{"as_of":"2026-08-10T19:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:997414de02aa573993ce0bb690bc6c844ec52613c7d3f913ea7ed4ee35c95185","coverage":[{"denominator":54,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":54,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:07:20.164955Z","state":"measured"},{"denominator":54,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":54,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2506.11600/citation-record","integrity":"/paper/2506.11600/integrity","json":"/paper/2506.11600/citation-record.json","paper":"/paper/2506.11600"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.153685Z","title":"MLModeler5@ Causal News Corpus 2023: Us- ing RoBERTa for Casual Event Classification","venue":null,"work_id":"0c224944-5627-4050-b826-e37f66af3d39","year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:19.985484Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:ca24338ea1b8a1ece33ed60208ba528cabe8ceac58ffb3d51f94d5c79506e675","observation_id":"95ea8c9d-9e4c-416d-8065-69decd5ec69d","resolution":{"observed_at":"2026-08-07T04:07:21.157022Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.143136Z","title":"Investigating Causal Reasoning in Large Language Models","venue":null,"work_id":"449ead6b-97dc-40e2-ba19-82530d6f679a","year":2024},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:19.989385Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:ca87668480f56c3dd1d4a85e046bdd76e483c0210ad63801bcb971eea6ed39d0","observation_id":"9bffe9cf-ee3b-4a63-9c48-ae6e15bde72d","resolution":{"observed_at":"2026-08-07T04:07:21.146794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.09901","last_updated":"2023-09-18T16:05:07Z","snapshot_observed_at":"2026-08-10T11:47:29.961456Z","submitted_at":"2023-09-18T16:05:07Z","title":"The role of causality in explainable artificial intelligence","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.09901","snapshot_observed_at":"2026-08-07T04:07:19.992573Z","title":"The Role of Causality in Explainable Artificial Intelli- gence","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:19.992573Z"},"links":{"cited_paper":"/paper/2309.09901","citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:fb7b424bb276d9c0f76426eb4aff2a9140fdd4f7308bc789c6c7ffd6721adb38","observation_id":"44844602-0398-4b65-9b5f-954ac92e6069","resolution":{"observed_at":"2026-08-07T04:07:19.992573Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.00725","last_updated":"2022-07-30T05:18:10Z","snapshot_observed_at":"2026-08-07T18:10:38.409986Z","submitted_at":"2021-09-02T05:40:08Z","title":"Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.00725","snapshot_observed_at":"2026-08-07T04:07:19.996254Z","title":"Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:19.996254Z"},"links":{"cited_paper":"/paper/2109.00725","citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:f1919930b95e3f1e4784e602e8d7062167d496831cfd79b4ba8a5426e274931e","observation_id":"72796c67-8960-4cae-b5e9-6ae88d33bf21","resolution":{"observed_at":"2026-08-07T04:07:19.996254Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.132061Z","title":"CausalNLP Tutorial: An Introduction to Causality for Natural Language Processing","venue":null,"work_id":"89f5205d-a80a-4c34-b409-a359cbaaa21b","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.000544Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:09e5fc333442dfeb4c192d28deffdd718c8fd9e34573657639a17057acc304a4","observation_id":"508c399c-ace8-4152-bba3-520155b2b6d7","resolution":{"observed_at":"2026-08-07T04:07:21.136108Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.004152Z","title":"Using Natural Language Processing to Extract Health-Related Causality from Twitter Messages","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.004152Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:e42f1ba5490a81e4468ef3ca273d951de83f662e2ce0788f945a7cf7a8bf67c0","observation_id":"4d5a354a-6488-461a-9f54-c20d33929579","resolution":{"observed_at":"2026-08-07T04:07:20.004152Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.12626","last_updated":"2021-09-28T14:01:26Z","snapshot_observed_at":"2026-08-10T11:46:54.503349Z","submitted_at":"2021-08-28T11:12:49Z","title":"HeadlineCause: A Dataset of News Headlines for Detecting Causalities","version":2},"cited_work":{"arxiv_id":"2108.12626","doi":null,"metadata_source":"pith","pith_arxiv_id":"2108.12626","snapshot_observed_at":"2026-08-07T04:07:20.698381Z","title":"HeadlineCause: A Dataset of News Headlines for Detecting