{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:WIV766GY2WCAKAKKSMO7LHTPH4","short_pith_number":"pith:WIV766GY","canonical_record":{"source":{"id":"2308.08520","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-08-16T17:18:30Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e03b044778c90050f6f6aaef11233576ed7c4b1d3af8d9ef0634ad2bd1d348e0","abstract_canon_sha256":"737f5b5b3a1b44c4fc50081e6a2c5346b6b0a8acffff8c2d8cd5c39b388d7aa2"},"schema_version":"1.0"},"canonical_sha256":"b22bff78d8d58405014a931df59e6f3f09cc19c1178b736bb99612fbe799372c","source":{"kind":"arxiv","id":"2308.08520","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.08520","created_at":"2026-07-05T06:42:00Z"},{"alias_kind":"arxiv_version","alias_value":"2308.08520v1","created_at":"2026-07-05T06:42:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.08520","created_at":"2026-07-05T06:42:00Z"},{"alias_kind":"pith_short_12","alias_value":"WIV766GY2WCA","created_at":"2026-07-05T06:42:00Z"},{"alias_kind":"pith_short_16","alias_value":"WIV766GY2WCAKAKK","created_at":"2026-07-05T06:42:00Z"},{"alias_kind":"pith_short_8","alias_value":"WIV766GY","created_at":"2026-07-05T06:42:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:WIV766GY2WCAKAKKSMO7LHTPH4","target":"record","payload":{"canonical_record":{"source":{"id":"2308.08520","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-08-16T17:18:30Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e03b044778c90050f6f6aaef11233576ed7c4b1d3af8d9ef0634ad2bd1d348e0","abstract_canon_sha256":"737f5b5b3a1b44c4fc50081e6a2c5346b6b0a8acffff8c2d8cd5c39b388d7aa2"},"schema_version":"1.0"},"canonical_sha256":"b22bff78d8d58405014a931df59e6f3f09cc19c1178b736bb99612fbe799372c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:42:00.272004Z","signature_b64":"8F8YCvN0aM9zHnVLqvIBA1helI1OcphtNpzT/8XRB7Ar1QotSa7TZ9BzA0rBkdOHiIAVBKPPDDsRrjMD2buSBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b22bff78d8d58405014a931df59e6f3f09cc19c1178b736bb99612fbe799372c","last_reissued_at":"2026-07-05T06:42:00.271532Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:42:00.271532Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.08520","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":"2026-07-05T06:42:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JE0bPeGLhFgNKp7Jz6LJkQ1xF9BgNIGIIabO3WvYVwsf0mQTl9CsWn8Sy5N8nQnoXuObR9Gy7rphJ7BybcvsAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T09:48:10.871757Z"},"content_sha256":"2c604f19127a7e0d3a1e5ee2f3d0230f62b8e5460b4acdb155585a6df40b88d2","schema_version":"1.0","event_id":"sha256:2c604f19127a7e0d3a1e5ee2f3d0230f62b8e5460b4acdb155585a6df40b88d2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:WIV766GY2WCAKAKKSMO7LHTPH4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Painter: Teaching Auto-regressive Language Models to Draw Sketches","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Apratim Bhattacharyya, Mingu Lee, Pulkit Madan, Reza Pourreza, Roland Memisevic, Sunny Panchal","submitted_at":"2023-08-16T17:18:30Z","abstract_excerpt":"Large language models (LLMs) have made tremendous progress in natural language understanding and they have also been successfully adopted in other domains such as computer vision, robotics, reinforcement learning, etc. In this work, we apply LLMs to image generation tasks by directly generating the virtual brush strokes to paint an image. We present Painter, an LLM that can convert user prompts in text description format to sketches by generating the corresponding brush strokes in an auto-regressive way. We construct Painter based on off-the-shelf LLM that is pre-trained on a large text corpus"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.08520","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/2308.08520/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":"2026-07-05T06:42:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sNwr6w7wzAbciMrwxYeJuPyClR9zIvjb948hkaVW06Y2cD0Ojb8TLhQuMnnSit/xqRTy2vrHDRXGl2nhG1pGAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T09:48:10.872254Z"},"content_sha256":"65dd0927bb93be9f2c815c81611f9a45b3f6801d33d58a40b02abe7cf2c2abb4","schema_version":"1.0","event_id":"sha256:65dd0927bb93be9f2c815c81611f9a45b3f6801d33d58a40b02abe7cf2c2abb4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WIV766GY2WCAKAKKSMO7LHTPH4/bundle.json","state_url":