{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:HZGLOBFSB7QDGGICCADFQPDIPR","short_pith_number":"pith:HZGLOBFS","canonical_record":{"source":{"id":"2406.13779","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-19T19:06:36Z","cross_cats_sorted":[],"title_canon_sha256":"5341cf44ab744a68686c1d51a4482a517548e0168fbdd787cf51a6cb97bf4b89","abstract_canon_sha256":"76bd21cd688371e6abb8104ccfece87a918ededc3dff876e60cfef1970f3ac18"},"schema_version":"1.0"},"canonical_sha256":"3e4cb704b20fe03319021006583c687c7bec4e3e1693dfa0b43cbd43054616e6","source":{"kind":"arxiv","id":"2406.13779","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.13779","created_at":"2026-07-05T08:38:38Z"},{"alias_kind":"arxiv_version","alias_value":"2406.13779v1","created_at":"2026-07-05T08:38:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.13779","created_at":"2026-07-05T08:38:38Z"},{"alias_kind":"pith_short_12","alias_value":"HZGLOBFSB7QD","created_at":"2026-07-05T08:38:38Z"},{"alias_kind":"pith_short_16","alias_value":"HZGLOBFSB7QDGGIC","created_at":"2026-07-05T08:38:38Z"},{"alias_kind":"pith_short_8","alias_value":"HZGLOBFS","created_at":"2026-07-05T08:38:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:HZGLOBFSB7QDGGICCADFQPDIPR","target":"record","payload":{"canonical_record":{"source":{"id":"2406.13779","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-19T19:06:36Z","cross_cats_sorted":[],"title_canon_sha256":"5341cf44ab744a68686c1d51a4482a517548e0168fbdd787cf51a6cb97bf4b89","abstract_canon_sha256":"76bd21cd688371e6abb8104ccfece87a918ededc3dff876e60cfef1970f3ac18"},"schema_version":"1.0"},"canonical_sha256":"3e4cb704b20fe03319021006583c687c7bec4e3e1693dfa0b43cbd43054616e6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:38:38.942057Z","signature_b64":"VT21gesqEwvmGFMIFaYp6FYmoxB12jyx8VOs0xIFS1u4wCv/kkN+6QhffFqmREWnvWjWL7v9/trgn6RT1Rq4Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3e4cb704b20fe03319021006583c687c7bec4e3e1693dfa0b43cbd43054616e6","last_reissued_at":"2026-07-05T08:38:38.941606Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:38:38.941606Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.13779","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":"2026-07-05T08:38:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eBS9p91ToR2xaTVmoNO9AxoZIvSKEjJY8NhZwyshiKeOe+lVQAC1VSXfsnuhGqmOn5ZU9uecRKChGM8MpkRDCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T23:15:12.613113Z"},"content_sha256":"bb73f1136d987cded81e2a79e0bbb8671b4db07c5959b8fbf9927425c787ec13","schema_version":"1.0","event_id":"sha256:bb73f1136d987cded81e2a79e0bbb8671b4db07c5959b8fbf9927425c787ec13"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:HZGLOBFSB7QDGGICCADFQPDIPR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answering","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jinjie Gu, Jiyan Jiang, Tao Sun, Tianchi Cai, Xierui Song, Yinger Zhang, Yunqi Xu, Zhiwen Tan","submitted_at":"2024-06-19T19:06:36Z","abstract_excerpt":"Retrieval Augmented Generation (RAG) has become prevalent in question-answering (QA) tasks due to its ability of utilizing search engine to enhance the quality of long-form question-answering (LFQA). Despite the emergence of various open source methods and web-enhanced commercial systems such as Bing Chat, two critical problems remain unsolved, i.e., the lack of factuality and clear logic in the generated long-form answers. In this paper, we remedy these issues via a systematic study on answer generation in web-enhanced LFQA. Specifically, we first propose a novel outline-enhanced generator to"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.13779","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/2406.13779/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":"2026-07-05T08:38:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5xEOxm9mprWXmkCqVqRv85KRCgFre9Z4EFNHWnovyG0bGdwI9ZnHXT2yUdVNdwyMmPCsEZtgYo0LYw5z9rcRAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T23:15:12.613499Z"},"content_sha256":"c1d3be52f5f0c093c615d409010ab0aaf02d77a08fff4594fed189a65abe4239","schema_version":"1.0","event_id":"sha256:c1d3be52f5f0c093c615d409010ab0aaf02d77a08fff4594fed189a65abe4239"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HZGLOBFSB7QDGGICCADFQPDIPR/bundle.json","state_url":"https