{"as_of":"2026-08-08T04:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:694f4ae45d39d99352586b72aaabc2dfdc3d0444cd4e49b4dcfc3581335255f0","coverage":[{"denominator":69,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":69,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:48:08.762913Z","state":"measured"},{"denominator":69,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":69,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2506.09566/citation-record","integrity":"/paper/2506.09566/integrity","json":"/paper/2506.09566/citation-record.json","paper":"/paper/2506.09566"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:48:09.324234Z","title":"Llama3.1:A405b-parameteropen-sourcelanguagemodel.https: //github.com/facebookresearch/llama, 2024","venue":null,"work_id":"35b37a3e-d839-4e35-9e80-6667b961ea7f","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.597634Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:29e1771e3e799c7cbfd2409837ae3277ba022a4a8aa82f175f0b4144f3f36e7c","observation_id":"89d469be-920c-4464-851f-1a24f6b61035","resolution":{"observed_at":"2026-08-07T04:48:09.326671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.317168Z","title":"Mixtral 8x22b: Sparse mixture-of-experts model with 141b parameters.https://github.com/mistralai/Mixtral, 2024","venue":null,"work_id":"1193ff72-42e4-4016-b775-6c3c352ccfb1","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.600548Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:e72d46acd4ba894375bfe5406cdb2367d257ba2de196bbbb65e5245b637fa06c","observation_id":"61fb91a4-d165-4465-bb21-9dbd68bc6ed4","resolution":{"observed_at":"2026-08-07T04:48:09.319772Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.310297Z","title":"Language model guided knowledge graph embeddings.IEEE Access, 10:76008–76020, 2022","venue":null,"work_id":"963cb2ed-1b4e-4fee-a702-4138eaf85cac","year":2022},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.603348Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:2f600077e5f045f6b20a33504ad79d62bb5390415daf7abcbcc1c8f4fb27d89b","observation_id":"2478c9f7-58b8-4727-81cf-1132d6e0e820","resolution":{"observed_at":"2026-08-07T04:48:09.312795Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.302830Z","title":"Neural machine translation by jointly learning to align and translate","venue":null,"work_id":"205f6cb9-8b2d-4a91-bea6-cb5d8aa86bd5","year":2015},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.606243Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:2ba25fdad86dc3083c932dfcbfcd5369fbaea38209cd566e77ad85055359632a","observation_id":"8bb9ebe1-7af5-41b1-a14b-034d25d2a5f7","resolution":{"observed_at":"2026-08-07T04:48:09.305536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.295874Z","title":"SciBERT: A pretrained language model for scientific text","venue":null,"work_id":"6dbc2fdd-9cad-49f8-be64-c412eb955ea3","year":2019},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.608821Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:539a75df407badbb9c6f126039cf6bd2bb825055746e2fa92fac3524b5836ed5","observation_id":"5cb9e543-962a-4a93-a3dd-963b53719359","resolution":{"observed_at":"2026-08-07T04:48:09.298660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.289089Z","title":"Courville, and Pascal Vincent","venue":null,"work_id":"4d43e31e-b7f5-467f-8c9d-631345732b4c","year":2013},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.611326Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:546c4d25851365c36d1c60566524c2eeecb7049a39e740ecaf47e2333aa62b89","observation_id":"ce79ba7c-315c-4786-91a9-5bfeea8e717f","resolution":{"observed_at":"2026-08-07T04:48:09.291521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.07258","last_updated":"2022-07-12T23:45:14Z","snapshot_observed_at":"2026-08-02T09:20:40.804790Z","submitted_at":"2021-08-16T17:50:08Z","title":"On the Opportunities and Risks of Foundation Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.07258","snapshot_observed_at":"2026-08-07T04:48:08.614029Z","title":"On the opportunities and risks of foundation models","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.614029Z"},"links":{"cited_paper":"/paper/2108.07258","citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:f6782ab87a66bdfd21a749b9402d7fef3b2fb2972943766bb28cbee8fa66f735","observation_id":"14389e9f-9e94-4686-ad67-3fe17b8924af","resolution":{"observed_at":"2026-08-07T04:48:08.614029Z","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":"2026-08-07T04:48:09.282188Z","title":null,"venue":null,"work_id":"33c72ed8-243f-4fba-8de5-d6265d07f962","year":2020},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.616917Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:a2c7dc0c243c8cfd9e91a30a5b785759f7f016d22ca77d73d0bb76d3eadc7e01","observation_id":"85832cc1-e677-44fe-968f-f2669a3e1c27","resolution":{"observed_at":"2026-08-07T04:48:09.284448Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.275539Z","title":null,"venue":null,"work_id":"1445a93f-190d-4761-ad57-70637e520559","year":2020},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.619265Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:445c2895dacd48a0ed5f3ac5241a252a2332c920157d4f7e8e300000a452469e","observation_id":"2084df79-730c-47a7-ab69-f69eb6002c30","resolution":{"observed_at":"2026-08-07T04:48:09.277909Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.268253Z","title":"PairRE: