{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:X7BU7742FUKM6XNX4UG2RPDZDZ","short_pith_number":"pith:X7BU7742","canonical_record":{"source":{"id":"2407.10424","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.PL","submitted_at":"2024-07-15T03:57:20Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"66e64e08fc7002bc51c006fe85c2bbe3a1fceabaee970b4114338b480c948fce","abstract_canon_sha256":"9a99dfc1a58fc061358bea105782221d6026ef012a5c52d7f0d57e32ac1dccbc"},"schema_version":"1.0"},"canonical_sha256":"bfc34fff9a2d14cf5db7e50da8bc791e5a4b67a04bbc9333574898eb0ca378d5","source":{"kind":"arxiv","id":"2407.10424","version":5},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.10424","created_at":"2026-07-05T11:01:25Z"},{"alias_kind":"arxiv_version","alias_value":"2407.10424v5","created_at":"2026-07-05T11:01:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.10424","created_at":"2026-07-05T11:01:25Z"},{"alias_kind":"pith_short_12","alias_value":"X7BU7742FUKM","created_at":"2026-07-05T11:01:25Z"},{"alias_kind":"pith_short_16","alias_value":"X7BU7742FUKM6XNX","created_at":"2026-07-05T11:01:25Z"},{"alias_kind":"pith_short_8","alias_value":"X7BU7742","created_at":"2026-07-05T11:01:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:X7BU7742FUKM6XNX4UG2RPDZDZ","target":"record","payload":{"canonical_record":{"source":{"id":"2407.10424","kind":"arxiv","version":5},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.PL","submitted_at":"2024-07-15T03:57:20Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"66e64e08fc7002bc51c006fe85c2bbe3a1fceabaee970b4114338b480c948fce","abstract_canon_sha256":"9a99dfc1a58fc061358bea105782221d6026ef012a5c52d7f0d57e32ac1dccbc"},"schema_version":"1.0"},"canonical_sha256":"bfc34fff9a2d14cf5db7e50da8bc791e5a4b67a04bbc9333574898eb0ca378d5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:01:25.329336Z","signature_b64":"AWciQcweyBkrZUCwKq846WCS+y2PZS0aJj85h2ktIWBE34SMes4j6RQ7IW7LhJ65BQ4etQXHej+vjygJ2L22CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bfc34fff9a2d14cf5db7e50da8bc791e5a4b67a04bbc9333574898eb0ca378d5","last_reissued_at":"2026-07-05T11:01:25.328862Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:01:25.328862Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.10424","source_version":5,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:01:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/uvi3FGH7Dp6lICS0NwBDVARtaMb6cNcYhasPPUSsruftmQ1SLjD19pet9/Hb3jlUR5TnNxm/iF+DhSj0udYBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:42:38.810450Z"},"content_sha256":"f74576a8b0c3afd6167d1c69df8928d389426f4c20bad43c1a83a74504d9d918","schema_version":"1.0","event_id":"sha256:f74576a8b0c3afd6167d1c69df8928d389426f4c20bad43c1a83a74504d9d918"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:X7BU7742FUKM6XNX4UG2RPDZDZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CodeV: Empowering LLMs with HDL Generation through Multi-Level Summarization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.PL","authors_text":"Chongxiao Li, Di Huang, Lei Qi, Mingju Gao, Muxin Song, Pengwei Jin, Qi Guo, Rui Zhang, Tianyun Ma, Xing Hu, Xishan Zhang, Yang Zhao, Yansong Pan, Yinan Xu, Zhenxing Zhang, Zidong Du, Ziyuan Nan","submitted_at":"2024-07-15T03:57:20Z","abstract_excerpt":"The design flow of processors, particularly in hardware description languages (HDL) like Verilog and Chisel, is complex and costly. While recent advances in large language models (LLMs) have significantly improved coding tasks in software languages such as Python, their application in HDL generation remains limited due to the scarcity of high-quality HDL data. Traditional methods of adapting LLMs for hardware design rely on synthetic HDL datasets, which often suffer from low quality because even advanced LLMs like GPT perform poorly in the HDL domain. Moreover, these methods focus solely on ch"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.10424","kind":"arxiv","version":5},"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/2407.10424/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":"2026-07-05T11:01:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6QfuPk1+y/slE36Rkv2BmN3XcwwyqYec+XObNGv/yqjPVCoUn5ndVcl54cQZCXc00X7BjSKsJ6ILLPQFB4QUBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:42:38.810821Z"},"content_sha256":"e3892d1d5b6c48ce9900c5863735269e43bc138daa41e529df5309498cb522cc","schema_version":"1.0","event_id":"sha256:e3892d1d5b6c48ce9900c5863735269e43bc138daa41e529df5309498cb522cc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X7BU7742FUKM6XNX4UG2RPDZDZ/bundle.json","state