Causalities","venue":"cs.CL","work_id":"ed66da77-d02e-4ffb-9b28-0508ceb06dfd","year":2021},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.007788Z"},"links":{"cited_paper":"/paper/2108.12626","citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:20ffcd471c72fb44905298c828672a4943bf223083a4766c1f49775ec3e03029","observation_id":"e43c0a74-479d-4df7-9fc9-b5ecb12fefce","resolution":{"observed_at":"2026-08-07T04:07:20.702081Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1145/3665494","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Causality for Trustworthy Artificial Intelligence: Status, Challenges, and Opportu- nities","venue":"ACM Computing Surveys","work_id":"fa8225be-a437-4d8c-b049-ae2518019e4d","year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.011214Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:4421842d8b37102959495bbbb14f4636f169353bcbb94cba480507146e949579","observation_id":"6a4c1a58-1b4a-4edc-9b07-f06b07d97c0e","resolution":{"observed_at":"2026-08-07T04:07:20.294993Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.122207Z","title":"ARGUABLY @ Causal News Corpus 2022: Contextually Augmented Language Models for Event Causality Identification","venue":null,"work_id":"b8a64d39-e7a0-43bf-a5e8-3f0bcc70fce3","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.014893Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:628af8b6ea84c4e3d8d838d0c16f75b25b9ece1f66a85ac57beeef58e6eabe23","observation_id":"9bb276d8-356c-43b1-bbfa-7d10a89405f8","resolution":{"observed_at":"2026-08-07T04:07:21.125521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"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":"2026-08-07T04:07:20.021125Z","title":"Retrieval-Augmented Generation for Large Language Models: A Survey","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.021125Z"},"links":{"cited_paper":"/paper/2312.10997","citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:649f1646de316f390f3fabf65c4bff5b882e1e8c6b387285b62ff20be21ce19c","observation_id":"859a16d5-2375-4c28-831d-f4cde1bd2380","resolution":{"observed_at":"2026-08-07T04:07:20.021125Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.00309","last_updated":"2025-01-08T05:16:25Z","snapshot_observed_at":"2026-08-07T12:37:34.294206Z","submitted_at":"2024-12-31T06:59:35Z","title":"Retrieval-Augmented Generation with Graphs (GraphRAG)","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.00309","snapshot_observed_at":"2026-08-07T04:07:20.025264Z","title":"Retrieval-Augmented Generation with Graphs (GraphRAG)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.025264Z"},"links":{"cited_paper":"/paper/2501.00309","citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:305039c077e3a7e6be9af8353fda3af5dae8f9d808043fedebb104c98d5ed13c","observation_id":"a140c81e-c2de-44e2-9aff-1d91d0ea16b5","resolution":{"observed_at":"2026-08-07T04:07:20.025264Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.06685","last_updated":"2023-12-09T08:44:41Z","snapshot_observed_at":"2026-07-06T17:00:00.321552Z","submitted_at":"2023-12-09T08:44:41Z","title":"Causal-CoG: A Causal-Effect Look at Context Generation for Boosting Multi-modal Language Models","version":1},"cited_work":{"arxiv_id":"2312.06685","doi":null,"metadata_source":"pith","pith_arxiv_id":"2312.06685","snapshot_observed_at":"2026-08-07T04:07:20.663065Z","title":"Causal-CoG: A Causal-Effect Look at Context Generation for Boosting Multi-modal Language Models","venue":"cs.AI","work_id":"a2b94191-ea7b-4dc5-bf18-a3efb9847c75","year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.028891Z"},"links":{"cited_paper":"/paper/2312.06685","citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:35946a5ef9bc371b146122bca0f43e22f11adc2c2e35f41828701c8b12d5c599","observation_id":"03165f89-5fb4-415e-aa46-ded501cdeebb","resolution":{"observed_at":"2026-08-07T04:07:20.666661Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-031-35051-1_9","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T00:03:56.115653Z","title":"Causal Inference and Natural Language Processing","venue":null,"work_id":"93bbc3af-f721-46e5-a8cc-ac3e0ad755d6","year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.032522Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:e7a2ad948f638ec1339ebec0eb82ef1920da8c5e777728c108462b2901ff5a55","observation_id":"3b13c7b3-0b45-481f-8c0d-bf82f8fbe7ca","resolution":{"observed_at":"2026-08-07T04:07:20.283675Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.098137Z","title":"CSECU-DSG @ Causal News Corpus 2022: Fusion of RoBERTa Transformers Variants for Causal Event