Knowl- edge graph embeddings via paired relation vectors","venue":null,"work_id":"d3278d3f-70ee-433f-9832-1cc0ad81ba19","year":2021},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.621435Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:4df65d9e90359356bb1e19e35e3a383420f1913e9cf64ef3cca1d7af146452f4","observation_id":"58c069fb-a254-43ef-ac7c-9de12d970a8a","resolution":{"observed_at":"2026-08-07T04:48:09.270859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.261082Z","title":"SAC-KG: Exploiting large language models as skilled automatic construc- torsfordomainknowledgegraph","venue":null,"work_id":"fb20bf58-0cb5-4c2c-a588-83f90ce73ff4","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.623807Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:7b825e9f253f4406c0b87260cfe00751d21bc101ca7fe6238993757b5c56fb43","observation_id":"3522d8ae-b5ed-4fee-b617-779e75948f74","resolution":{"observed_at":"2026-08-07T04:48:09.263591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.253548Z","title":"Augmenting multimodal llms with self-reflective tokens for knowledge-based visual question answering, 2025","venue":null,"work_id":"0f1e4c49-6071-4671-9e25-ec822dfd0737","year":2025},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.626436Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:ba926f1dc1855ba9cff122db25f2c38932272e932a02117c2c0bbcef8318f339","observation_id":"68bfd77a-778a-4bb3-b2d9-d18d766e10f9","resolution":{"observed_at":"2026-08-07T04:48:09.256502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.245381Z","title":"Command r: A retrieval-augmented open source language model","venue":null,"work_id":"55fd6d5d-be98-4e0e-ae36-6b9ba153c2cc","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.628870Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:4f61bc9665c41153c5c24f25febe7eb9f1be4c6eb8c26e371afa86a01c703951","observation_id":"736456ff-2fcc-4586-8ed7-30ecf652292f","resolution":{"observed_at":"2026-08-07T04:48:09.248129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.238358Z","title":"Command r+: Enhanced version for large-scale tasks.https: //github.com/cohere-ai/command-r-plus, 2024","venue":null,"work_id":"d71d71b1-8750-4a52-a2ed-c65850341759","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.631239Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:383795c5f80ff4f04ae3be0a06185fc8eafa6b74d0ed441fe2a882ede70ded62","observation_id":"60069522-e7c3-4d4e-9009-6624c5b41d83","resolution":{"observed_at":"2026-08-07T04:48:09.241082Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.229963Z","title":"Gemma: Lightweight llms in 2b and 7b sizes.https: //github.com/google-research/gemma, 2024","venue":null,"work_id":"9c5cadc6-f5cd-4742-8a44-f3f4412b42f8","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.633596Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:0db25d4bc7ac2eaa1ea9c162213c55adfd089be7861acbcf52b37e0b2aab6817","observation_id":"ba133355-ed0f-4abd-9686-dad15ebbe061","resolution":{"observed_at":"2026-08-07T04:48:09.232702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.222170Z","title":"Deepseek-v3: Scaling open-source llms via efficient retrieval","venue":null,"work_id":"f04b2a3e-588e-4e6e-91fc-9f55c15d2c95","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.635902Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:939ece63422bead38f6b9d289dce902108957e726cfcff438a49689827022451","observation_id":"d69a87c9-09e9-4e33-bdc1-069934cc4ccd","resolution":{"observed_at":"2026-08-07T04:48:09.224980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.214794Z","title":"BERT: Pre-training of deep bidirectional transformers for language under- standing","venue":null,"work_id":"d845287f-7dfa-46d9-b692-ab783ae2ce70","year":2019},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.638206Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:0f7d7dbd8666a702bebd27fd4f1e33b9ed7ec988925f092dffa9151dd86a70dd","observation_id":"a946631a-3983-4e2f-aa72-9181f3b98fa7","resolution":{"observed_at":"2026-08-07T04:48:09.217716Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.207186Z","title":"Core techniques of question answering systems over knowledge bases: A survey","venue":null,"work_id":"2c643e6d-0b75-4f75-a5f2-3ee0f130ae63","year":2018},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.640347Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:1c73da782c555996104ad0735a9a24dcfc0a308fdb91ebfc8684edb8113d6d6a","observation_id":"5962bea1-9a52-4b1c-b211-c94f000454f5","resolution":{"observed_at":"2026-08-07T04:48:09.209903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.199466Z","title":"Knowledge