://pith.science/pith/HZGLOBFSB7QDGGICCADFQPDIPR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HZGLOBFSB7QDGGICCADFQPDIPR/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":"2026-07-08T23:15:12Z","links":{"resolver":"https://pith.science/pith/HZGLOBFSB7QDGGICCADFQPDIPR","bundle":"https://pith.science/pith/HZGLOBFSB7QDGGICCADFQPDIPR/bundle.json","state":"https://pith.science/pith/HZGLOBFSB7QDGGICCADFQPDIPR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HZGLOBFSB7QDGGICCADFQPDIPR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HZGLOBFSB7QDGGICCADFQPDIPR","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":"76bd21cd688371e6abb8104ccfece87a918ededc3dff876e60cfef1970f3ac18","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-19T19:06:36Z","title_canon_sha256":"5341cf44ab744a68686c1d51a4482a517548e0168fbdd787cf51a6cb97bf4b89"},"schema_version":"1.0","source":{"id":"2406.13779","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.13779","created_at":"2026-07-05T08:38:38Z"},{"alias_kind":"arxiv_version","alias_value":"2406.13779v1","created_at":"2026-07-05T08:38:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.13779","created_at":"2026-07-05T08:38:38Z"},{"alias_kind":"pith_short_12","alias_value":"HZGLOBFSB7QD","created_at":"2026-07-05T08:38:38Z"},{"alias_kind":"pith_short_16","alias_value":"HZGLOBFSB7QDGGIC","created_at":"2026-07-05T08:38:38Z"},{"alias_kind":"pith_short_8","alias_value":"HZGLOBFS","created_at":"2026-07-05T08:38:38Z"}],"graph_snapshots":[{"event_id":"sha256:c1d3be52f5f0c093c615d409010ab0aaf02d77a08fff4594fed189a65abe4239","target":"graph","created_at":"2026-07-05T08:38:38Z","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/2406.13779/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Retrieval Augmented Generation (RAG) has become prevalent in question-answering (QA) tasks due to its ability of utilizing search engine to enhance the quality of long-form question-answering (LFQA). Despite the emergence of various open source methods and web-enhanced commercial systems such as Bing Chat, two critical problems remain unsolved, i.e., the lack of factuality and clear logic in the generated long-form answers. In this paper, we remedy these issues via a systematic study on answer generation in web-enhanced LFQA. Specifically, we first propose a novel outline-enhanced generator to","authors_text":"Jinjie Gu, Jiyan Jiang, Tao Sun, Tianchi Cai, Xierui Song, Yinger Zhang, Yunqi Xu, Zhiwen Tan","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-19T19:06:36Z","title":"FoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.13779","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:bb73f1136d987cded81e2a79e0bbb8671b4db07c5959b8fbf9927425c787ec13","target":"record","created_at":"2026-07-05T08:38:38Z","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":"76bd21cd688371e6abb8104ccfece87a918ededc3dff876e60cfef1970f3ac18","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-19T19:06:36Z","title_canon_sha256":"5341cf44ab744a68686c1d51a4482a517548e0168fbdd787cf51a6cb97bf4b89"},"schema_version":"1.0","source":{"id":"2406.13779","kind":"arxiv","version":1}},"canonical_sha256":"3e4cb704b20fe03319021006583c687c7bec4e3e1693dfa0b43cbd43054616e6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3e4cb704b20fe03319021006583c687c7bec4e3e1693dfa0b43cbd43054616e6","first_computed_at":"2026-07-05T08:38:38.941606Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:38:38.941606Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VT21gesqEwvmGFMIFaYp6FYmoxB12jyx8VOs0xIFS1u4wCv/kkN+6QhffFqmREWnvWjWL7v9/trgn6RT1Rq4Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:38:38.942057Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.13779","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bb73f1136d987cded81e2a79e0bbb8671b4db07c5959b8fbf9927425c787ec13","sha256:c1d3be52f5f0c093c615d409010ab0aaf02d77a08fff4594fed189a65abe4239"],"state_sha256":"acb39d65c43ec8388f0404ddeefc8f11917fa241ff7d29ea7e13a9c718e3fa5f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E3n0HvYLCWYdxdsWKsgf8S91WdIOv2RQwdhjetzbd1pNOLnpggIojbDIXB290spUk4Z/5LKgDrSV9geY6hctAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T23:15:12.615609Z","bundle_sha256":"3340afc1ff313a94b3276dfd3cec787252a0ea8f9f852de2007415e1f33cf73f"}}