{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:D2LJQVO2J7S2A7DNWCVEPQM6MT","short_pith_number":"pith:D2LJQVO2","canonical_record":{"source":{"id":"2304.11384","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2023-04-22T12:26:24Z","cross_cats_sorted":[],"title_canon_sha256":"1fd6859061a74c47993f56d53ab65dbb1c69438e880f797dffc85542c7a4d7e3","abstract_canon_sha256":"5fbcf5b11574df351d4d793e0ae86a51b0eaa2b724247011aa50133ded084c82"},"schema_version":"1.0"},"canonical_sha256":"1e969855da4fe5a07c6db0aa47c19e64f2dd1fc64ee2344e8db15f229ab65568","source":{"kind":"arxiv","id":"2304.11384","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.11384","created_at":"2026-07-05T06:20:43Z"},{"alias_kind":"arxiv_version","alias_value":"2304.11384v3","created_at":"2026-07-05T06:20:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.11384","created_at":"2026-07-05T06:20:43Z"},{"alias_kind":"pith_short_12","alias_value":"D2LJQVO2J7S2","created_at":"2026-07-05T06:20:43Z"},{"alias_kind":"pith_short_16","alias_value":"D2LJQVO2J7S2A7DN","created_at":"2026-07-05T06:20:43Z"},{"alias_kind":"pith_short_8","alias_value":"D2LJQVO2","created_at":"2026-07-05T06:20:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:D2LJQVO2J7S2A7DNWCVEPQM6MT","target":"record","payload":{"canonical_record":{"source":{"id":"2304.11384","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2023-04-22T12:26:24Z","cross_cats_sorted":[],"title_canon_sha256":"1fd6859061a74c47993f56d53ab65dbb1c69438e880f797dffc85542c7a4d7e3","abstract_canon_sha256":"5fbcf5b11574df351d4d793e0ae86a51b0eaa2b724247011aa50133ded084c82"},"schema_version":"1.0"},"canonical_sha256":"1e969855da4fe5a07c6db0aa47c19e64f2dd1fc64ee2344e8db15f229ab65568","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:20:43.244243Z","signature_b64":"YEIFKBgSuHynuFvdQjzkf2ZL8k8vcOKcBJxz89NgpKZPs1QEVeMBpXjHt8jeUjJdOzZtX+0Ghglc8Phujs4UDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1e969855da4fe5a07c6db0aa47c19e64f2dd1fc64ee2344e8db15f229ab65568","last_reissued_at":"2026-07-05T06:20:43.243763Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:20:43.243763Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.11384","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":"2026-07-05T06:20:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e4DOT2gbVcThjRNk58eflDiZpODgKZuq8mnfKuvKcH4ZoFhe4J08rePE78ON0vBXKd8VbfDSlda6ZeT/9SLYDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:26:32.463106Z"},"content_sha256":"423e36115729c2394d687ee13db90d2c35f8aea711fc6614492e9fefaa4dc20c","schema_version":"1.0","event_id":"sha256:423e36115729c2394d687ee13db90d2c35f8aea711fc6614492e9fefaa4dc20c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:D2LJQVO2J7S2A7DNWCVEPQM6MT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Large Language Models are Few-Shot Summarizers: Multi-Intent Comment Generation via In-Context Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.SE","authors_text":"Dezun Dong, Ge Li, Haotian Wang, Mingyang Geng, Shangwen Wang, Xiangke Liao, Xiaoguang Mao, Zhi Jin","submitted_at":"2023-04-22T12:26:24Z","abstract_excerpt":"Code comment generation aims at generating natural language descriptions for a code snippet to facilitate developers' program comprehension activities. Despite being studied for a long time, a bottleneck for existing approaches is that given a code snippet, they can only generate one comment while developers usually need to know information from diverse perspectives such as what is the functionality of this code snippet and how to use it. To tackle this limitation, this study empirically investigates the feasibility of utilizing large language models (LLMs) to generate comments that can fulfil"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.11384","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/2304.11384/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":"2026-07-05T06:20:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ff40Kl8OV3EOhIMZ9nfw00Tf4IpluNtLEZVm4KLfTONHg2WLlCi3GuR1G368QMHS59udZaUdAhknMDd/GnogBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:26:32.463589Z"},"content_sha256":"8d1659740ea9d26119f64914b72b9b1d16766be503e24177ee9662238cd8377c","schema_version":"1.0","event_id":"sha256:8d1659740ea9d26119f64914b72b9b1d16766be503e24177ee9662238cd8377c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/D2LJQVO2J7S2A7DNWCVEPQM6MT/bundle.json","state_url":"https://pith.science/pith