vault: a web-scale approach to probabilistic knowledge fusion","venue":null,"work_id":"599b1d8a-3b65-43b3-9bf4-f8ee161198b7","year":2014},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.642564Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:4a848133e45547ee28d60af71c29fdc54fcc2a6d965377cbbd8a6223746f9b5d","observation_id":"7e9974e3-5815-4965-8c9b-9e5a8cac6e24","resolution":{"observed_at":"2026-08-07T04:48:09.202217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.192390Z","title":"Enrich- ing contextualized language model from knowledge graph for biomedical information extraction.Briefings in bioinformatics, 22(3):bbaa110, 2021","venue":null,"work_id":"5b01f368-b3ec-4ede-89c4-55f691f72071","year":2021},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.644864Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:be7be8b21e9d501149694881ab50e7003ab51cbc7f27d0d45f196e4907c53928","observation_id":"c2c972ff-a03e-48b0-b367-3c7f4f18cb4d","resolution":{"observed_at":"2026-08-07T04:48:09.194938Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.184907Z","title":"Comprehensive analysis of knowledge graph embedding techniques benchmarked on link prediction.Electronics, 11(23):3866, 2022","venue":null,"work_id":"544e2470-fe44-49c0-a208-662971f349fc","year":2022},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.647405Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:00b83ba857a47970a247c66a4b86003cc699075a41bbd5bc1836ea8f656f88c9","observation_id":"f7b2795f-c413-48d7-844e-67b42e3d554c","resolution":{"observed_at":"2026-08-07T04:48:09.187663Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.177163Z","title":"A survey on knowledge graph-based recommender sys- tems.IEEE Transactions on Knowledge and Data Engineering, 34(8):3549– 3568, 2022","venue":null,"work_id":"ba725ddb-eee5-4a95-9332-244051d4b312","year":2022},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.649761Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:1b67399d87b0c525c99fd4dcf32292421176acc6599af87897ada771a1628bab","observation_id":"e204620a-6721-4ed6-aca9-f2d0d4636345","resolution":{"observed_at":"2026-08-07T04:48:09.179869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.170055Z","title":"Rashid, Anisa Rula, Lukas Schmelzeisen, Juan Sequeda, Steffen Staab, and Antoine Zimmermann.Knowledge Graphs","venue":null,"work_id":"8b9f2aa6-818a-4859-8ad8-42b94395d0f8","year":2021},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.652018Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:5ead56b635ccf6300376dd0b1f6a345069e153b2314daf4d5e98f3c23c51bbd3","observation_id":"e7752068-09ae-463c-9cd4-48b583c4cdf2","resolution":{"observed_at":"2026-08-07T04:48:09.172772Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.162590Z","title":"Knowledge graphs.ACM Computing Surveys (Csur), 54(4):1–37, 2021","venue":null,"work_id":"56daa5c4-ea36-4200-9e35-3d24b116ad36","year":2021},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.654406Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:bab47600077856ef50bbad0d2ed0034f22d194a7f04e156ccac36279dbd7cd8a","observation_id":"01d6e2e7-3bb9-4772-9d1e-36425a894d14","resolution":{"observed_at":"2026-08-07T04:48:09.165108Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.155267Z","title":"A survey of knowledge-enhanced pre-trained language models.IEEE Trans- actions on Knowledge and Data Engineering, 36:1413–1430, 2023","venue":null,"work_id":"e63474ba-b7da-4999-a6a3-3c12281ddadf","year":2023},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.656664Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:112cdd7960d0d52606c7042938ab6a90fc9c596aa51b9660650eac57f63615b4","observation_id":"c227afbe-c72f-46c6-9c93-802756c95552","resolution":{"observed_at":"2026-08-07T04:48:09.158142Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.148141Z","title":"Can llms be good graph judger for knowledge graph construction?, 2025","venue":null,"work_id":"57641a4a-7204-4dc0-9784-efe643ccba7f","year":2025},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.658890Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:c07826544f33b905cb4fb48392886ddc9aa3ee4a1bf4669cefe54fdf95ce95f3","observation_id":"d6d8f003-3a56-41ed-af51-85f1ae2e73af","resolution":{"observed_at":"2026-08-07T04:48:09.150698Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.140862Z","title":"Improving knowledge graph em- bedding using locally and globally attentive relation paths","venue":null,"work_id":"b890bcdf-1193-49f4-ade3-ba0fe16c87ed","year":2020},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.661203Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:28099786442a04cd1055fcc7b2e1389242f97d24e2203a3b3ef7caadd5bf2725","observation_id":"f5de0058-621e-4cbe-a7ee-9ef07540d8c0","resolution":{"observed_at":"2026-08-07T04:48:09.143477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.133620Z","title":"Carte: pretraining and transfer for tabular