{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ASXSCR3EL2UQRQIXB3DEWWBXI6","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":"8ccdab060d9ad0c15930817145df1c2c25c6389c1047ee2999a16186dae7c34b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-17T14:47:33Z","title_canon_sha256":"719e14f618b4aa606590dea41aa9f79c6f4a6c6a3cdd0671a548157abdf55c2f"},"schema_version":"1.0","source":{"id":"2409.11242","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.11242","created_at":"2026-07-05T10:53:11Z"},{"alias_kind":"arxiv_version","alias_value":"2409.11242v4","created_at":"2026-07-05T10:53:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.11242","created_at":"2026-07-05T10:53:11Z"},{"alias_kind":"pith_short_12","alias_value":"ASXSCR3EL2UQ","created_at":"2026-07-05T10:53:11Z"},{"alias_kind":"pith_short_16","alias_value":"ASXSCR3EL2UQRQIX","created_at":"2026-07-05T10:53:11Z"},{"alias_kind":"pith_short_8","alias_value":"ASXSCR3E","created_at":"2026-07-05T10:53:11Z"}],"graph_snapshots":[{"event_id":"sha256:760b0d6654420711ed0c1109b0ec902f3bdf96f1242efda2005de756f9ad3e40","target":"graph","created_at":"2026-07-05T10:53:11Z","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/2409.11242/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"LLMs are an integral component of retrieval-augmented generation (RAG) systems. While many studies focus on evaluating the overall quality of end-to-end RAG systems, there is a gap in understanding the appropriateness of LLMs for the RAG task. To address this, we introduce Trust-Score, a holistic metric that evaluates the trustworthiness of LLMs within the RAG framework. Our results show that various prompting methods, such as in-context learning, fail to effectively adapt LLMs to the RAG task as measured by Trust-Score. Consequently, we propose Trust-Align, a method to align LLMs for improved","authors_text":"Hai Leong Chieu, Maojia Song, Navonil Majumder, Rishabh Bhardwaj, Shang Hong Sim, Soujanya Poria","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-17T14:47:33Z","title":"Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to Refuse"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.11242","kind":"arxiv","version":4},"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":"sha256:61b744603d6a2050655aef35f49932d6c98741d74afe359c9f3b539521a96915","target":"record","created_at":"2026-07-05T10:53:11Z","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":"8ccdab060d9ad0c15930817145df1c2c25c6389c1047ee2999a16186dae7c34b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-09-17T14:47:33Z","title_canon_sha256":"719e14f618b4aa606590dea41aa9f79c6f4a6c6a3cdd0671a548157abdf55c2f"},"schema_version":"1.0","source":{"id":"2409.11242","kind":"arxiv","version":4}},"canonical_sha256":"04af2147645ea908c1170ec64b583747a06d1bfef4cb2e07c7da8e78e2e83aa5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"04af2147645ea908c1170ec64b583747a06d1bfef4cb2e07c7da8e78e2e83aa5","first_computed_at":"2026-07-05T10:53:11.818785Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:53:11.818785Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e8qAr5DjaMmR4Rtp0ZGF6nsslqrhjyUfwnUFq1q2+dbV9Fk4zNujSmym+rnJqMFnakflh1WfoSsa5VQAo/vWBw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:53:11.819269Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.11242","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:61b744603d6a2050655aef35f49932d6c98741d74afe359c9f3b539521a96915","sha256:760b0d6654420711ed0c1109b0ec902f3bdf96f1242efda2005de756f9ad3e40"],"state_sha256":"0334a0ffd05a77e33bbfc03873db285d299baeb2cdc90f6933fc9d4bb1167027"}