{"as_of":"2026-08-12T16:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ec477d6c3cf83d9b2f95a8c340afb5b51adae14012f4ebc8b5185164eb3ff7eb","coverage":[{"denominator":24,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":24,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T22:50:44.191695Z","state":"measured"},{"denominator":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T14:55:48.045850Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-11T00:39:36.052997Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03097","snapshot_observed_at":"2026-08-11T12:12:20.100276Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over- Smoothing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.14521","last_updated":"2024-12-19T04:37:47Z","snapshot_observed_at":"2026-08-11T12:07:35.331175Z","submitted_at":"2024-12-19T04:37:47Z","title":"Dynamic User Interface Generation for Enhanced Human-Computer Interaction Using Variational Autoencoders","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T12:12:20.100276Z"},"links":{"cited_paper":"/paper/2412.03097","citing_paper":"/paper/2412.14521"},"observation_digest":"sha256:103a8b62c5a5aa8ef86e649391b9a96e092c7c0f1d28fbb2ad3afcd0f218e6ef","observation_id":"475e16ca-928e-42c1-bf72-66b35d2a474f","resolution":{"observed_at":"2026-08-11T12:12:20.100276Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03097","snapshot_observed_at":"2026-08-11T11:18:31.290025Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over- Smoothing,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.15593","last_updated":"2024-12-20T06:32:05Z","snapshot_observed_at":"2026-08-11T11:15:04.870807Z","submitted_at":"2024-12-20T06:32:05Z","title":"Machine Learning Techniques for Pattern Recognition in High-Dimensional Data Mining","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T11:18:31.290025Z"},"links":{"cited_paper":"/paper/2412.03097","citing_paper":"/paper/2412.15593"},"observation_digest":"sha256:f3c0e28baedd445c260f6741260297bc98ec446ae2fa519d4b0d98302289ffac","observation_id":"bc7c5c36-1b49-4c06-9585-d00ed01c9d77","resolution":{"observed_at":"2026-08-11T11:18:31.290025Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03097","snapshot_observed_at":"2026-08-11T10:18:14.590914Z","title":"Enhancing RecommendationSystemswithGNNsandAddressingOver- Smoothing,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.16837","last_updated":"2024-12-22T03:06:48Z","snapshot_observed_at":"2026-08-11T10:13:08.389642Z","submitted_at":"2024-12-22T03:06:48Z","title":"Adaptive User Interface Generation Through Reinforcement Learning: A Data-Driven Approach to Personalization and Optimization","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T10:18:14.590914Z"},"links":{"cited_paper":"/paper/2412.03097","citing_paper":"/paper/2412.16837"},"observation_digest":"sha256:cdcacdc039c73f455718d56d9aeef2c139444faaca4b8a7abf21b492dfe4023f","observation_id":"b946952a-e40c-4462-bf3b-867c3c6b235b","resolution":{"observed_at":"2026-08-11T10:18:14.590914Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03097","snapshot_observed_at":"2026-08-11T05:40:19.771118Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over- Smoothing,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.17301","last_updated":"2024-12-23T05:43:17Z","snapshot_observed_at":"2026-08-11T19:47:35.865345Z","submitted_at":"2024-12-23T05:43:17Z","title":"Dynamic Scheduling Strategies for Resource Optimization in Computing Environments","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T05:40:19.771118Z"},"links":{"cited_paper":"/paper/2412.03097","citing_paper":"/paper/2412.17301"},"observation_digest":"sha256:54d2f4356cc97812c2056c6a674fe8332f41a1d487f4007352dbad36ad156ec5","observation_id":"ba10ba14-915d-4d13-b3e2-8473f512b40e","resolution":{"observed_at":"2026-08-11T05:40:19.771118Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03097","snapshot_observed_at":"2026-08-11T04:50:46.881109Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over- Smoothing,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.18321","last_updated":"2024-12-24T10:13:20Z","snapshot_observed_at":"2026-08-11T09:56:16.571247Z","submitted_at":"2024-12-24T10:13:20Z","title":"Computer