/D2LJQVO2J7S2A7DNWCVEPQM6MT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/D2LJQVO2J7S2A7DNWCVEPQM6MT/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":"2026-08-08T20:26:32Z","links":{"resolver":"https://pith.science/pith/D2LJQVO2J7S2A7DNWCVEPQM6MT","bundle":"https://pith.science/pith/D2LJQVO2J7S2A7DNWCVEPQM6MT/bundle.json","state":"https://pith.science/pith/D2LJQVO2J7S2A7DNWCVEPQM6MT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/D2LJQVO2J7S2A7DNWCVEPQM6MT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:D2LJQVO2J7S2A7DNWCVEPQM6MT","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":"5fbcf5b11574df351d4d793e0ae86a51b0eaa2b724247011aa50133ded084c82","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2023-04-22T12:26:24Z","title_canon_sha256":"1fd6859061a74c47993f56d53ab65dbb1c69438e880f797dffc85542c7a4d7e3"},"schema_version":"1.0","source":{"id":"2304.11384","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.11384","created_at":"2026-07-05T06:20:43Z"},{"alias_kind":"arxiv_version","alias_value":"2304.11384v3","created_at":"2026-07-05T06:20:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.11384","created_at":"2026-07-05T06:20:43Z"},{"alias_kind":"pith_short_12","alias_value":"D2LJQVO2J7S2","created_at":"2026-07-05T06:20:43Z"},{"alias_kind":"pith_short_16","alias_value":"D2LJQVO2J7S2A7DN","created_at":"2026-07-05T06:20:43Z"},{"alias_kind":"pith_short_8","alias_value":"D2LJQVO2","created_at":"2026-07-05T06:20:43Z"}],"graph_snapshots":[{"event_id":"sha256:8d1659740ea9d26119f64914b72b9b1d16766be503e24177ee9662238cd8377c","target":"graph","created_at":"2026-07-05T06:20:43Z","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/2304.11384/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Code comment generation aims at generating natural language descriptions for a code snippet to facilitate developers' program comprehension activities. Despite being studied for a long time, a bottleneck for existing approaches is that given a code snippet, they can only generate one comment while developers usually need to know information from diverse perspectives such as what is the functionality of this code snippet and how to use it. To tackle this limitation, this study empirically investigates the feasibility of utilizing large language models (LLMs) to generate comments that can fulfil","authors_text":"Dezun Dong, Ge Li, Haotian Wang, Mingyang Geng, Shangwen Wang, Xiangke Liao, Xiaoguang Mao, Zhi Jin","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2023-04-22T12:26:24Z","title":"Large Language Models are Few-Shot Summarizers: Multi-Intent Comment Generation via In-Context Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.11384","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":"sha256:423e36115729c2394d687ee13db90d2c35f8aea711fc6614492e9fefaa4dc20c","target":"record","created_at":"2026-07-05T06:20:43Z","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":"5fbcf5b11574df351d4d793e0ae86a51b0eaa2b724247011aa50133ded084c82","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.SE","submitted_at":"2023-04-22T12:26:24Z","title_canon_sha256":"1fd6859061a74c47993f56d53ab65dbb1c69438e880f797dffc85542c7a4d7e3"},"schema_version":"1.0","source":{"id":"2304.11384","kind":"arxiv","version":3}},"canonical_sha256":"1e969855da4fe5a07c6db0aa47c19e64f2dd1fc64ee2344e8db15f229ab65568","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1e969855da4fe5a07c6db0aa47c19e64f2dd1fc64ee2344e8db15f229ab65568","first_computed_at":"2026-07-05T06:20:43.243763Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:20:43.243763Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YEIFKBgSuHynuFvdQjzkf2ZL8k8vcOKcBJxz89NgpKZPs1QEVeMBpXjHt8jeUjJdOzZtX+0Ghglc8Phujs4UDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:20:43.244243Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.11384","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:423e36115729c2394d687ee13db90d2c35f8aea711fc6614492e9fefaa4dc20c","sha256:8d1659740ea9d26119f64914b72b9b1d16766be503e24177ee9662238cd8377c"],"state_sha256":"09998c9838218ff0e0e22ce62dfb3c3a379f8d842fb94b374d3830ad51324289"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dz09tIHqy/vsgAPFBgrfnmvUrAM07C1huSRt7GMNMO5EHrLMh6iCsbDMv5QgKPTC9PTM4uBL5j6TI+waXfR6BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T20:26:32.468028Z","bundle_sha256":"0dff4d1263078bebf23e2540cb98562a613eaa1881bc00626fbd3b12b4fd1395"}}