"https://pith.science/pith/WIV766GY2WCAKAKKSMO7LHTPH4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WIV766GY2WCAKAKKSMO7LHTPH4/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":"2026-08-10T09:48:10Z","links":{"resolver":"https://pith.science/pith/WIV766GY2WCAKAKKSMO7LHTPH4","bundle":"https://pith.science/pith/WIV766GY2WCAKAKKSMO7LHTPH4/bundle.json","state":"https://pith.science/pith/WIV766GY2WCAKAKKSMO7LHTPH4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WIV766GY2WCAKAKKSMO7LHTPH4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:WIV766GY2WCAKAKKSMO7LHTPH4","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":"737f5b5b3a1b44c4fc50081e6a2c5346b6b0a8acffff8c2d8cd5c39b388d7aa2","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-08-16T17:18:30Z","title_canon_sha256":"e03b044778c90050f6f6aaef11233576ed7c4b1d3af8d9ef0634ad2bd1d348e0"},"schema_version":"1.0","source":{"id":"2308.08520","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.08520","created_at":"2026-07-05T06:42:00Z"},{"alias_kind":"arxiv_version","alias_value":"2308.08520v1","created_at":"2026-07-05T06:42:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.08520","created_at":"2026-07-05T06:42:00Z"},{"alias_kind":"pith_short_12","alias_value":"WIV766GY2WCA","created_at":"2026-07-05T06:42:00Z"},{"alias_kind":"pith_short_16","alias_value":"WIV766GY2WCAKAKK","created_at":"2026-07-05T06:42:00Z"},{"alias_kind":"pith_short_8","alias_value":"WIV766GY","created_at":"2026-07-05T06:42:00Z"}],"graph_snapshots":[{"event_id":"sha256:65dd0927bb93be9f2c815c81611f9a45b3f6801d33d58a40b02abe7cf2c2abb4","target":"graph","created_at":"2026-07-05T06:42:00Z","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/2308.08520/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) have made tremendous progress in natural language understanding and they have also been successfully adopted in other domains such as computer vision, robotics, reinforcement learning, etc. In this work, we apply LLMs to image generation tasks by directly generating the virtual brush strokes to paint an image. We present Painter, an LLM that can convert user prompts in text description format to sketches by generating the corresponding brush strokes in an auto-regressive way. We construct Painter based on off-the-shelf LLM that is pre-trained on a large text corpus","authors_text":"Apratim Bhattacharyya, Mingu Lee, Pulkit Madan, Reza Pourreza, Roland Memisevic, Sunny Panchal","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-08-16T17:18:30Z","title":"Painter: Teaching Auto-regressive Language Models to Draw Sketches"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.08520","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":"sha256:2c604f19127a7e0d3a1e5ee2f3d0230f62b8e5460b4acdb155585a6df40b88d2","target":"record","created_at":"2026-07-05T06:42:00Z","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":"737f5b5b3a1b44c4fc50081e6a2c5346b6b0a8acffff8c2d8cd5c39b388d7aa2","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-08-16T17:18:30Z","title_canon_sha256":"e03b044778c90050f6f6aaef11233576ed7c4b1d3af8d9ef0634ad2bd1d348e0"},"schema_version":"1.0","source":{"id":"2308.08520","kind":"arxiv","version":1}},"canonical_sha256":"b22bff78d8d58405014a931df59e6f3f09cc19c1178b736bb99612fbe799372c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b22bff78d8d58405014a931df59e6f3f09cc19c1178b736bb99612fbe799372c","first_computed_at":"2026-07-05T06:42:00.271532Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:42:00.271532Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8F8YCvN0aM9zHnVLqvIBA1helI1OcphtNpzT/8XRB7Ar1QotSa7TZ9BzA0rBkdOHiIAVBKPPDDsRrjMD2buSBA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:42:00.272004Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.08520","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2c604f19127a7e0d3a1e5ee2f3d0230f62b8e5460b4acdb155585a6df40b88d2","sha256:65dd0927bb93be9f2c815c81611f9a45b3f6801d33d58a40b02abe7cf2c2abb4"],"state_sha256":"32592f4bbd5758ea0756128c5828142135f58b84f7bfa0110e867ae89bab5978"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TyAPEILfkcIuJx99xT2aBreshCmtPR36mK4VzyL7yPMjYpcmv3kjnGXKZsB1O/tB4LlwCd5TciybOwxdUa3YAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T09:48:10.878233Z","bundle_sha256":"63f5fdd8884c479b6d2a488e83c8dff8874fb214a21def902938a07f9b8afd19"}}