Classification","venue":null,"work_id":"62e99336-303a-4030-8688-2ce39ba17486","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.035959Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:35025e39e5e68c7ecd4b0c68c997691c6d8ee1f9c81b800731c147f4318cb5f9","observation_id":"05949f2b-a634-4ed5-a1b6-4013f79f0b15","resolution":{"observed_at":"2026-08-07T04:07:21.101970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.14892","last_updated":"2025-03-17T14:32:08Z","snapshot_observed_at":"2026-08-10T14:47:00.571921Z","submitted_at":"2025-01-24T19:31:06Z","title":"Causal Graphs Meet Thoughts: Enhancing Complex Reasoning in Graph-Augmented LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.14892","snapshot_observed_at":"2026-08-07T04:07:20.039249Z","title":"Causal Graphs Meet Thoughts: Enhancing Complex Reasoning in Graph-Augmented LLMs","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.039249Z"},"links":{"cited_paper":"/paper/2501.14892","citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:ae7a1ac4057b291197d55cca7416409fc6cf0c1212da37b407d51f1ae7aff890","observation_id":"a4ceaf70-db15-4fd5-ac96-4d48ab1355c4","resolution":{"observed_at":"2026-08-07T04:07:20.039249Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.088473Z","title":"NLP4ITF @ Causal News Corpus 2022: Leveraging Linguistic Infor- mation for Event Causality Classification","venue":null,"work_id":"5338b110-8b48-4159-a396-d7e87b174c9c","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.042877Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:19764b814fbb0647a71c1d0b17f9fa90d47769f0be7df0720cabd8455e70df38","observation_id":"e64fe035-bc18-478b-9bba-507447bf6b1f","resolution":{"observed_at":"2026-08-07T04:07:21.091585Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.7717/peerj-cs.1066","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Causal graph extraction from news: a comparative study of time-series causality learning techniques","venue":"PeerJ Computer Science","work_id":"296656fa-a67c-4f29-a049-74f488624930","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.047173Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:096a2e43de7e1c26da15f61ce3fcc9dde913c1ca65b04f9eb08ae811c5301b73","observation_id":"660cf45d-683b-4aef-9edd-fe21ed1503c9","resolution":{"observed_at":"2026-08-07T04:07:20.272981Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.050457Z","title":"Causality: Models, Reasoning, and Inference","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.050457Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:9a44a6e960e51740dc5505fbb6d64cfa58738646c8d8eb92775b270d10f83010","observation_id":"7260ceae-7eed-475d-bbc0-68e6a414d342","resolution":{"observed_at":"2026-08-07T04:07:20.050457Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.079375Z","title":"Iden- tifying Predictive Causal Factors from News Streams","venue":null,"work_id":"3e846bb5-9996-4e61-87af-edc10590844d","year":2019},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.053839Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:585419f7c3169599ce4d79dee66f2ebf888dc9b0403d4c4a9fcd44ebe4206ef4","observation_id":"824cd6e8-f8a9-49d0-a63d-30fcf760be7b","resolution":{"observed_at":"2026-08-07T04:07:21.082346Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.057457Z","title":"Causal Understanding of Fake News Dissemination on Social Media","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.057457Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:393e9d9585bf9d72aca39cbccc5ac704f35857a3a583f14998a8287a5fba79f3","observation_id":"276b8c6a-d9ed-4db5-aeb5-3108df691965","resolution":{"observed_at":"2026-08-07T04:07:20.057457Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.069348Z","title":"NoisyAnnot@ Causal News Corpus 2022: Causality Detection using Multiple Annotation Decisions","venue":null,"work_id":"4ca15971-2c68-4357-8099-6f20d2558297","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.060787Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:6608397ef7f31f52cfa21ba6556aea8c2fe891b1fd5dbcb00d2eb5ce66a5bece","observation_id":"5897dc4a-725c-4632-824f-01caf03d3507","resolution":{"observed_at":"2026-08-07T04:07:21.072572Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.059626Z","title":"A survey on extraction of causal relations from nat- ural language text","venue":null,"work_id":"7ae7e5db-e67d-415f-afb0-fd2aefb76e51","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.064214Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:1cb8a1ed27e5832c6aa34e55a9f0996abbc427e1071bf666bf3c5f419f504d8b","observation_id":"69995901-247b-4b1d-874a-5b62000125dc","resolution":{"observed_at":"2026-08-07T04:07:21.062875Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.049030Z","title":"Text