{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:BPSD32PZN3HGE5NCE6UBJ5X2MK","short_pith_number":"pith:BPSD32PZ","canonical_record":{"source":{"id":"2411.07870","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-12T15:26:17Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c280b55c94528ac6273e8146375511d520918befe985d4cf437f77e1fbec7f9b","abstract_canon_sha256":"1db0f69ca056359f6843384e49754fb5d63e06aabd58d0032c5f35dd84a11b77"},"schema_version":"1.0"},"canonical_sha256":"0be43de9f96ece6275a227a814f6fa62b3491717391d80feaf35b83f660c0b30","source":{"kind":"arxiv","id":"2411.07870","version":6},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.07870","created_at":"2026-07-05T09:52:18Z"},{"alias_kind":"arxiv_version","alias_value":"2411.07870v6","created_at":"2026-07-05T09:52:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.07870","created_at":"2026-07-05T09:52:18Z"},{"alias_kind":"pith_short_12","alias_value":"BPSD32PZN3HG","created_at":"2026-07-05T09:52:18Z"},{"alias_kind":"pith_short_16","alias_value":"BPSD32PZN3HGE5NC","created_at":"2026-07-05T09:52:18Z"},{"alias_kind":"pith_short_8","alias_value":"BPSD32PZ","created_at":"2026-07-05T09:52:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:BPSD32PZN3HGE5NCE6UBJ5X2MK","target":"record","payload":{"canonical_record":{"source":{"id":"2411.07870","kind":"arxiv","version":6},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-12T15:26:17Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c280b55c94528ac6273e8146375511d520918befe985d4cf437f77e1fbec7f9b","abstract_canon_sha256":"1db0f69ca056359f6843384e49754fb5d63e06aabd58d0032c5f35dd84a11b77"},"schema_version":"1.0"},"canonical_sha256":"0be43de9f96ece6275a227a814f6fa62b3491717391d80feaf35b83f660c0b30","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:52:18.034065Z","signature_b64":"0x6h/e7RHXDGvylXmWCA48bUEWmpcOautdpiIaViU/A/DEHf09jYH7CyJqKM0FM22w46dUhqDQZmN6OnrENrBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0be43de9f96ece6275a227a814f6fa62b3491717391d80feaf35b83f660c0b30","last_reissued_at":"2026-07-05T09:52:18.033048Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:52:18.033048Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.07870","source_version":6,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:52:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"32udOCDr6hii3mZiw9B8s40NDNYDfX5ZAKqTU6l/fRJOT7jcP0kdJizlPrEM5UL7ihXkHgaeFsjMDgXZek6/Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:13:18.670651Z"},"content_sha256":"91222220b18a1685854f88d8c5ae36c90e9766e55c0b3a39122d3a844c6089ce","schema_version":"1.0","event_id":"sha256:91222220b18a1685854f88d8c5ae36c90e9766e55c0b3a39122d3a844c6089ce"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:BPSD32PZN3HGE5NCE6UBJ5X2MK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Trustful LLMs: Customizing and Grounding Text Generation with Knowledge Bases and Dual Decoders","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Jaya Krishna Mandivarapu, Xiaofeng Zhu","submitted_at":"2024-11-12T15:26:17Z","abstract_excerpt":"Although people are impressed by the content generation skills of large language models, the use of LLMs, such as ChatGPT, is limited by the domain grounding of the content. The correctness and groundedness of the generated content need to be based on a verified context, such as results from Retrieval-Augmented Generation (RAG). One important issue when adapting LLMs to a customized domain is that the generated responses are often incomplete, or the additions are not verified and may even be hallucinated. Prior studies on hallucination detection have focused on evaluation metrics, which are no"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.07870","kind":"arxiv","version":6},"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/2411.07870/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":"2026-07-05T09:52:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"u28VR/2H0bh+ijHdwJM3/xFGLoNNpGZJlsXKp/pFbmxRkFJ3DR18ABF2AfKhkW2nClh7iBcIh8dMcVzbVBtcCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:13:18.671046Z"},"content_sha256":"f117d39a689b3be5b2dc4e6a054cc573e7de13d3e888f46e4a8bd5225a9dce67","schema_version":"1.0","event_id":"sha256:f117d39a689b3be5b2dc4e6a054cc573e7de13d3e888f46e4a8bd5225a9dce67"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BPSD32PZN3HGE5NCE6UBJ5X2MK/bundle.json","state_url":"https://pith.science/pith