{"as_of":"2026-08-14T03:08:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:223827d58ab11ac7e09db082fc0969d8fe629060a21b7ca9fa6a066662ed6b30","coverage":[{"denominator":22,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":22,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-11T20:50:52.068889Z","state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.04223/citation-record","integrity":"/paper/2607.04223/integrity","json":"/paper/2607.04223/citation-record.json","paper":"/paper/2607.04223"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"Retrieval- augmented generation for knowledge-intensive NLP tasks,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:a8d8d0227e40cb79355316c50761bfc9a1c41bd0c0af5853c59cfcfa45014667","observation_id":"da7a38df-1f08-44b6-a687-6f4ff2905b22","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"Survey of halluci- nation in natural language generation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:38977db5364dd89afa70c4b7542c02e1c6664171fb27a18cc136205ed273ec08","observation_id":"06236f93-ef52-4afe-a2d9-45376ff2b1a6","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"A survey on hallucination in large language models: Principles, taxonomy, challenges, and open questions,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:0bd0db1b3f5931923216585eed5d495b499d01cefabd5056e8370f499b77f5d2","observation_id":"d518fe9c-8a7b-41f9-ba29-10a48ef92cde","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"Detecting hallucinations in large language models using semantic entropy,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:1cd464351868ceea1791c04b6afe6e6268ff842147a123841b7e75fb8d3997aa","observation_id":"f67e9a36-9a39-46fb-9bfd-f59566c94407","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"INSIDE: LLMs’ internal states retain the power of hallucination detection,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:fc82382da736676d85a69f9f887c48f54ba1a758604b1211253ed2c6d63ea8f3","observation_id":"3441851f-e2ba-49e6-a364-862901749dd9","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"LLM-Check: Investigating detection of hallucinations in large language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:e6f6f2aae6a81f2be056609b128e6df5178754cdb0746933d8bfd7dc32b3a593","observation_id":"1ab14bca-965d-4639-af85-6470a02e88b1","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"SelfCheck- GPT: Zero-resource black-box hallucination detection for generative large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:0c7d8c3b7eead1acb66a6744a1142905d9f2cf778f4978ffca3a721440b296c9","observation_id":"5548c19f-97eb-4282-9af5-2e6af6db3f82","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"FActScore: Fine-grained atomic evaluation of factual precision in long form text generation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:eda02816c5d839253f44e7b493c0022920c34c5e4d3702051005db7b215a0a5b","observation_id":"4b7c4dfb-3da2-4479-8266-a3113f1021d0","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"ContextCite: Attributing model generation to context,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:137758cf5405d7101a00fd966054cd0d98cd3fc5933c29f69569ce7ba9b3718d","observation_id":"c09a48eb-58b0-42a6-ac08-8767b863c748","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"Lookback lens: Detecting and mitigating contextual hallucinations in large language models using only attention maps,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:1b61ea9b1986de6d5767ca28737f2967f3e8b301f48d7b14dfe96fd30d9363d6","observation_id":"95766cb1-b7a4-4cdf-a7e3-20a0dd102631","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"ReDeEP: Detecting hallucination in retrieval-augmented generation via mechanistic inter- pretability,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:967d7d1943cd14b6383adfd7689db117d103a4237d955f5dba8e636ac4e4fe66","observation_id":"e744a48c-a74a-4303-ae16-d629c251c2af","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"LUMINA: Detecting hallucinations in RAG systems with context-knowledge signals,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:7eaca0847c58c5b652c0f2918fbaa7123eefd16aef9ea6bec740291169e5d6bf","observation_id":"1e84af66-4520-4cc2-ae5d-7a4488b98034","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"RAGTruth: A hallucination corpus for developing trustworthy retrieval- augmented language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:82a82f885ac6495fa722c6802b9eda6cdc3c441eccaabb0e0ea0f15f9923e63d","observation_id":"ec383540-15f7-4d2b-9eb6-00d4be92fb60","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"RAGAs: Automated evaluation of retrieval augmented generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:c5911b7ccb865a6fa3d5bff3d4b15a5a47b1f8845e14ddbfc8e0d50b9229f253","observation_id":"0cfa3811-73b5-407e-9d82-0d28fd2aaeb1","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.17125","last_updated":"2025-02-24T13:11:47Z","snapshot_observed_at":"2026-08-10T17:59:38.518370Z","submitted_at":"2025-02-24T13:11:47Z","title":"LettuceDetect: A Hallucination Detection Framework for RAG Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.17125","snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"Kovács and G","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"cited_paper":"/paper/2502.17125","citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:2d34fc0e669f0472857c5dd75f1cca3843c18bc2409acba26f92c3993c350a4c","observation_id":"5e0df7e0-e6b2-407b-874c-21e0c595bb3f","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"Fractal attractors in random nonlinear it- erated function systems: Existence, stability, and dimen- sional properties,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:487d91a443516bf1a446a7058c38ec141c42abd040676c08d929ab7a523c4af8","observation_id":"e146cd35-e64d-4732-88a8-ac95e0e7ff0a","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"Light- GBM: A highly efficient gradient boosting decision tree,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:83bc832ff4c78eb3d473df4cee1a3c3d2f384c4318a79f319242350a057b21ca","observation_id":"47e45e25-4170-455f-b7d0-7c77770a3aeb","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"TofuEval: Evaluating hallucinations of large language models on topic-focused dialogue summarization,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:81f81adfcbfc0e2e0d8a264d4b995a739b3efeac2f22cfa70043135bb2590769","observation_id":"8e361f44-56da-457d-8594-a1d9e07c8505","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"MeetingBank: A benchmark dataset for meeting summarization,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:f9b12e9cb04c500ae2c16e5b8ce59c3531618b2c158a0017b1efa35011e407d6","observation_id":"5b7dc90e-13e5-4899-94aa-e226a6dc749b","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.11005","last_updated":"2025-01-16T10:05:17Z","snapshot_observed_at":"2026-08-12T23:34:57.594338Z","submitted_at":"2024-06-25T20:23:15Z","title":"RAGBench: Explainable Benchmark for Retrieval-Augmented Generation Systems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.11005","snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"RAGBench: Explain- able benchmark for retrieval-augmented generation sys- tems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"cited_paper":"/paper/2407.11005","citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:2e2d6cf4d844d308cf3785f0626470d52f0a61bfd6ab2eef9ee70000f8c6f662","observation_id":"d581c92c-f77e-42f8-9bf4-92d55a11760f","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"Qwen2.5 technical report,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:9d22a1f46ede2e1a1b91f24463f3b44054346fd2c77727304a9cf2fb4a5c0a8c","observation_id":"cd4ffd5d-7f52-4a85-bf6e-a9207b65dc8b","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.02737","last_updated":"2025-02-04T21:43:16Z","snapshot_observed_at":"2026-08-13T00:38:34.374692Z","submitted_at":"2025-02-04T21:43:16Z","title":"SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.02737","snapshot_observed_at":"2026-07-11T20:50:52.068889Z","title":"SmolLM2: When smol goes big – data-centric training of a small lan- guage model,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-11T20:50:52.068889Z"},"links":{"cited_paper":"/paper/2502.02737","citing_paper":"/paper/2607.04223"},"observation_digest":"sha256:d5c574d035f71ad39630cb615a8ed06ab12d915c41112fcbdbe1d0501e82d661","observation_id":"7f2a0416-7b7d-4f59-ad65-178dd98023b9","resolution":{"observed_at":"2026-07-11T20:50:52.068889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.04223","last_updated":"2026-07-05T10:35:30Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-13T05:15:01.957678Z","submitted_at":"2026-07-05T10:35:30Z","title":"Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)"},"reference_resolution":{"displayed":22,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":22,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":22},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2607.04223."}