to causal knowledge graph: A framework to synthesize knowledge from unstructured business texts into causal graphs","venue":null,"work_id":"5c8a63f3-1df2-4619-a841-5850bce4be87","year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.067775Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:336020d11f72def6d11e16f3fa0abbb207637140d52eb5f2a1ea31c40b3c17c7","observation_id":"79c8a754-5016-4914-a109-49a41574a1aa","resolution":{"observed_at":"2026-08-07T04:07:21.052772Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.00903","last_updated":"2026-06-11T16:46:27Z","snapshot_observed_at":"2026-08-02T00:45:07.688016Z","submitted_at":"2024-10-01T17:46:21Z","title":"Causal Inference with Generative Artificial Intelligence: Application to Texts as Treatments","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.00903","snapshot_observed_at":"2026-08-07T04:07:20.070948Z","title":"Causal Representation Learning with Generative Artificial Intelligence: Application to Texts as Treatments","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.070948Z"},"links":{"cited_paper":"/paper/2410.00903","citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:a3936baf7775ae6c69505c5c1371cc06997b4ae95d02a662d4892fe8da3eedd5","observation_id":"903aa6e4-037a-4cdc-926e-33cc7a5593dc","resolution":{"observed_at":"2026-08-07T04:07:20.070948Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.11714","last_updated":"2022-04-25T15:14:07Z","snapshot_observed_at":"2026-07-06T13:03:32.889984Z","submitted_at":"2022-04-25T15:14:07Z","title":"The Causal News Corpus: Annotating Causal Relations in Event Sentences from News","version":1},"cited_work":{"arxiv_id":"2204.11714","doi":null,"metadata_source":"pith","pith_arxiv_id":"2204.11714","snapshot_observed_at":"2026-08-07T04:07:20.551609Z","title":"The Causal News Corpus: Annotating Causal Relations in Event Sentences from News","venue":"cs.CL","work_id":"4c05b64c-1352-4bc5-90d9-1732dfa2f610","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.074939Z"},"links":{"cited_paper":"/paper/2204.11714","citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:b21954395883d77f0aca8f7dc54afc33fbcec1a5bbed1d823eef98f2c30f6f94","observation_id":"25ee4723-56a3-41be-8631-5c3f4251ee55","resolution":{"observed_at":"2026-08-07T04:07:20.555895Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.078617Z","title":"Causality for Machine Learning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.078617Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:5c94b8e5fa098d956161e93369444fb5e78af15c41c3a700bc6808d03e25b7d2","observation_id":"8b8f71da-f290-4b8d-ae0e-594ae75df5c7","resolution":{"observed_at":"2026-08-07T04:07:20.078617Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.037650Z","title":"Constructing and interpreting causal knowledge graphs from news","venue":null,"work_id":"c765da7e-381c-4737-87dd-1b728b8e8bab","year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.082091Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:7a19e8389d559194d69a124d5167ac8ff81ab119d3600d400713ed88f0d9dac3","observation_id":"d87fbb81-1094-43b9-b6a5-374a127306d0","resolution":{"observed_at":"2026-08-07T04:07:21.041057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.00050","last_updated":"2024-08-20T17:16:20Z","snapshot_observed_at":"2026-07-06T15:21:19.790554Z","submitted_at":"2023-04-28T19:00:43Z","title":"Causal Reasoning and Large Language Models: Opening a New Frontier for Causality","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.00050","snapshot_observed_at":"2026-08-07T04:07:20.085171Z","title":"Causal reasoning and large language models: Opening a new frontier for causality","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.085171Z"},"links":{"cited_paper":"/paper/2305.00050","citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:eab0a239059a2910f05cb3286947085c9e2cabf9cc38a341eb0f2fcc6e3c574b","observation_id":"3f87f16e-2595-4b6d-bfb6-3864ab78235f","resolution":{"observed_at":"2026-08-07T04:07:20.085171Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.026066Z","title":"Causal Reasoning in Large Language Models using Causal Graph Retrieval Augmented Generation","venue":null,"work_id":"20020ef8-6c37-4bad-bd2b-18afc55e36b4","year":2024},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.088643Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:b79ef913b448abbeabafbdc4378d4c296e8dfd77badbbb2975f595e7b695fd7e","observation_id":"de3a2a76-e665-4fc4-a154-a764469a45bf","resolution":{"observed_at":"2026-08-07T04:07:21.029712Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.016004Z","title":"Groq - Accelerating AI Workloads","venue":null,"work_id":"05f8a972-36f9-422c-9d4f-00232992bb00","year":2024},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.091492Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:4e5a19e5c4eff8ed253e999509aca096a3a19edd26e4db9fc9b40b141d0ac3c4","observation_id":"723a1cb7-8492-4a96-bd02-016eaf5937d3","resolution":{"observed_at":"2026-08-07T04:07:21.019628Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.094571Z","title":"A Survey of Learning Causality with Data: Problems and Methods","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.094571Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:f95fbc71b6a3745ae8b72ca41c6fd25114e2eaffc914f7d629f2de943790275d","observation_id":"d21ffb0a-4519-4456-8723-8b54db2f50f1","resolution":{"observed_at":"2026-08-07T04:07:20.094571Z","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":"2026-08-07T04:07:20.097917Z","title":"Learning Causality for News Events Prediction","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.097917Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:c96653754d7b592d03b18d97f17bf959c193a77bf4e447957df32a2e93422a3e","observation_id":"6e282807-9de9-4904-b4f4-17472497fe95","resolution":{"observed_at":"2026-08-07T04:07:20.097917Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.005500Z","title":"Investigating causal understanding in LLMs","venue":null,"work_id":"e7ffe442-35b5-4922-be62-e58a63541724","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.100772Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:dbb6f2dc58fffb8a3d0231027d33d1d8545aaf5500b72fda3ba0c28707e017eb","observation_id":"45df3571-7097-4ec7-83c6-0a3ca218e874","resolution":{"observed_at":"2026-08-07T04:07:21.009099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.993196Z","title":"Causal Intervention and Counterfactual Reasoning for Multi-modal Fake News Detection","venue":null,"work_id":"9273c1fc-d496-4647-81e0-51e8aae02484","year":null},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.103563Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:cabd8acef9bfd2026d8301f964d189f60a3764c2d5aefbbcb9a1843d6409931d","observation_id":"80a82777-1dd4-4ce9-8418-3c4584ffafd7","resolution":{"observed_at":"2026-08-07T04:07:20.998313Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1177/09636625211005249","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"The explanation of a complex problem: A content analysis of causality in cancer news","venue":"Public Understanding of Science","work_id":"75631c58-3623-446c-8e9c-4361919276ee","year":2021},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.110130Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:eb9326b3dfaf065dc5c4d21ea712a519cba9163fe8a5be22fc8ee744af8d248d","observation_id":"70817d11-065a-4c1f-ac24-6574ff050489","resolution":{"observed_at":"2026-08-07T04:07:20.248961Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.971556Z","title":"Chain-of-thought prompting elicits reasoning in large language models","venue":null,"work_id":"ea223f82-14cf-47de-ab6f-7343d679646d","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.112946Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:f2815e6fb94561f6979ff07778d7f97d123f1526414ceada423e435dc18d3e10","observation_id":"c7359645-d786-45f4-8d5f-ae5f04d4644c","resolution":{"observed_at":"2026-08-07T04:07:20.975109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.13067","last_updated":"2023-08-24T20:23:13Z","snapshot_observed_at":"2026-08-10T11:46:17.764088Z","submitted_at":"2023-08-24T20:23:13Z","title":"Causal Parrots: Large Language Models May Talk Causality But Are Not Causal","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.13067","snapshot_observed_at":"2026-08-07T04:07:20.115884Z","title":"Causal parrots: Large language models may talk causality but are not causal","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.115884Z"},"links":{"cited_paper":"/paper/2308.13067","citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:88411f8aecfe4eb2e88cb8f70e867b1cce54552e822af9bb995528d8fa0653e9","observation_id":"821e719b-6e79-4401-b4f3-062a6d316a76","resolution":{"observed_at":"2026-08-07T04:07:20.115884Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.16899","last_updated":"2025-04-09T04:44:48Z","snapshot_observed_at":"2026-07-06T18:36:16.828338Z","submitted_at":"2024-05-29T09:06:18Z","title":"Prompting or Fine-tuning? Exploring Large Language Models for Causal Graph Validation","version":2},"cited_work":{"arxiv_id":"2406.16899","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.16899","snapshot_observed_at":"2026-08-07T04:07:20.369030Z","title":"Prompting