learning","venue":null,"work_id":"a38f8ca4-3dff-4d2c-b697-41e52d476bc5","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.663806Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:938b6209fb8a865cb7810a83c34540aacd27dba94b3b2688fbd6d1f490a77942","observation_id":"806184c2-50bb-473e-8356-b6833a08dd7e","resolution":{"observed_at":"2026-08-07T04:48:09.136231Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.124957Z","title":"Knowledge graph informed fake news classification via heterogeneous representation ensembles.Neurocomputing, 496:208–226, 2022","venue":null,"work_id":"967d5a03-ae58-47b7-9949-3bb066b1c972","year":2022},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.666072Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:ae83416182a4b02c7438e56f500fce645e99d592279dfa79d5fae1a8e84dbfd1","observation_id":"13b9088a-44cf-464f-85f7-b68eb10bc372","resolution":{"observed_at":"2026-08-07T04:48:09.128720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.117216Z","title":"Jamba: A production-grade hybrid llm.https://github.com/ ai21labs/Jamba, 2024","venue":null,"work_id":"53e23cc2-e895-4008-9453-2887171686ae","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.668347Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:d17f563fe9ce9698fda46b9b8cb7e15c63873a44f34cebed989383f79eb69c58","observation_id":"6f13331a-d6c5-4854-8c0e-2efc9806b305","resolution":{"observed_at":"2026-08-07T04:48:09.120005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.18415","last_updated":"2024-10-24T04:01:40Z","snapshot_observed_at":"2026-08-04T16:12:44.810124Z","submitted_at":"2024-10-24T04:01:40Z","title":"Decoding on Graphs: Faithful and Sound Reasoning on Knowledge Graphs through Generation of Well-Formed Chains","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.18415","snapshot_observed_at":"2026-08-07T04:48:08.670603Z","title":"Decoding on Graphs: Faithful and Sound Reasoning on Knowl- edge Graphs through Generation of Well-Formed Chains.arXiv preprint arXiv:2410.18415, 2024","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.670603Z"},"links":{"cited_paper":"/paper/2410.18415","citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:ba0359174b6d73430b840db700e0f4812f7d6222c0eb07ea89c2f70b588bfa8d","observation_id":"48a976cb-8fcb-4038-8ce8-c00192f4b197","resolution":{"observed_at":"2026-08-07T04:48:08.670603Z","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":"2026-08-07T04:48:09.108484Z","title":"TransE-MTP: A new representation learn- ing method for knowledge graph embedding with multi-translation princi- ples and TransE.Electronics, 13(16):3171, 2024","venue":null,"work_id":"db3a16b6-1365-4768-b3a3-e033f7ccb336","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.673361Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:6e594ce3c405dccf7cb4fb2bf3b623c0c919ab73829d131752ba5ae6b785781a","observation_id":"c93faddc-cf9d-4b0a-b0c2-43eb27d01918","resolution":{"observed_at":"2026-08-07T04:48:09.111453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.100031Z","title":"Dual Reason- ing: A GNN-LLM Collaborative Framework for Knowledge Graph Question Answering","venue":null,"work_id":"15a4ccce-5822-41d8-a2de-40cb4537e3c0","year":2025},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.675615Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:025eb0b170c1ab4f513178ebc79b64bb16d83a9c4eaa5c4612ca412af1dc269d","observation_id":"7efdc4b2-eef5-4a26-86e7-ba4ce73d8635","resolution":{"observed_at":"2026-08-07T04:48:09.102780Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.090986Z","title":"K-BERT: enabling language representation with knowl- edge graph","venue":null,"work_id":"315aa6b7-e9d9-4d69-b540-98ebb37464a4","year":2020},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.678375Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:b9a421eff82323391ef6c2a370cbf528f430a09aa43525e0be517a6df43679bb","observation_id":"0a091a61-7fc0-42bb-87b8-697f422573e8","resolution":{"observed_at":"2026-08-07T04:48:09.094274Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10805","last_updated":"2025-02-10T03:16:09Z","snapshot_observed_at":"2026-08-01T01:40:45.155448Z","submitted_at":"2024-07-15T15:20:40Z","title":"Think-on-Graph 2.0: Deep and Faithful Large Language Model Reasoning with Knowledge-guided Retrieval Augmented Generation","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10805","snapshot_observed_at":"2026-08-07T04:48:08.680583Z","title":"Think-on-Graph 2.0: Deep and Interpretable Large Language Model Reasoning with Knowledge Graph-guided Retrieval.arXiv preprint arXiv:2407.10805, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.680583Z"},"links":{"cited_paper":"/paper/2407.10805","citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:b141835254bae76dfdf77f0107bc39bf81d3cd030186e1edce90ae861a7b692e","observation_id":"bc272e87-0bbb-4186-ab94-2e17387b5b68","resolution":{"observed_at":"2026-08-07T04:48:08.680583Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21358","last_updated":"2024-07-31T06:01:24Z","snapshot_observed_at":"2026-07-06T18:54:49.923926Z","submitted_at":"2024-07-31T06:01:24Z","title":"Tree-of-Traversals: A Zero-Shot Reasoning Algorithm for Augmenting Black-box Language Models with Knowledge Graphs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21358","snapshot_observed_at":"2026-08-07T04:48:08.683344Z","title":"Tree-of-Traversals: A Zero-Shot Reasoning Algorithm for Augmenting Black-box Language Models with Knowledge Graphs.arXiv preprint arXiv:2407.21358, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.683344Z"},"links":{"cited_paper":"/paper/2407.21358","citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:b07ad0a237bd58dcaee418f1c94755ba57bd201248ea8f993c3d4c78cac0ca4a","observation_id":"0fd7e21e-6b72-4624-b4c8-339a94a2dfc0","resolution":{"observed_at":"2026-08-07T04:48:08.683344Z","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":"2026-08-07T04:48:09.082064Z","title":"Phi-3 medium: A 14b-parameter language model.https:// github.com/microsoft/phi, 2024","venue":null,"work_id":"fdccae1c-cae2-4d0a-9352-4f0813e7d924","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.685824Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:0a7d1da4d83b42b35e3eef00b2bc328ed97c8e63eb66e2780092555f53e7a088","observation_id":"e3924bce-22fc-40ee-b024-cd118e6b883e","resolution":{"observed_at":"2026-08-07T04:48:09.085038Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.074097Z","title":"Corrado, and Jeffrey Dean","venue":null,"work_id":"1eb16685-ab5d-436f-aee9-5760bbcc4f84","year":2013},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.688208Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:b192f5a213229fc7947d64e53ead81deb5be2fadb4bebad46c543b896a98b51a","observation_id":"6f1bc0c6-f67e-414c-a52b-d4a38aedd832","resolution":{"observed_at":"2026-08-07T04:48:09.076568Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.065909Z","title":"Dbrx: An open-source mixture-of-experts language model.https://github.com/databricks/DBRX, 2024","venue":null,"work_id":"d240ee93-a4d0-46b0-9c1f-16ba7c82414d","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.690624Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:aadbdf542453e75f38d341408f1658432b9ecdbbe3c586a2f0afa9cbde8e6b8c","observation_id":"c27fe78b-fdcc-4bda-9896-bc90db86e77e","resolution":{"observed_at":"2026-08-07T04:48:09.068980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.058036Z","title":"Nemotron-4: A 340b-parameter open source language model","venue":null,"work_id":"58fe4305-d7b4-490e-be07-a06d70c07a65","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.692771Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:9d2757baabb5a88b9ce208ed0f6388b6d81371359443da1fe08e96af293e9996","observation_id":"5cf7bf6c-a960-429a-b9b8-bdf516bbe4b3","resolution":{"observed_at":"2026-08-07T04:48:09.060991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.050071Z","title":null,"venue":null,"work_id":"0b8943a5-a875-4955-9822-b570fa7ab123","year":2023},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.694927Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:d2b2f6b70d685a9911cc173e2fb0b8623516f655bd8b250f7ff44ba572d08c45","observation_id":"109002d8-fdf3-439d-b534-760485afbb21","resolution":{"observed_at":"2026-08-07T04:48:09.052875Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.08302","last_updated":"2024-01-25T00:48:34Z","snapshot_observed_at":"2026-07-06T15:42:25.794343Z","submitted_at":"2023-06-14T07:15:26Z","title":"Unifying Large Language Models and Knowledge Graphs: A Roadmap","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.08302","snapshot_observed_at":"2026-08-07T04:48:08.697352Z","title":"Unifying Large Language Models and Knowledge Graphs: A Roadmap","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.697352Z"},"links":{"cited_paper":"/paper/2306.08302","citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:5941892d4f4a8e810827d4e0cefd2e44cc3e7531688cb68bd32b97eecc827549","observation_id":"e64d9027-7c48-4194-828b-8d256030c36a","resolution":{"observed_at":"2026-08-07T04:48:08.697352Z","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":"2026-08-07T04:48:08.699902Z","title":"Unifying large language models and knowledge graphs: A roadmap","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.699902Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:9517b00312a13271f9c48355eed1d16c10d5e36f8800f359a29903591decb7c3","observation_id":"d72bcec4-ccb7-4d67-ad38-720ebf224c4e","resolution":{"observed_at":"2026-08-07T04:48:08.699902Z","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":"2026-08-07T04:48:09.035130Z","title":"Knowl- edge graphs: Opportunities and challenges.Artificial Intelligence Review, 56(11):13071–13102, 2023","venue":null,"work_id":"7974867a-9aac-4d81-802b-e870077e7933","year":2023},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.702471Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:4eaac1614d69bdbcd7061dcd5211fcdf246d1a726331974652d969a9f45c887e","observation_id":"82fd05fa-5969-4cac-aa15-2d64e53bb16d","resolution":{"observed_at":"2026-08-07T04:48:09.038183Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.026375Z","title":"GloVe: Global vectors for word representation","venue":null,"work_id":"eb548275-a63c-431e-a9a5-b93c0d23d8d1","year":2014},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.704970Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:fb350da2cea85c2016620e4a68ded436b02b30e24c3dc5a23f86c3f1bfd02eb6","observation_id":"f3dff939-c523-44fa-865a-ef28117da9ac","resolution":{"observed_at":"2026-08-07T04:48:09.029134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.018117Z","title":"Peters, M","venue":null,"work_id":"666fa570-ba7f-4232-9554-302cd8451590","year":2019},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.707500Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:de338078f5bc7a75ee569af99d89496859196a46073c0b0eec5de72322e689cf","observation_id":"ee5f9cee-872e-4b4a-a7df-cbed4a86b9b5","resolution":{"observed_at":"2026-08-07T04:48:09.020687Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.009754Z","title":null,"venue":null,"work_id":"13f29eb1-65ea-4fac-a108-96b23c2a4c22","year":2019},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.709696Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:4f788d1fcab2eedf5de4020cabc4d176d6cdfb61b59a9abe1b41ecd7b61d93ec","observation_id":"44861c87-24b3-4edd-85da-87a6e1f589d4","resolution":{"observed_at":"2026-08-07T04:48:09.012618Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:09.001939Z","title":"Ad-hoc object retrieval in the web of data","venue":null,"work_id":"acb5a9ff-9874-4282-98bc-eb549511f2f5","year":2010},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.712087Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:d8a1cf5f7917d2de5991801aa545f41a2f8e6a4bf1b1be3e77e95a39e2a3de8f","observation_id":"fe6b0c74-052d-4940-a0f3-f50a3c4bcda5","resolution":{"observed_at":"2026-08-07T04:48:09.004512Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:08.993251Z","title":"Language models are unsupervised multitask learners","venue":null,"work_id":"5c6c9c1f-7219-463a-8cb2-030eca4b36c0","year":2019},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.714624Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:022eda7889612917e58dfe6deda7c8dee8cdbc7839ddc2a455da5cbfe2ef73f9","observation_id":"2c3f2c34-831a-4690-8597-543f90479918","resolution":{"observed_at":"2026-08-07T04:48:08.996421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:08.716882Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.716882Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:b63d22e63fb1a1ea9b7fb777255187f3f842da4f01e926e3aa11691721069f3d","observation_id":"1696ace2-46ee-4728-96bc-57650ea3e6f9","resolution":{"observed_at":"2026-08-07T04:48:08.716882Z","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":"2026-08-07T04:48:08.719174Z","title":"You CAN teach an old dog new tricks! on training knowledge graph embeddings","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.719174Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:e74012a30a1db06bea23fb24c108870738302ca839cd2965e83f1e668f04e6f1","observation_id":"4576d610-e9b5-4505-bb29-ae8072221e68","resolution":{"observed_at":"2026-08-07T04:48:08.719174Z","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":"2026-08-07T04:48:08.968161Z","title":"Synthesis Lectures on Data, Semantics, and Knowledge","venue":null,"work_id":"66dbcc71-eaac-4571-9b76-7dd3286e9117","year":2021},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.721851Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:f24fca6bc1814a36789f2e961dcc03143d489746989ec688af64e8d820b5982e","observation_id":"7eb9323a-f9d5-42c8-86e5-16c22003da75","resolution":{"observed_at":"2026-08-07T04:48:08.971793Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:08.957145Z","title":"Neural entity linking: A survey of models based on deep learning.Semantic Web, 13(3):527–570, 2022","venue":null,"work_id":"412455ae-ddd6-409b-b156-4cfaa405d09e","year":2022},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.724039Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:ce4b7dc75756f0f94ced6a15726c9e15cba8a301bc77c5d5d9309123ed4dfab5","observation_id":"1811f8dc-89cf-42d0-9143-d7d21176fec2","resolution":{"observed_at":"2026-08-07T04:48:08.960517Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:08.947291Z","title":"Conceptnet 5.5: An open multilingual graph of general knowledge","venue":null,"work_id":"8ddd7d00-b927-41bf-9b3a-15b51ed11816","year":2017},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.726320Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:68f1fc9461b89c2913585e77dba05d29f035f5cdc9742475533a6013d9cd80f5","observation_id":"08d2ab57-ca2f-4df4-9fc1-6eb0824a8327","resolution":{"observed_at":"2026-08-07T04:48:08.950090Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:08.939114Z","title":"Ernie: Enhanced representation through knowledge