{"as_of":"2026-08-17T06:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7c176a8a1d5c1229e55c41a16a4b6a8163c3b9faafe62deb5ad3cead6deb348a","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T11:36:08.831144Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/2607.22597/citation-record","integrity":"/paper/2607.22597/integrity","json":"/paper/2607.22597/citation-record.json","paper":"/paper/2607.22597"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T11:36:03.970233Z","title":"A survey on rag with llms","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:03.970233Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:65269e6ca7a7129accc3365a280c0144d101082c01a917d9131871bbcbc9bd56","observation_id":"d0c3ed4b-6d56-4908-a51b-5a7ca61d6f49","resolution":{"observed_at":"2026-08-02T11:36:03.970233Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.10470","last_updated":"2020-02-14T07:43:06Z","snapshot_observed_at":"2026-08-16T17:03:55.082690Z","submitted_at":"2019-11-24T08:27:42Z","title":"Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.10470","snapshot_observed_at":"2026-08-02T11:36:04.093079Z","title":"Learningtoretrievereasoningpathsoverwikipediagraphforquestion answering","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:04.093079Z"},"links":{"cited_paper":"/paper/1911.10470","citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:2127e1c0d09faa1a74b1a24f54d841febabf25a089336d84a51de014abc9e3d8","observation_id":"9bfb43b2-caa7-4230-811a-f4198df51722","resolution":{"observed_at":"2026-08-02T11:36:04.093079Z","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":"2026-08-02T11:36:04.237855Z","title":"Self-rag: Learningtoretrieve,generate,andcritiquethroughself-reflection,in: Internationalconferenceonlearningrepresentations,pp.9112–9141","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:04.237855Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:1aaf21ef8e67e3c1dc035732e9081a130f8872b77913837b4cddd3099c95e2cd","observation_id":"d05c77a4-6aac-4caf-a0dd-5d3e0e808f6d","resolution":{"observed_at":"2026-08-02T11:36:04.237855Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.02610","last_updated":"2021-06-06T04:29:57Z","snapshot_observed_at":"2026-08-14T02:56:27.840162Z","submitted_at":"2019-10-07T04:58:43Z","title":"Multi-hop Question Answering via Reasoning Chains","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.02610","snapshot_observed_at":"2026-08-02T11:36:04.399421Z","title":"Multi-hop question answering via reasoning chains","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:04.399421Z"},"links":{"cited_paper":"/paper/1910.02610","citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:57bb2aed58c2d39fe20b136ccee5be0cade8d385c3b4051ebe0c80cf90d49c48","observation_id":"36771222-1f10-4e7b-8aa1-bcf7b5f12ffc","resolution":{"observed_at":"2026-08-02T11:36:04.399421Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.16130","last_updated":"2025-02-19T10:49:41Z","snapshot_observed_at":"2026-08-16T12:38:40.131901Z","submitted_at":"2024-04-24T18:38:11Z","title":"From Local to Global: A Graph RAG Approach to Query-Focused Summarization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.16130","snapshot_observed_at":"2026-08-02T11:36:04.521863Z","title":"From local to global:Agraphragapproachtoquery-focusedsummarization","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:04.521863Z"},"links":{"cited_paper":"/paper/2404.16130","citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:d35562a5cb4a915dd2c4f433e63da7c07219399164d1687231f537a8c4139413","observation_id":"93ab73f6-3f50-4eda-a468-bb68fb9df7f6","resolution":{"observed_at":"2026-08-02T11:36:04.521863Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.10997","last_updated":"2024-03-27T09:16:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-18T07:47:33Z","title":"Retrieval-Augmented Generation for Large Language Models: A Survey","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.10997","snapshot_observed_at":"2026-08-02T11:36:04.637892Z","title":"Retrieval- augmented generation for large language models: A survey","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:04.637892Z"},"links":{"cited_paper":"/paper/2312.10997","citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:cc1bc3c56056c2100c8de831a9d1a5c8c32c7f47fc9c4c56a44b7e821701a4b7","observation_id":"bd62c3b1-d080-45ce-a7e6-d1a4a2dbf2e9","resolution":{"observed_at":"2026-08-02T11:36:04.637892Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.05779","last_updated":"2025-04-28T17:36:27Z","snapshot_observed_at":"2026-08-11T13:00:45.634760Z","submitted_at":"2024-10-08T08:00:12Z","title":"LightRAG: Simple and Fast Retrieval-Augmented Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.05779","snapshot_observed_at":"2026-08-02T11:36:04.823478Z","title":"Lightrag: Simple and fast retrieval-augmented generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:04.823478Z"},"links":{"cited_paper":"/paper/2410.05779","citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:88193ce3956891782f803841b3f327f0c0f33cd560ec8b079a23f419df39754c","observation_id":"06bb60c2-daca-41ec-b11f-0d08cfeb64bf","resolution":{"observed_at":"2026-08-02T11:36:04.823478Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12837","last_updated":"2024-10-03T22:29:47Z","snapshot_observed_at":"2026-08-16T13:12:46.081601Z","submitted_at":"2024-10-03T22:29:47Z","title":"A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12837","snapshot_observed_at":"2026-08-02T11:36:04.933133Z","title":"A comprehensive survey ofretrieval-augmentedgeneration(rag):Evolution,currentlandscape and future directions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:04.933133Z"},"links":{"cited_paper":"/paper/2410.12837","citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:f17b05514952690077543fcd247828ca63c72d47ba2fb0d667a519ca7a2789b7","observation_id":"45b6de1c-7bdf-4dbb-83a0-df8f15360e36","resolution":{"observed_at":"2026-08-02T11:36:04.933133Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2002.08909","last_updated":"2020-02-10T18:40:59Z","snapshot_observed_at":"2026-08-02T17:52:27.326803Z","submitted_at":"2020-02-10T18:40:59Z","title":"REALM: Retrieval-Augmented Language Model Pre-Training","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.08909","snapshot_observed_at":"2026-08-02T11:36:05.055361Z","title":"REALM: retrieval-augmented language model pre-training","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:05.055361Z"},"links":{"cited_paper":"/paper/2002.08909","citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:490c90581e1082223523d91b45770ae268cf464c436346d7c08836c0d5461961","observation_id":"6a32f48e-5658-44c1-90b7-cf9893180169","resolution":{"observed_at":"2026-08-02T11:36:05.055361Z","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":"2026-08-02T11:36:05.165973Z","title":"Con- structing a multi-hop qa dataset for comprehensive evaluation of reasoningsteps,in:Proceedingsofthe28thInternationalConference on Computational Linguistics, pp","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:05.165973Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:ce62848137dbc9aacb23a1fd2dc783c5eb51b6ac9207cafd2c3179ae1f41d7f7","observation_id":"4644caeb-c103-424f-ad3a-d76f1163d26b","resolution":{"observed_at":"2026-08-02T11:36:05.165973Z","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":"2026-08-02T11:36:05.325913Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:05.325913Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:2f3883a0108bf7443908d3d3399b30deda23066708aa4b63c10b84a3559c9617","observation_id":"72b1883a-a554-4933-a2d7-3d0093058092","resolution":{"observed_at":"2026-08-02T11:36:05.325913Z","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":"2026-08-02T11:36:05.567069Z","title":"Retrieve, summarize, plan: Advancing multi-hop question answering with an iterative ap- proach, in: Companion Proceedings of the ACM on Web Conference 2025, pp","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:05.567069Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:0a8e649e5c0e8f2155da6c2bd0613b7f429ead53f728baad14b1a681ddad4b0f","observation_id":"cf817599-d29a-49d1-bc89-e4a75436bd6f","resolution":{"observed_at":"2026-08-02T11:36:05.567069Z","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":"2026-08-02T11:36:05.725230Z","title":"Active retrieval augmented generation, in: Proceedings of the 2023 conference on empirical methods in natural language processing, pp","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:05.725230Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:7f3d0d0dd92e1e6d6454baa07ce7b0cc072d001d967f89fd91045d77a28e90c6","observation_id":"dbec0fea-01e1-4ac3-8171-59326eb39108","resolution":{"observed_at":"2026-08-02T11:36:05.725230Z","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":"2026-08-02T11:36:05.894650Z","title":"Densepassageretrievalforopen-domainquestion answering, in: Proceedings of the 2020 conference on empirical methods in natural language processing (EMNLP), pp","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:05.894650Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:535ce541a4d0f2f443c863646cd4be609f9276771585e91c73407466bb10b8c8","observation_id":"3dbef87a-c761-431d-b5e0-fd23824dbd5e","resolution":{"observed_at":"2026-08-02T11:36:05.894650Z","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":"2026-08-02T11:36:06.083138Z","title":"Efficient memory man- agement for large language model serving with pagedattention, in: Proceedings of the ACM SIGOPS 29th Symposium on Operating Systems