{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:NKDUKDBYJLR6WYISWTTXMXBHVI","short_pith_number":"pith:NKDUKDBY","canonical_record":{"source":{"id":"2412.10571","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-13T21:28:17Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"635531ac190dc00c64dd80eaf449f60ae054e89fb9f7ded17114f49570670268","abstract_canon_sha256":"25d631250c1b743ef022be8ab058c069069b8f848b642c63dbdd1b0a90c7c16a"},"schema_version":"1.0"},"canonical_sha256":"6a87450c384ae3eb6112b4e7765c27aa28356ca23f0c38f7f76c4b74eda65fc3","source":{"kind":"arxiv","id":"2412.10571","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.10571","created_at":"2026-07-05T09:53:08Z"},{"alias_kind":"arxiv_version","alias_value":"2412.10571v3","created_at":"2026-07-05T09:53:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.10571","created_at":"2026-07-05T09:53:08Z"},{"alias_kind":"pith_short_12","alias_value":"NKDUKDBYJLR6","created_at":"2026-07-05T09:53:08Z"},{"alias_kind":"pith_short_16","alias_value":"NKDUKDBYJLR6WYIS","created_at":"2026-07-05T09:53:08Z"},{"alias_kind":"pith_short_8","alias_value":"NKDUKDBY","created_at":"2026-07-05T09:53:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:NKDUKDBYJLR6WYISWTTXMXBHVI","target":"record","payload":{"canonical_record":{"source":{"id":"2412.10571","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-13T21:28:17Z","cross_cats_sorted":["cs.IR"],"title_canon_sha256":"635531ac190dc00c64dd80eaf449f60ae054e89fb9f7ded17114f49570670268","abstract_canon_sha256":"25d631250c1b743ef022be8ab058c069069b8f848b642c63dbdd1b0a90c7c16a"},"schema_version":"1.0"},"canonical_sha256":"6a87450c384ae3eb6112b4e7765c27aa28356ca23f0c38f7f76c4b74eda65fc3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:53:08.814762Z","signature_b64":"BNXRwlPvObFEiNZgv9e/aPUBtCfXUrz1X9qbQqOlqV5rqQJDXXfdWtog9csDb9j8zAgyAeDCxtTZWbG7ktsLBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6a87450c384ae3eb6112b4e7765c27aa28356ca23f0c38f7f76c4b74eda65fc3","last_reissued_at":"2026-07-05T09:53:08.814301Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:53:08.814301Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.10571","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":"2026-07-05T09:53:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gS4JtAbXo9Rn1xTfIMVk1Lo7835sN1x+fCto3comZ+ORrGR2C8UZy9fqVph0CwW/hGXZs7BGjLfyYEsgIHrhBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T02:44:36.637482Z"},"content_sha256":"a05ae8e99618e8392efdbd25896bd8ad98544e1ee494db432978f9f4d70e92ba","schema_version":"1.0","event_id":"sha256:a05ae8e99618e8392efdbd25896bd8ad98544e1ee494db432978f9f4d70e92ba"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:NKDUKDBYJLR6WYISWTTXMXBHVI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Evidence Contextualization and Counterfactual Attribution for Conversational QA over Heterogeneous Data with RAG Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IR"],"primary_cat":"cs.CL","authors_text":"Andreas Foltyn, Chris Hinze, Fabian Kuech, Joel Schlotthauer, Luzian Hahn, Rishiraj Saha Roy","submitted_at":"2024-12-13T21:28:17Z","abstract_excerpt":"Retrieval Augmented Generation (RAG) works as a backbone for interacting with an enterprise's own data via Conversational Question Answering (ConvQA). In a RAG system, a retriever fetches passages from a collection in response to a question, which are then included in the prompt of a large language model (LLM) for generating a natural language (NL) answer. However, several RAG systems today suffer from two shortcomings: (i) retrieved passages usually contain their raw text and lack appropriate document context, negatively impacting both retrieval and answering quality; and (ii) attribution str"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.10571","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/2412.10571/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":"2026-07-05T09:53:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XbTbCbqIpcN1bK+dV+dQZE1EdiFf4YP9hKILl286P8fbXqYpTqq6o2t+XB6gUxBaJ3RXQKo3I0DXKGeINxwhAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T02:44:36.638562Z"},"content_sha256":"bdf4269bef0be3bbf316ea66250cda6113f1355cf5adbd33b991bd4d69a80f9f","schema_version":"1.0","event_id":"sha256:bdf4269bef0be3bbf316ea66250cda6113f1355cf5adbd33b991bd4d69a80f9f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NKDUKDBYJLR6WYISWTTXMXBHVI/bundle.json","state_url":"https://pith.science