integration","venue":null,"work_id":"1ec25ca2-8735-4cd9-8647-b1b4c9483df9","year":2019},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.728591Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:8142875fec210f27ff3541f778b28c35e55f5117b9a81d3422dccc78fcb78d2c","observation_id":"547edd57-d415-487d-bd46-c640482337ed","resolution":{"observed_at":"2026-08-07T04:48:08.941843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.08239","last_updated":"2022-02-10T16:30:11Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-01-20T15:44:37Z","title":"LaMDA: Language Models for Dialog Applications","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.08239","snapshot_observed_at":"2026-08-07T04:48:08.730814Z","title":"Lamda: Language models for dialog applications","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.730814Z"},"links":{"cited_paper":"/paper/2201.08239","citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:51499b2d96f5b5282851568bb29ee4905408634362e8a38dce102929e709128d","observation_id":"b8a0663d-56b0-4706-bd2f-e4f14432163e","resolution":{"observed_at":"2026-08-07T04:48:08.730814Z","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":"2026-08-07T04:48:08.930457Z","title":"Knowledge graph validation by integrating llms and human-in-the-loop.In- formation Processing & Management, 62(5):104145, 2025","venue":null,"work_id":"84c4dc04-18b1-4669-b94c-8c430646be28","year":2025},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.733573Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:ab4ab59b5561fef2135cd3207b58c980c6a31eb601cbf7f688f65ae64e5ef3a2","observation_id":"b91c6eaa-c539-427f-ab01-61537db3d731","resolution":{"observed_at":"2026-08-07T04:48:08.933456Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:08.921579Z","title":"Gomez, Lukasz Kaiser, and Illia Polosukhin","venue":null,"work_id":"9ca6261b-39f1-4347-a4b6-7a6bcf8534fc","year":2017},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.735799Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:f5f0fbec038bd97c2c6f674eef4ec5b190b4e4c3089935a46ca8ec9314f2c553","observation_id":"f6493bae-fefc-424e-a2c1-64df748d1709","resolution":{"observed_at":"2026-08-07T04:48:08.924642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14282","last_updated":"2024-10-23T09:42:59Z","snapshot_observed_at":"2026-07-06T18:34:15.291938Z","submitted_at":"2024-06-20T13:07:38Z","title":"Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14282","snapshot_observed_at":"2026-08-07T04:48:08.738187Z","title":"Pan, Wen Zhang, and Huajun Chen","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.738187Z"},"links":{"cited_paper":"/paper/2406.14282","citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:5e007d129842d43acde804c50c9a7729bd8d87dbc8fe7ebc76f930a7507a485b","observation_id":"dc98b0a4-14bf-4b29-91a1-eea9959bfa67","resolution":{"observed_at":"2026-08-07T04:48:08.738187Z","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":"2026-08-07T04:48:08.741282Z","title":"A survey on knowledge graph embeddings for link prediction.Symmetry, 13(3):485, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.741282Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:40ac7c1886915a9caa4dca8c0147acc12d6b3b7c6e5a98e67b55d8cf679437a9","observation_id":"eb4ff725-8028-46c9-8763-1a6b0196a0d0","resolution":{"observed_at":"2026-08-07T04:48:08.741282Z","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":"2026-08-07T04:48:08.908373Z","title":"Mindmap: Prompting large language models with knowledge graphs for graph-of- thoughtreasoning","venue":null,"work_id":"14dd1e13-1ced-42f3-8750-39d1a9e2c326","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.743631Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:68af9fc18a05cdd7e251e33e187168beb99107a3ecc16d9983cc2103770dd839","observation_id":"d10c2085-9ac2-4649-83bf-655c4b81f38d","resolution":{"observed_at":"2026-08-07T04:48:08.910924Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:08.901036Z","title":"Fact-aware generation in large language models.https://example.org/yang2024factaware, 2024","venue":null,"work_id":"5279919a-14fe-4479-973d-09ebdd3bdcaf","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.746049Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:b2fcbfd14906a21da56c6f342adf5d9f6787c97c9516073122d1ca6c1c43534e","observation_id":"46598aef-03a5-4294-95e3-08baca7a0333","resolution":{"observed_at":"2026-08-07T04:48:08.903459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:08.893682Z","title":"Toward better drug discovery with knowledge graph.Current opinion in structural biology, 72:114–126, 2022","venue":null,"work_id":"d7f67104-9201-4c12-9993-6485b0f86019","year":2022},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.748399Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:0f31ec456e5e4305dde18c499827dabbf446cb69bc14397fdf17d54975680b4a","observation_id":"bb493e28-6b91-41bf-919f-de42ed77ffdf","resolution":{"observed_at":"2026-08-07T04:48:08.896260Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-07T04:48:08.885977Z","title":"Kg-enhanced reasoning in large language