Principles","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:06.083138Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:5962b916ef2dbbab3b9ecbe4e884081e8587a4b4d220f9989e55a04a883901b8","observation_id":"307c0510-7cfd-466e-aaf4-d206583acf80","resolution":{"observed_at":"2026-08-02T11:36:06.083138Z","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":"2026-08-02T11:36:06.294059Z","title":"Retrieval-augmented generation for knowledge-intensive nlp tasks","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:06.294059Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:9ce426c1318665d57e8a115010a72a77363deca03907dcd1968ee2f81bb2eab1","observation_id":"663079da-712e-4805-9bf9-33a2ea1e4e51","resolution":{"observed_at":"2026-08-02T11:36:06.294059Z","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":"2026-08-02T11:36:06.450451Z","title":"Advances in Neural Information Processing Systems 38, 152206–152234","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:06.450451Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:733e9aed5c33fb657954cfae84d08edf55bb4ffa71f3b576f0f49993142d2f77","observation_id":"1da7c0f5-0d14-4cc6-83e0-709fff661452","resolution":{"observed_at":"2026-08-02T11:36:06.450451Z","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":"2026-08-02T11:36:06.553248Z","title":"Gfm-rag:graphfoundationmodelforretrievalaugmentedgeneration","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:06.553248Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:6c1e928a2bdbd0253e614c03c50d36518a7f601a44460f829f767039237e8ad5","observation_id":"e16f0bec-4989-4cc4-8023-0b79a07a6b89","resolution":{"observed_at":"2026-08-02T11:36:06.553248Z","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":"2026-08-02T11:36:06.633988Z","title":"Multi-hopquestionanswering","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:06.633988Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:6e8546c26dd9b838f282a0005eefddc0b1164d993c1a545d6df95f26abceccce","observation_id":"9ac5d9d4-e4b2-4f66-94f6-232ba87ac61f","resolution":{"observed_at":"2026-08-02T11:36:06.633988Z","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":"2026-08-02T11:36:06.744130Z","title":"Ordered and hamilton digraphs","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:06.744130Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:5f317f5872498082698d68584496cef0ed4d44ab5075c8874fa20bf7fa0010fb","observation_id":"c9481d00-9f1b-4771-9796-aaa139574b45","resolution":{"observed_at":"2026-08-02T11:36:06.744130Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.10925","last_updated":"2025-08-08T19:24:38Z","snapshot_observed_at":"2026-08-14T02:46:12.121034Z","submitted_at":"2025-08-08T19:24:38Z","title":"gpt-oss-120b & gpt-oss-20b Model Card","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.10925","snapshot_observed_at":"2026-08-02T11:36:06.806458Z","title":"gpt-oss-120b & gpt-oss-20b model card","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:06.806458Z"},"links":{"cited_paper":"/paper/2508.10925","citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:8e7836e5d5c00bca1ca9eec6b7177100985b7d923a62c1f00f45d32afee85065","observation_id":"20594ba1-d097-4d95-962b-8b4a0a8729ca","resolution":{"observed_at":"2026-08-02T11:36:06.806458Z","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":"2026-08-02T11:36:06.899221Z","title":"IEEE Transactions on Knowledge and Data Engineering 36, 3580–3599","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:06.899221Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:7f3f0fcc327a8e4d62d9d58310a4a85447486876810979c219f56eaeb37316b8","observation_id":"411c7a2e-974c-4b99-a7b0-cf97983feebe","resolution":{"observed_at":"2026-08-02T11:36:06.899221Z","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":"2026-08-02T11:36:07.038869Z","title":"Howmuchknowledgecan you pack into the parameters of a language model?, in: Proceedings of the 2020 conference on empirical methods in natural language processing (EMNLP), pp","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:07.038869Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:0807066fb1dbee8183b30e27cba4f1091d788e17d3f9d053c6952d31cc327fb2","observation_id":"af907e1e-3e9b-42fe-b227-1f422c80eded","resolution":{"observed_at":"2026-08-02T11:36:07.038869Z","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":"2026-08-02T11:36:07.177806Z","title":"Transactions of the Association for Computational Linguistics 10, 539–554","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:07.177806Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:b836f97ac232612f5a708e50b259ae4a080d32c62b9b9bb3a4d5b7177e3f33b4","observation_id":"b4064116-09f5-4e3f-91fa-d2c8b52760e3","resolution":{"observed_at":"2026-08-02T11:36:07.177806Z","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":"2026-08-02T11:36:07.299309Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:07.299309Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:84385da7b0d3f895bceca3c3cea252d04ea63c34b30416ff5c0ae71c1f765e74","observation_id":"c407d716-ce12-40c6-a317-81483f3ddd9c","resolution":{"observed_at":"2026-08-02T11:36:07.299309Z","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":"2026-08-02T11:36:07.444820Z","title":"Diagnosability