/pith/NKDUKDBYJLR6WYISWTTXMXBHVI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NKDUKDBYJLR6WYISWTTXMXBHVI/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":"2026-08-16T02:44:36Z","links":{"resolver":"https://pith.science/pith/NKDUKDBYJLR6WYISWTTXMXBHVI","bundle":"https://pith.science/pith/NKDUKDBYJLR6WYISWTTXMXBHVI/bundle.json","state":"https://pith.science/pith/NKDUKDBYJLR6WYISWTTXMXBHVI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NKDUKDBYJLR6WYISWTTXMXBHVI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NKDUKDBYJLR6WYISWTTXMXBHVI","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":"25d631250c1b743ef022be8ab058c069069b8f848b642c63dbdd1b0a90c7c16a","cross_cats_sorted":["cs.IR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-13T21:28:17Z","title_canon_sha256":"635531ac190dc00c64dd80eaf449f60ae054e89fb9f7ded17114f49570670268"},"schema_version":"1.0","source":{"id":"2412.10571","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.10571","created_at":"2026-07-05T09:53:08Z"},{"alias_kind":"arxiv_version","alias_value":"2412.10571v3","created_at":"2026-07-05T09:53:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.10571","created_at":"2026-07-05T09:53:08Z"},{"alias_kind":"pith_short_12","alias_value":"NKDUKDBYJLR6","created_at":"2026-07-05T09:53:08Z"},{"alias_kind":"pith_short_16","alias_value":"NKDUKDBYJLR6WYIS","created_at":"2026-07-05T09:53:08Z"},{"alias_kind":"pith_short_8","alias_value":"NKDUKDBY","created_at":"2026-07-05T09:53:08Z"}],"graph_snapshots":[{"event_id":"sha256:bdf4269bef0be3bbf316ea66250cda6113f1355cf5adbd33b991bd4d69a80f9f","target":"graph","created_at":"2026-07-05T09:53:08Z","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/2412.10571/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Retrieval Augmented Generation (RAG) works as a backbone for interacting with an enterprise's own data via Conversational Question Answering (ConvQA). In a RAG system, a retriever fetches passages from a collection in response to a question, which are then included in the prompt of a large language model (LLM) for generating a natural language (NL) answer. However, several RAG systems today suffer from two shortcomings: (i) retrieved passages usually contain their raw text and lack appropriate document context, negatively impacting both retrieval and answering quality; and (ii) attribution str","authors_text":"Andreas Foltyn, Chris Hinze, Fabian Kuech, Joel Schlotthauer, Luzian Hahn, Rishiraj Saha Roy","cross_cats":["cs.IR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-13T21:28:17Z","title":"Evidence Contextualization and Counterfactual Attribution for Conversational QA over Heterogeneous Data with RAG Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.10571","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:a05ae8e99618e8392efdbd25896bd8ad98544e1ee494db432978f9f4d70e92ba","target":"record","created_at":"2026-07-05T09:53:08Z","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":"25d631250c1b743ef022be8ab058c069069b8f848b642c63dbdd1b0a90c7c16a","cross_cats_sorted":["cs.IR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-13T21:28:17Z","title_canon_sha256":"635531ac190dc00c64dd80eaf449f60ae054e89fb9f7ded17114f49570670268"},"schema_version":"1.0","source":{"id":"2412.10571","kind":"arxiv","version":3}},"canonical_sha256":"6a87450c384ae3eb6112b4e7765c27aa28356ca23f0c38f7f76c4b74eda65fc3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6a87450c384ae3eb6112b4e7765c27aa28356ca23f0c38f7f76c4b74eda65fc3","first_computed_at":"2026-07-05T09:53:08.814301Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:53:08.814301Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"BNXRwlPvObFEiNZgv9e/aPUBtCfXUrz1X9qbQqOlqV5rqQJDXXfdWtog9csDb9j8zAgyAeDCxtTZWbG7ktsLBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:53:08.814762Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.10571","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a05ae8e99618e8392efdbd25896bd8ad98544e1ee494db432978f9f4d70e92ba","sha256:bdf4269bef0be3bbf316ea66250cda6113f1355cf5adbd33b991bd4d69a80f9f"],"state_sha256":"75559cb6562190564d19fc3c632c8af1ee40c04d2450cb0aca60c32686a9554c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q2KTh9/jTbdFFzt6BTZvoRWrmH4tb+7lPjtNbM9OVFhJTusOGt0P3Ur1P3DKZUZh9E8cjRkFgem9U/3E+28FCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T02:44:36.644856Z","bundle_sha256":"b17e2477da77651e3240b96f896c3e8d1d1c7044506b0ea0880991e616c30ddb"}}