or Fine-tuning? Exploring Large Language Models for Causal Graph Validation","venue":"cs.CL","work_id":"f54404d5-2e77-4798-be5d-7943770fd5c3","year":2024},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.119069Z"},"links":{"cited_paper":"/paper/2406.16899","citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:9411b64c298c39d88d83a4cb7d6e3b686e02693f295428772c597b6b6a68c89d","observation_id":"24b2bb8a-0dc9-4bc0-b729-58dca40a4514","resolution":{"observed_at":"2026-08-07T04:07:20.374730Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1609/aaaiss.v4i1.31764","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Cause and Effect: Can Large Language Models Truly Understand Causality?","venue":"Proceedings of the AAAI Symposium Series","work_id":"6f56ff86-90a6-413b-b11d-a3cad6f777b3","year":2024},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.122132Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:fac6310a8172b4cda254c688ca4a82c4d7acae60063ce6049aa782b7867db811","observation_id":"bf77b822-8fe9-4e6c-942e-48df428068df","resolution":{"observed_at":"2026-08-07T04:07:20.237248Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.125166Z","title":"Evaluation Methods and Measures for Causal Learning Algorithms","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.125166Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:d2ad82592ea18f716854db3665f9fcc5fe5f920cd1553af8025e42c12ab9adae","observation_id":"1a14294c-b0ac-4893-8fcd-c376c450b306","resolution":{"observed_at":"2026-08-07T04:07:20.125166Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.950665Z","title":"Pairwise Causality Guided Transformers for Event Sequences","venue":null,"work_id":"e3c5fd00-1423-49d5-9831-7dcea1dad5d7","year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.128260Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:8e96a4147260f8037675a4083d5bd0e8a09be2b8a6b23448e04197fa75e3fc8b","observation_id":"c8fc6854-e4d5-48f3-ba0f-1a4d6761909e","resolution":{"observed_at":"2026-08-07T04:07:20.964289Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.914370Z","title":"all-MiniLM-L6-v2 - Sentence Transformers","venue":null,"work_id":"738f1c62-9176-484c-a65f-f3f49bb3b529","year":2024},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.131913Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:836b4c4c4d03c1c9532957508c71200c9b724ab985dc6ffecab3d638bcc7805e","observation_id":"2d97e2a7-0a28-473b-9340-7402b5d320c3","resolution":{"observed_at":"2026-08-07T04:07:20.928172Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.874404Z","title":"A survey on extraction of causal relations from natural language text","venue":null,"work_id":"8365066f-84f9-472f-ae1a-45c38b93c0c8","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.134862Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:e39e697071b5debcca664e1e26f819ca70fb6941213b57a621f1b4c153f534cd","observation_id":"5a87e7e4-4f44-4561-b34c-b62358549950","resolution":{"observed_at":"2026-08-07T04:07:20.891592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.857813Z","title":"Causal knowledge extraction from long text maintenance documents","venue":null,"work_id":"2a4b30fb-b0f2-4b71-8129-659444b8ff2b","year":2024},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.137910Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:ae99cb15f625654e8b23c5ec5434af929d10bb93e6db4cc07baebdd9acf943f9","observation_id":"b126aeff-3f4a-4886-8400-7310ed04ee02","resolution":{"observed_at":"2026-08-07T04:07:20.862197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.846490Z","title":"Causal-CoG: A Causal-Effect Look at Context Generation for Boosting Multi-modal Language Models","venue":null,"work_id":"d557c57e-4229-4e8e-9ae8-94444cba6585","year":2024},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.140956Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:5079af707d7f10184e6ca21d92536ab7446abe3f2e04fc1296de45cf159f27df","observation_id":"457151bc-9f4f-42f4-a353-1c2949230479","resolution":{"observed_at":"2026-08-07T04:07:20.849973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.833431Z","title":"CHEER: Centrality-aware high-order event reasoning network for document-level event causality identification","venue":null,"work_id":"de0ff543-e12e-4d54-9293-2a407049f8fc","year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.144278Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:9a36a0b518ac22323171104b80cb83fd8333b45c0df82777ac71fb8a5fe48965","observation_id":"bca616a4-ffbc-4c5e-837d-82be89ddc07e","resolution":{"observed_at":"2026-08-07T04:07:20.837534Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.147938Z","title":"Root