/BPSD32PZN3HGE5NCE6UBJ5X2MK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BPSD32PZN3HGE5NCE6UBJ5X2MK/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":"2026-07-07T04:13:18Z","links":{"resolver":"https://pith.science/pith/BPSD32PZN3HGE5NCE6UBJ5X2MK","bundle":"https://pith.science/pith/BPSD32PZN3HGE5NCE6UBJ5X2MK/bundle.json","state":"https://pith.science/pith/BPSD32PZN3HGE5NCE6UBJ5X2MK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BPSD32PZN3HGE5NCE6UBJ5X2MK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:BPSD32PZN3HGE5NCE6UBJ5X2MK","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":"1db0f69ca056359f6843384e49754fb5d63e06aabd58d0032c5f35dd84a11b77","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-12T15:26:17Z","title_canon_sha256":"c280b55c94528ac6273e8146375511d520918befe985d4cf437f77e1fbec7f9b"},"schema_version":"1.0","source":{"id":"2411.07870","kind":"arxiv","version":6}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.07870","created_at":"2026-07-05T09:52:18Z"},{"alias_kind":"arxiv_version","alias_value":"2411.07870v6","created_at":"2026-07-05T09:52:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.07870","created_at":"2026-07-05T09:52:18Z"},{"alias_kind":"pith_short_12","alias_value":"BPSD32PZN3HG","created_at":"2026-07-05T09:52:18Z"},{"alias_kind":"pith_short_16","alias_value":"BPSD32PZN3HGE5NC","created_at":"2026-07-05T09:52:18Z"},{"alias_kind":"pith_short_8","alias_value":"BPSD32PZ","created_at":"2026-07-05T09:52:18Z"}],"graph_snapshots":[{"event_id":"sha256:f117d39a689b3be5b2dc4e6a054cc573e7de13d3e888f46e4a8bd5225a9dce67","target":"graph","created_at":"2026-07-05T09:52:18Z","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/2411.07870/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Although people are impressed by the content generation skills of large language models, the use of LLMs, such as ChatGPT, is limited by the domain grounding of the content. The correctness and groundedness of the generated content need to be based on a verified context, such as results from Retrieval-Augmented Generation (RAG). One important issue when adapting LLMs to a customized domain is that the generated responses are often incomplete, or the additions are not verified and may even be hallucinated. Prior studies on hallucination detection have focused on evaluation metrics, which are no","authors_text":"Jaya Krishna Mandivarapu, Xiaofeng Zhu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-12T15:26:17Z","title":"Trustful LLMs: Customizing and Grounding Text Generation with Knowledge Bases and Dual Decoders"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.07870","kind":"arxiv","version":6},"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":"sha256:91222220b18a1685854f88d8c5ae36c90e9766e55c0b3a39122d3a844c6089ce","target":"record","created_at":"2026-07-05T09:52:18Z","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":"1db0f69ca056359f6843384e49754fb5d63e06aabd58d0032c5f35dd84a11b77","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-11-12T15:26:17Z","title_canon_sha256":"c280b55c94528ac6273e8146375511d520918befe985d4cf437f77e1fbec7f9b"},"schema_version":"1.0","source":{"id":"2411.07870","kind":"arxiv","version":6}},"canonical_sha256":"0be43de9f96ece6275a227a814f6fa62b3491717391d80feaf35b83f660c0b30","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0be43de9f96ece6275a227a814f6fa62b3491717391d80feaf35b83f660c0b30","first_computed_at":"2026-07-05T09:52:18.033048Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:52:18.033048Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0x6h/e7RHXDGvylXmWCA48bUEWmpcOautdpiIaViU/A/DEHf09jYH7CyJqKM0FM22w46dUhqDQZmN6OnrENrBA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:52:18.034065Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.07870","source_kind":"arxiv","source_version":6}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:91222220b18a1685854f88d8c5ae36c90e9766e55c0b3a39122d3a844c6089ce","sha256:f117d39a689b3be5b2dc4e6a054cc573e7de13d3e888f46e4a8bd5225a9dce67"],"state_sha256":"d826bfbb4efa886e91c2cc61c0dd97d14f2bfbe23ae1652680f974da203ad68c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9BlGbbCTtUc55E4699zRLVoPUXIg+PISiKhnermJHk8M5VGtqxr4Fb+oNWv6o2JXXuutkNnzXvMz0oxHAzF6Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T04:13:18.673045Z","bundle_sha256":"db40925585b527783693365f389301cac2cfe152bdd313d2b041a4671308d3d9"}}