models","venue":null,"work_id":"ce0c6e7c-6b87-463b-9756-6522beff28b6","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.750710Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:deccfea0a66c74770bde80b33e73af002c9c2aa16e253991aa80a8642353af51","observation_id":"02f4f48c-9d9f-42da-af9c-3214fa69587b","resolution":{"observed_at":"2026-08-07T04:48:08.888982Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06671","last_updated":"2024-04-14T05:30:19Z","snapshot_observed_at":"2026-07-06T16:30:33.889293Z","submitted_at":"2023-10-10T14:47:09Z","title":"Making Large Language Models Perform Better in Knowledge Graph Completion","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06671","snapshot_observed_at":"2026-08-07T04:48:08.753054Z","title":"Making large language models perform better in knowledge graph completion.arXiv preprint arXiv:2310.06671, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.753054Z"},"links":{"cited_paper":"/paper/2310.06671","citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:062e0fdec9411b19ecadddb57ce505d442a1ea7897ef9407f5b910a281f5469f","observation_id":"8a8dff96-958d-4d8b-b619-5ae5e9d0cd7f","resolution":{"observed_at":"2026-08-07T04:48:08.753054Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00653","last_updated":"2024-06-30T10:49:32Z","snapshot_observed_at":"2026-07-06T18:39:03.315371Z","submitted_at":"2024-06-30T10:49:32Z","title":"Chain-of-Knowledge: Integrating Knowledge Reasoning into Large Language Models by Learning from Knowledge Graphs","version":1},"cited_work":{"arxiv_id":"2407.00653","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.00653","snapshot_observed_at":"2026-08-07T04:48:08.805515Z","title":"Chain-of-Knowledge: Integrating Knowledge Reasoning into Large Language Models by Learning from Knowledge Graphs","venue":"cs.CL","work_id":"2820833f-58d3-4ba5-b278-f1669b49ab91","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.755446Z"},"links":{"cited_paper":"/paper/2407.00653","citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:2792307d01cc6d6860f53e5729ecf3e2151f9695485c3cfdc4b8bbf198341060","observation_id":"52b0853b-ac57-49f4-97ad-de306d971d7b","resolution":{"observed_at":"2026-08-07T04:48:08.810325Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.18223","last_updated":"2026-03-18T05:34:39Z","snapshot_observed_at":"2026-08-06T23:27:24.356320Z","submitted_at":"2023-03-31T17:28:46Z","title":"A Survey of Large Language Models","version":19},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.18223","snapshot_observed_at":"2026-08-07T04:48:08.757887Z","title":"A survey of large language models.ArXiv preprint, abs/2303.18223, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.757887Z"},"links":{"cited_paper":"/paper/2303.18223","citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:beb8fb76cac58e2659e0ed16fff276b365daeea181cc68d8ceb1f76c76766316","observation_id":"eaaf5c93-f681-4d20-9ef6-153826259e24","resolution":{"observed_at":"2026-08-07T04:48:08.757887Z","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":"2026-08-07T04:48:08.877691Z","title":"A survey of knowl- edge graph construction using machine learning.Computer Modeling in Engineering & Sciences, 139(1):225–257, 2024","venue":null,"work_id":"6a6eeb52-db9b-4558-a66d-8cc7420e0c48","year":2024},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.760526Z"},"links":{"citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:94c04eeda0d26a91b5a49fed516fbd9e8c94834c41a0f825ef54ad643acddb3a","observation_id":"ed0571ef-513d-4330-9097-a8574f4a39f2","resolution":{"observed_at":"2026-08-07T04:48:08.880514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.13168","last_updated":"2024-12-26T18:54:53Z","snapshot_observed_at":"2026-07-06T15:30:45.921201Z","submitted_at":"2023-05-22T15:56:44Z","title":"LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.13168","snapshot_observed_at":"2026-08-07T04:48:08.762913Z","title":"Llms for knowledge graph construction and reasoning: Recent capabilities and future opportunities","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-07T04:48:08.762913Z"},"links":{"cited_paper":"/paper/2305.13168","citing_paper":"/paper/2506.09566"},"observation_digest":"sha256:e02437041f59d8c0470c11e162966a8427616bf9c738f25d80cee702779c0226","observation_id":"7d2d828b-e0b5-4fe4-940e-eeee0b4a6c6f","resolution":{"observed_at":"2026-08-07T04:48:08.762913Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.09566","last_updated":"2025-06-11T09:58:14Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T04:43:00.864186Z","submitted_at":"2025-06-11T09:58:14Z","title":"From Symbolic to Neural and Back: Exploring Knowledge Graph-Large Language Model Synergies"},"reference_resolution":{"displayed":69,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":18,"verified_exact":1,"verified_fuzzy":50},"total_outbound_references":69},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 69 of 69 outbound references and 0 inbound Pith citation observations for arXiv:2506.09566."}