uYKFfctPMlK2mYR65khIDB/RzsjyCbFRBHirjUhtFROlMFAI02MDXYbbuuZ7IoCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-17T14:07:07.963817Z","bundle_sha256":"ec9e59e8bbc4587b26954e54111ccc25f228d89ca3e020deda3de67e0f011112"}}