Cause Analysis in Microservice Using Neural Granger Causal Discovery","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.147938Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:e91e9de92cb88d9709c2d1a2d182ed0f0a844310ebe148ebb065098237efc1af","observation_id":"78568b44-fdff-489e-b615-645be74dc1af","resolution":{"observed_at":"2026-08-07T04:07:20.147938Z","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":"10.1007/s11227-021-04097-5","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Financial Causal Sentence Recognition Based on BERT-CNN Text Classification","venue":"The Journal of Supercomputing","work_id":"d1adcb39-6700-4f59-95e1-87599451956e","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.151254Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:4bdcdbeef7602a607ac758b59baf375dc8c044875d06e9ecde8ebf39db1f92b4","observation_id":"925256d2-79b5-42c4-96ed-f6aee437f461","resolution":{"observed_at":"2026-08-07T04:07:20.218866Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.822313Z","title":"The Financial Document Causality Detection Shared Task (FinCausal 2023)","venue":null,"work_id":"d627d763-7233-4286-8f30-b7ffcc651c87","year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.154373Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:5518f4bbc9d962d5ab456c9ce48deb301ea7ffab4683a8fa2890420b92529f18","observation_id":"f179c511-4db5-49e9-95e0-01c5f86f47fe","resolution":{"observed_at":"2026-08-07T04:07:20.826000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.158032Z","title":"Event Causality Extraction via Implicit Cause-Effect Interactions","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.158032Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:29aeec425896df5dc53b78e9daaf853ee95814e0d9a5697688dc66d2873791f0","observation_id":"58d33168-ed8f-4e02-aa62-b1f5a414016c","resolution":{"observed_at":"2026-08-07T04:07:20.158032Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1016/j.dcan.2023.02.005","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"End-to-end multi-granulation causality extraction model","venue":"Digital Communications and Networks","work_id":"e765ade5-0cae-4568-a15e-7e15f326cbe6","year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.161282Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:c4c24e38831ec490e89a05077a054ad8550f7bad3877b2c54a462980b4fcbb17","observation_id":"62c05f01-da2b-463b-8284-ffd09db7da07","resolution":{"observed_at":"2026-08-07T04:07:20.199782Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.810267Z","title":"Neo4j Resources","venue":null,"work_id":"d619032a-7d5e-4344-9223-69fd0f322707","year":2024},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.164955Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:6a2e544b5fc593e1ba6c27ea7496aaa1db5a68d703a6aa0b0cf47c45bc889dee","observation_id":"abd5fba2-d5c1-47f5-b746-5c2b7a88192a","resolution":{"observed_at":"2026-08-07T04:07:20.814217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:21.109545Z","title":null,"venue":null,"work_id":"2e445a06-d175-4b93-a1c9-638805b22408","year":2022},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.018057Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:b347eca9b87a990d530b60de06bfe7ced8a1f1cb825a691fe0854bdbbd6d6183","observation_id":"de32066b-9cec-488e-a7ad-3259da379634","resolution":{"observed_at":"2026-08-07T04:07:21.114897Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:07:20.982845Z","title":"17 A PREPRINT - AUGUST 28, 2025","venue":null,"work_id":"8107b770-9d81-41fe-ab3c-f1fafb48694f","year":2023},"citing_paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T04:07:20.107072Z"},"links":{"citing_paper":"/paper/2506.11600"},"observation_digest":"sha256:07ca2db913bb6a594f5566481b80ae45518c8acac548f63cb0dd70eee34a3389","observation_id":"093cab93-b1ba-44b3-94bb-506c4408a0a8","resolution":{"observed_at":"2026-08-07T04:07:20.986179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.11600","last_updated":"2025-06-13T09:09:08Z","latest_version":1,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-08T11:22:34.761135Z","submitted_at":"2025-06-13T09:09:08Z","title":"GraphRAG-Causal: A novel graph-augmented framework for causal reasoning and annotation in news"},"reference_resolution":{"displayed":54,"state_counts":{"malformed_identifier":2,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":11,"verified_fuzzy":24},"total_outbound_references":54},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2506.11600."}