{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:V2FWEA6BNFMULRDV35YIM6HP55","short_pith_number":"pith:V2FWEA6B","canonical_record":{"source":{"id":"2303.02927","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-03-06T06:47:22Z","cross_cats_sorted":["cs.HC","cs.PL"],"title_canon_sha256":"0488dabd137c01f8a67a1ad5645d8c164292dfab500983fbcfa2c59607570769","abstract_canon_sha256":"4ca6469b697f0cad8a147136093d61eba997f3235c7fab00b2294260e6a5dfbd"},"schema_version":"1.0"},"canonical_sha256":"ae8b6203c1695945c475df708678efef4f3a65403a4b0e0c0224fbe701ff4114","source":{"kind":"arxiv","id":"2303.02927","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.02927","created_at":"2026-07-05T06:17:47Z"},{"alias_kind":"arxiv_version","alias_value":"2303.02927v3","created_at":"2026-07-05T06:17:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.02927","created_at":"2026-07-05T06:17:47Z"},{"alias_kind":"pith_short_12","alias_value":"V2FWEA6BNFMU","created_at":"2026-07-05T06:17:47Z"},{"alias_kind":"pith_short_16","alias_value":"V2FWEA6BNFMULRDV","created_at":"2026-07-05T06:17:47Z"},{"alias_kind":"pith_short_8","alias_value":"V2FWEA6B","created_at":"2026-07-05T06:17:47Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:V2FWEA6BNFMULRDV35YIM6HP55","target":"record","payload":{"canonical_record":{"source":{"id":"2303.02927","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-03-06T06:47:22Z","cross_cats_sorted":["cs.HC","cs.PL"],"title_canon_sha256":"0488dabd137c01f8a67a1ad5645d8c164292dfab500983fbcfa2c59607570769","abstract_canon_sha256":"4ca6469b697f0cad8a147136093d61eba997f3235c7fab00b2294260e6a5dfbd"},"schema_version":"1.0"},"canonical_sha256":"ae8b6203c1695945c475df708678efef4f3a65403a4b0e0c0224fbe701ff4114","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:17:47.400078Z","signature_b64":"EjkRBK0IWO5/0iwwK5JGslXB0/f49YdADQ3am0lJDl/9V46DdGKUM/cpJrdMI0WFeBdViSM2iSNusOmCO1lsCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ae8b6203c1695945c475df708678efef4f3a65403a4b0e0c0224fbe701ff4114","last_reissued_at":"2026-07-05T06:17:47.399606Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:17:47.399606Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2303.02927","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:17:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ktb9oB4NzHL69NElhqz4lPZwgBlnUqr8W8UVkE8vO4kFHhaFeZ1ukO1HXbsS+JVCIQFJ+iKG9M6vv6YvkZhcAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T18:01:42.922998Z"},"content_sha256":"13513dc4431c3c3d0e9d358f0c5b9568cc137a95f036065902dd63c3820f2a30","schema_version":"1.0","event_id":"sha256:13513dc4431c3c3d0e9d358f0c5b9568cc137a95f036065902dd63c3820f2a30"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:V2FWEA6BNFMULRDV35YIM6HP55","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.HC","cs.PL"],"primary_cat":"cs.AI","authors_text":"Victor Dibia","submitted_at":"2023-03-06T06:47:22Z","abstract_excerpt":"Systems that support users in the automatic creation of visualizations must address several subtasks - understand the semantics of data, enumerate relevant visualization goals and generate visualization specifications. In this work, we pose visualization generation as a multi-stage generation problem and argue that well-orchestrated pipelines based on large language models (LLMs) such as ChatGPT/GPT-4 and image generation models (IGMs) are suitable to addressing these tasks. We present LIDA, a novel tool for generating grammar-agnostic visualizations and infographics. LIDA comprises of 4 modul"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.02927","kind":"arxiv","version":3},"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/2303.02927/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":"2026-07-05T06:17:47Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MJQwSRMWmxk9d3873vSaDhF5nIneM5aU0ULdOKfm8D29JRmkL39SCZ7kn+LYWOG5X8580Fbwa/hZHo3GH+GVBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T18:01:42.923521Z"},"content_sha256":"39ec4637e24e01ca4ca2b232879478eb47d7fd74083b27b55deca0ff64ab622a","schema_version":"1.0","event_id":"sha256:39ec4637e24e01ca4ca2b232879478eb47d7fd74083b27b55deca0ff64ab622a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V2FWEA6BNFMULRDV35YIM6HP55/bundle.json","state_url":"https://pith.science/pith/V2FWEA6BNFMULRDV35YIM6HP55/