of cayley graph networks generated by transposition trees under the comparison diagnosis model","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:07.444820Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:077ed47c63052f7e93cf854cfb79ad96425f0cc5b78e8e097e98a436612e1402","observation_id":"34c6ec89-37b0-477c-93b4-8d37e3301415","resolution":{"observed_at":"2026-08-02T11:36:07.444820Z","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":"2026-08-02T11:36:07.563380Z","title":"The edge connectivity of expanded k-ary n-cubes","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:07.563380Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:bb877b1f73b71a0c65b0561f2e325ccb999eaa092b97f51f3ec6f55d3cf16c4a","observation_id":"9ca22f41-5643-4199-a2ec-ed86e03fa730","resolution":{"observed_at":"2026-08-02T11:36:07.563380Z","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":"2026-08-02T11:36:07.647315Z","title":"Embedding paths into the4-aryn-cubewithfaultynodes,in:2011InternationalConference onConsumerElectronics,CommunicationsandNetworks(CECNet), IEEE","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:07.647315Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:0051e2fb3779ce36a2013f545de32b083db749fd5f5d65a17012a32f955f44d6","observation_id":"e95a10ef-d947-46fb-beb8-4b132a075d5a","resolution":{"observed_at":"2026-08-02T11:36:07.647315Z","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":"2026-08-02T11:36:07.705778Z","title":"Fstgat:Financialspatio-temporalgraphattention network for non-stationary financial systems and its application in stock price prediction","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:07.705778Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:ef98e7dc80cd0f384b1ea91453a6b88afefe198ec7028f021d53d77bbe915f27","observation_id":"b63ff4e0-f966-4463-8168-48d8e9904353","resolution":{"observed_at":"2026-08-02T11:36:07.705778Z","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":"2026-08-02T11:36:07.790291Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:07.790291Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:4b66e9e3bf3f79563c232c06ab8c54939bf648062209f955443d06eb25477d69","observation_id":"5bf6af42-731e-4dff-b219-126a5f91835a","resolution":{"observed_at":"2026-08-02T11:36:07.790291Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.02404","last_updated":"2025-06-20T02:42:32Z","snapshot_observed_at":"2026-08-16T01:50:17.758639Z","submitted_at":"2025-06-03T03:44:26Z","title":"GraphRAG-Bench: Challenging Domain-Specific Reasoning for Evaluating Graph Retrieval-Augmented Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.02404","snapshot_observed_at":"2026-08-02T11:36:07.959250Z","title":"Graphrag-bench: Challenging domain-specific reasoningforevaluatinggraphretrieval-augmentedgeneration","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:07.959250Z"},"links":{"cited_paper":"/paper/2506.02404","citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:0bd4edbc5ea847885dae00c40e24255fa9f4e2e7b0a4682de20f5f2650ee8759","observation_id":"0a4a0624-9f20-4849-bdc7-736a8a9892a5","resolution":{"observed_at":"2026-08-02T11:36:07.959250Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.12756","last_updated":"2021-02-19T22:15:03Z","snapshot_observed_at":"2026-08-17T05:00:40.411194Z","submitted_at":"2020-09-27T06:12:29Z","title":"Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.12756","snapshot_observed_at":"2026-08-02T11:36:08.041393Z","title":"Answering complex open-domainquestionswithmulti-hopdenseretrieval","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:08.041393Z"},"links":{"cited_paper":"/paper/2009.12756","citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:4d620f0797bf854a920d105ee7baa62276f75c9097eb5605928473498c769113","observation_id":"2434b7b9-5a24-4337-a7cd-401a59540903","resolution":{"observed_at":"2026-08-02T11:36:08.041393Z","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":"2026-08-02T11:36:08.188794Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:08.188794Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:b2cc5ea3bb2b75bc859e1980b534c424086404f884f43b60e2b177144f2d16c5","observation_id":"9b8eb3ef-8b20-4ef8-9d70-92b9cc5b62a5","resolution":{"observed_at":"2026-08-02T11:36:08.188794Z","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":"2026-08-02T11:36:08.376366Z","title":"Hotpotqa: A dataset for diverse, explainable multi-hopquestionanswering,in:Proceedingsofthe2018conference