_url":"https://pith.science/pith/X7BU7742FUKM6XNX4UG2RPDZDZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X7BU7742FUKM6XNX4UG2RPDZDZ/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":"2026-07-06T18:42:38Z","links":{"resolver":"https://pith.science/pith/X7BU7742FUKM6XNX4UG2RPDZDZ","bundle":"https://pith.science/pith/X7BU7742FUKM6XNX4UG2RPDZDZ/bundle.json","state":"https://pith.science/pith/X7BU7742FUKM6XNX4UG2RPDZDZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X7BU7742FUKM6XNX4UG2RPDZDZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:X7BU7742FUKM6XNX4UG2RPDZDZ","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":"9a99dfc1a58fc061358bea105782221d6026ef012a5c52d7f0d57e32ac1dccbc","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.PL","submitted_at":"2024-07-15T03:57:20Z","title_canon_sha256":"66e64e08fc7002bc51c006fe85c2bbe3a1fceabaee970b4114338b480c948fce"},"schema_version":"1.0","source":{"id":"2407.10424","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.10424","created_at":"2026-07-05T11:01:25Z"},{"alias_kind":"arxiv_version","alias_value":"2407.10424v5","created_at":"2026-07-05T11:01:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.10424","created_at":"2026-07-05T11:01:25Z"},{"alias_kind":"pith_short_12","alias_value":"X7BU7742FUKM","created_at":"2026-07-05T11:01:25Z"},{"alias_kind":"pith_short_16","alias_value":"X7BU7742FUKM6XNX","created_at":"2026-07-05T11:01:25Z"},{"alias_kind":"pith_short_8","alias_value":"X7BU7742","created_at":"2026-07-05T11:01:25Z"}],"graph_snapshots":[{"event_id":"sha256:e3892d1d5b6c48ce9900c5863735269e43bc138daa41e529df5309498cb522cc","target":"graph","created_at":"2026-07-05T11:01:25Z","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/2407.10424/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The design flow of processors, particularly in hardware description languages (HDL) like Verilog and Chisel, is complex and costly. While recent advances in large language models (LLMs) have significantly improved coding tasks in software languages such as Python, their application in HDL generation remains limited due to the scarcity of high-quality HDL data. Traditional methods of adapting LLMs for hardware design rely on synthetic HDL datasets, which often suffer from low quality because even advanced LLMs like GPT perform poorly in the HDL domain. Moreover, these methods focus solely on ch","authors_text":"Chongxiao Li, Di Huang, Lei Qi, Mingju Gao, Muxin Song, Pengwei Jin, Qi Guo, Rui Zhang, Tianyun Ma, Xing Hu, Xishan Zhang, Yang Zhao, Yansong Pan, Yinan Xu, Zhenxing Zhang, Zidong Du, Ziyuan Nan","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.PL","submitted_at":"2024-07-15T03:57:20Z","title":"CodeV: Empowering LLMs with HDL Generation through Multi-Level Summarization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.10424","kind":"arxiv","version":5},"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:f74576a8b0c3afd6167d1c69df8928d389426f4c20bad43c1a83a74504d9d918","target":"record","created_at":"2026-07-05T11:01:25Z","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":"9a99dfc1a58fc061358bea105782221d6026ef012a5c52d7f0d57e32ac1dccbc","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.PL","submitted_at":"2024-07-15T03:57:20Z","title_canon_sha256":"66e64e08fc7002bc51c006fe85c2bbe3a1fceabaee970b4114338b480c948fce"},"schema_version":"1.0","source":{"id":"2407.10424","kind":"arxiv","version":5}},"canonical_sha256":"bfc34fff9a2d14cf5db7e50da8bc791e5a4b67a04bbc9333574898eb0ca378d5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bfc34fff9a2d14cf5db7e50da8bc791e5a4b67a04bbc9333574898eb0ca378d5","first_computed_at":"2026-07-05T11:01:25.328862Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:01:25.328862Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AWciQcweyBkrZUCwKq846WCS+y2PZS0aJj85h2ktIWBE34SMes4j6RQ7IW7LhJ65BQ4etQXHej+vjygJ2L22CA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:01:25.329336Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.10424","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f74576a8b0c3afd6167d1c69df8928d389426f4c20bad43c1a83a74504d9d918","sha256:e3892d1d5b6c48ce9900c5863735269e43bc138daa41e529df5309498cb522cc"],"state_sha256":"d2589196cfb14d17d39e818f27ad345a565c51c9609846073ef33a725e86af68"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wlD0wy8SBILauLqh0dhJeUBAw2hcX6wVy7M4nbzBrxwm9SQcUOVXJk+ONmQ7XN6VdelMMF9B4s0aIE2AU0VDDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T18:42:38.812974Z","bundle_sha256":"c531339e57983a45c1737c871fa86ac7139648db4afee2c0f1111391af27534a"}}