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V2FWEA6BNFMULRDV35YIM6HP55/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":"2026-08-09T18:01:42Z","links":{"resolver":"https://pith.science/pith/V2FWEA6BNFMULRDV35YIM6HP55","bundle":"https://pith.science/pith/V2FWEA6BNFMULRDV35YIM6HP55/bundle.json","state":"https://pith.science/pith/V2FWEA6BNFMULRDV35YIM6HP55/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V2FWEA6BNFMULRDV35YIM6HP55/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:V2FWEA6BNFMULRDV35YIM6HP55","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":"4ca6469b697f0cad8a147136093d61eba997f3235c7fab00b2294260e6a5dfbd","cross_cats_sorted":["cs.HC","cs.PL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-03-06T06:47:22Z","title_canon_sha256":"0488dabd137c01f8a67a1ad5645d8c164292dfab500983fbcfa2c59607570769"},"schema_version":"1.0","source":{"id":"2303.02927","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.02927","created_at":"2026-07-05T06:17:47Z"},{"alias_kind":"arxiv_version","alias_value":"2303.02927v3","created_at":"2026-07-05T06:17:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.02927","created_at":"2026-07-05T06:17:47Z"},{"alias_kind":"pith_short_12","alias_value":"V2FWEA6BNFMU","created_at":"2026-07-05T06:17:47Z"},{"alias_kind":"pith_short_16","alias_value":"V2FWEA6BNFMULRDV","created_at":"2026-07-05T06:17:47Z"},{"alias_kind":"pith_short_8","alias_value":"V2FWEA6B","created_at":"2026-07-05T06:17:47Z"}],"graph_snapshots":[{"event_id":"sha256:39ec4637e24e01ca4ca2b232879478eb47d7fd74083b27b55deca0ff64ab622a","target":"graph","created_at":"2026-07-05T06:17:47Z","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/2303.02927/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Systems that support users in the automatic creation of visualizations must address several subtasks - understand the semantics of data, enumerate relevant visualization goals and generate visualization specifications. In this work, we pose visualization generation as a multi-stage generation problem and argue that well-orchestrated pipelines based on large language models (LLMs) such as ChatGPT/GPT-4 and image generation models (IGMs) are suitable to addressing these tasks. We present LIDA, a novel tool for generating grammar-agnostic visualizations and infographics. LIDA comprises of 4 modul","authors_text":"Victor Dibia","cross_cats":["cs.HC","cs.PL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-03-06T06:47:22Z","title":"LIDA: A Tool for Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.02927","kind":"arxiv","version":3},"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":"sha256:13513dc4431c3c3d0e9d358f0c5b9568cc137a95f036065902dd63c3820f2a30","target":"record","created_at":"2026-07-05T06:17:47Z","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":"4ca6469b697f0cad8a147136093d61eba997f3235c7fab00b2294260e6a5dfbd","cross_cats_sorted":["cs.HC","cs.PL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2023-03-06T06:47:22Z","title_canon_sha256":"0488dabd137c01f8a67a1ad5645d8c164292dfab500983fbcfa2c59607570769"},"schema_version":"1.0","source":{"id":"2303.02927","kind":"arxiv","version":3}},"canonical_sha256":"ae8b6203c1695945c475df708678efef4f3a65403a4b0e0c0224fbe701ff4114","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ae8b6203c1695945c475df708678efef4f3a65403a4b0e0c0224fbe701ff4114","first_computed_at":"2026-07-05T06:17:47.399606Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:17:47.399606Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EjkRBK0IWO5/0iwwK5JGslXB0/f49YdADQ3am0lJDl/9V46DdGKUM/cpJrdMI0WFeBdViSM2iSNusOmCO1lsCw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:17:47.400078Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.02927","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:13513dc4431c3c3d0e9d358f0c5b9568cc137a95f036065902dd63c3820f2a30","sha256:39ec4637e24e01ca4ca2b232879478eb47d7fd74083b27b55deca0ff64ab622a"],"state_sha256":"a505ac716e3013c0d0bca8b505bd354301436962f312fdd5d5f966e44e6ca78d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TOReGp83PfRZPPJl0KLKWt9ERbe+21kQuyTvic2Nmu0nAx2GVGN4Kpiw8e4GS57deUjBXmtg+8HTqJgR7GUeAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T18:01:42.929360Z","bundle_sha256":"df4233f66fa206d0cd7e0196295d8cd918dc77679af13a6fa5922e1e46ca65a1"}}