onempiricalmethodsinnaturallanguageprocessing,pp.2369–2380","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:08.376366Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:a42c98d893d5d80e657084a637d7a20b738678226394247c7176a04ad16c3797","observation_id":"153b2e09-283d-41ac-afe8-f4f1f1c36f93","resolution":{"observed_at":"2026-08-02T11:36:08.376366Z","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":"2026-08-02T11:36:08.465655Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:08.465655Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:0be9187f4b33f98ba400a243b69baa9c71402f9f7e7e88307d76cff503a8b70b","observation_id":"0b7f6dd5-f905-4138-9655-94ed7533c7df","resolution":{"observed_at":"2026-08-02T11:36:08.465655Z","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":"2026-08-02T11:36:08.575381Z","title":"Ragpowered llmsforqa:Evolution,challenges,applications,andfuturedirections, in: 2025 International Conference on Communication Technologies (ComTech), IEEE","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:08.575381Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:f6fbb1304ffc36d8b2847862d45202511ea8a8bea2d50002de687344b63bf581","observation_id":"08a6db49-6810-4eab-8e45-0eb89f3f4d18","resolution":{"observed_at":"2026-08-02T11:36:08.575381Z","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":"2026-08-02T11:36:08.647512Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:08.647512Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:69d3845a6b57cffe36661c90fcaf2d46a4b791a2e77fb1052df36b8e758213e4","observation_id":"3e808fc3-d59b-4b7f-9b1b-2c5a028da105","resolution":{"observed_at":"2026-08-02T11:36:08.647512Z","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":"2026-08-02T11:36:08.699994Z","title":"A survey of large language models","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:08.699994Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:b4327aad24347cdf41436f1487f12d6680ad4d7968e2bf5bb6c497a4dba72c7d","observation_id":"86ed7d67-272a-4816-ba65-837d68fdbb5e","resolution":{"observed_at":"2026-08-02T11:36:08.699994Z","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":"2026-08-02T11:36:08.778150Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:08.778150Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:ac137a764790b0694286672916a93821908ae43af8a99a3f2984925e392abe4a","observation_id":"0e35cb28-a104-42ba-947a-c19eb96e5cb4","resolution":{"observed_at":"2026-08-02T11:36:08.778150Z","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":"2026-08-02T11:36:08.831144Z","title":"Linearrag: Linear graph retrieval augmented generationonlarge-scalecorpora","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:08.831144Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:3722422e7f246a8c05954ba46bf37f31d933a3dca9a4c54e264305820c91ed94","observation_id":"c16be3fa-2e14-44b8-83d1-9f9b8642437f","resolution":{"observed_at":"2026-08-02T11:36:08.831144Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.03629","last_updated":"2023-03-10T01:00:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-10-06T01:00:32Z","title":"ReAct: Synergizing Reasoning and Acting in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.03629","snapshot_observed_at":"2026-08-02T11:36:08.523104Z","title":"arXiv preprint arXiv:2210.03629","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:08.523104Z"},"links":{"cited_paper":"/paper/2210.03629","citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:bc15bbe516fe3dd0ca39b34c1792f7e9460f01d39247946dd860c8ee130e7da5","observation_id":"b57eebcd-c19b-476d-bbbe-c8170ec3cb47","resolution":{"observed_at":"2026-08-02T11:36:08.523104Z","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":"2026-08-02T11:36:07.871080Z","title":"arXiv preprint arXiv:2506.05690","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:07.871080Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:b5ffccbcd447a0d4c8fcc21dd1e3a744f3f877b4d00f8a681a684d535e6385b4","observation_id":"7ae26802-c94b-4238-a671-996fa67470fb","resolution":{"observed_at":"2026-08-02T11:36:07.871080Z","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":"2026-08-02T11:36:05.412669Z","title":"Symmetry 18, 394","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering","version":1},"reference_index":2026,"source":"pdf_text","source_observed_at":"2026-08-02T11:36:05.412669Z"},"links":{"citing_paper":"/paper/2607.22597"},"observation_digest":"sha256:d4f93734ec9dbf34c717a77ec30a2a520b429ad7478e667d31f6d79d30ee9717","observation_id":"8340d1fe-6f86-4f4b-a1e2-289a03637098","resolution":{"observed_at":"2026-08-02T11:36:05.412669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.22597","last_updated":"2026-06-12T08:28:42Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-17T04:13:14.637844Z","submitted_at":"2026-06-12T08:28:42Z","title":"HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":43,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":43},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2607.22597."}