Vision-Driven Gesture Recognition: Toward Natural and Intuitive Human-Computer","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T04:50:46.881109Z"},"links":{"cited_paper":"/paper/2412.03097","citing_paper":"/paper/2412.18321"},"observation_digest":"sha256:8ace9d25beac3a1b2ec298fd705969982721a96bee5fccdd51bea5b1b8fbe424","observation_id":"da5a2b00-ae72-4e94-9c4a-c89c9d4ee681","resolution":{"observed_at":"2026-08-11T04:50:46.881109Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"cited_work":{"arxiv_id":"2412.03097","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.03097","snapshot_observed_at":"2026-08-11T00:39:36.052997Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","venue":"cs.IR","work_id":"13588fbf-dc23-4ceb-8db5-1173bb0dbc07","year":2024},"citing_paper":{"arxiv_id":"2412.19420","last_updated":"2024-12-27T03:13:13Z","snapshot_observed_at":"2026-08-11T09:56:50.688458Z","submitted_at":"2024-12-27T03:13:13Z","title":"A Matrix Logic Approach to Efficient Frequent Itemset Discovery in Large Data Sets","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T00:39:35.398187Z"},"links":{"cited_paper":"/paper/2412.03097","citing_paper":"/paper/2412.19420"},"observation_digest":"sha256:a3c8bbe5f3f9d2b9f784365f7ed8f7d406b12d421890bf9600f15963b220fbaf","observation_id":"99d7ecbc-3bd7-4923-b3b8-0b4fab0c19f7","resolution":{"observed_at":"2026-08-11T00:39:36.062295Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03097","snapshot_observed_at":"2026-08-11T14:55:48.045850Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over- Smoothing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.14745","last_updated":"2024-12-16T06:37:09Z","snapshot_observed_at":"2026-08-11T14:51:28.690428Z","submitted_at":"2024-12-16T06:37:09Z","title":"AI-Driven Health Monitoring of Distributed Computing Architecture: Insights from XGBoost and SHAP","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T14:55:48.045850Z"},"links":{"cited_paper":"/paper/2412.03097","citing_paper":"/paper/2501.14745"},"observation_digest":"sha256:8b250a6452a41bf700ce9640e413386c0b2cf71da0955485421bf9caec6b717b","observation_id":"7ca53fb3-9c21-404b-b95e-d3b1ea050b18","resolution":{"observed_at":"2026-08-11T14:55:48.045850Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2412.03097/citation-record","integrity":"/paper/2412.03097/integrity","json":"/paper/2412.03097/citation-record.json","paper":"/paper/2412.03097"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T22:50:44.600329Z","title":"A comprehensive survey on graph neuralnetworks","venue":null,"work_id":"00931fec-946f-4e16-a5c2-6d3c220e57ae","year":2020},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.110191Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:3de28d9a4e3f58f2dc391ab8e1680e27bc2e8b549b469242973dd1ca0038f324","observation_id":"641294e1-0862-4ce6-a90e-4f416d975bde","resolution":{"observed_at":"2026-08-11T22:50:44.604102Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T22:50:44.588485Z","title":"Advances in collaborative filtering","venue":null,"work_id":"e33c5dab-a732-4e27-98a7-4b7bced383d8","year":2021},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.113930Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:bb006707a3108d17d07866b7cf8a84351ccbaa41cac55a306ed59709c30ce738","observation_id":"0a4cc6f4-3555-4f5f-bf16-a0c41883f6a2","resolution":{"observed_at":"2026-08-11T22:50:44.592718Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.03572","last_updated":"2024-11-06T00:23:55Z","snapshot_observed_at":"2026-07-06T19:45:53.289704Z","submitted_at":"2024-11-06T00:23:55Z","title":"Advanced RAG Models with Graph Structures: Optimizing Complex Knowledge Reasoning and Text Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.03572","snapshot_observed_at":"2026-08-11T22:50:44.117043Z","title":"Advanced RAG Models with Graph Structures: Optimizing Complex Knowledge Reasoning and Text Generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.117043Z"},"links":{"cited_paper":"/paper/2411.03572","citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:ba0f93b6798f8454fc7005f9fa374510f105603c2bc664e3515404c1a3491f54","observation_id":"969b5310-d7be-4bf4-a132-da7e7f298d72","resolution":{"observed_at":"2026-08-11T22:50:44.117043Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-07-06T19:52:20.541067Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.12161","snapshot_observed_at":"2026-08-11T22:50:44.120868Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based SpatiotemporalPrediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.120868Z"},"links":{"cited_paper":"/paper/2411.12161","citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:7438a6f68dc8b0fb7918dc39dccf20e657aefcbd44db6d457d61ddd449b7616c","observation_id":"e2cb5828-dc4f-4083-a608-91da80794928","resolution":{"observed_at":"2026-08-11T22:50:44.120868Z","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":"2026-08-11T22:50:44.577901Z","title":"Enhancing Recommendation Systems with Multi-Modal Transformers in Cross-Domain Scenarios,","venue":null,"work_id":"9e3aa048-41c8-427b-9955-de274bbe391c","year":2024},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.124738Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:a4c4a2f09e6e557f72961a992d029d15309caa4041b9aa3eaf6cc0181d0b7800","observation_id":"e37689b2-9f9a-4ab6-bc79-6f6ae0c96438","resolution":{"observed_at":"2026-08-11T22:50:44.581679Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.12157","last_updated":"2024-11-19T01:41:56Z","snapshot_observed_at":"2026-07-06T19:52:20.541067Z","submitted_at":"2024-11-19T01:41:56Z","title":"A Combined Encoder and Transformer Approach for Coherent and High-Quality Text Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.12157","snapshot_observed_at":"2026-08-11T22:50:44.128565Z","title":"A Combined Encoder and Transformer Approach for Coherent and High- QualityTextGeneration,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.128565Z"},"links":{"cited_paper":"/paper/2411.12157","citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:4b7b62f74d14ba76189b8340f1246a55997f911b1722d54269d77e253a3aef04","observation_id":"7201d1e6-2e37-41a6-98fa-22d479df27cb","resolution":{"observed_at":"2026-08-11T22:50:44.128565Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.12151","last_updated":"2024-11-19T01:01:56Z","snapshot_observed_at":"2026-08-12T09:49:40.556452Z","submitted_at":"2024-11-19T01:01:56Z","title":"Self-Supervised Learning in Deep Networks: A Pathway to Robust Few-Shot Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.12151","snapshot_observed_at":"2026-08-11T22:50:44.132539Z","title":"Self-Supervised Learning in Deep Networks: A Pathway to Robust Few-Shot Classification,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.132539Z"},"links":{"cited_paper":"/paper/2411.12151","citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:3c506bb67207628eaf60b1f7c2144e1194e80ce6e64f1996d6f3ea55a2147995","observation_id":"35201693-840a-4ada-82d5-2ab590f983e7","resolution":{"observed_at":"2026-08-11T22:50:44.132539Z","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":"2026-08-11T22:50:44.136357Z","title":"Financial Risk Analysis Using Integrated Data and Transformer-Based Deep Learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.136357Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:43e141c187f693a0e4018dc18073c1777abcf23fcf946a3fd5ba7d76c2a6845d","observation_id":"9045a7f5-3aa7-40ba-97ff-da339c857fde","resolution":{"observed_at":"2026-08-11T22:50:44.136357Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.14327","last_updated":"2024-10-08T07:14:04Z","snapshot_observed_at":"2026-08-04T14:40:34.537695Z","submitted_at":"2024-09-22T06:27:07Z","title":"Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.14327","snapshot_observed_at":"2026-08-11T22:50:44.139706Z","title":"Transforming Multidimensional Time Series into Interpretable Event Sequences for AdvancedDataMining,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.139706Z"},"links":{"cited_paper":"/paper/2409.14327","citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:8a586b1608fd6023f3f99282587852613deac7d2ba4afe0808d429cf8f935fe4","observation_id":"0303a912-3453-4d2d-992e-d0fc6d7e6b31","resolution":{"observed_at":"2026-08-11T22:50:44.139706Z","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":"2026-08-11T22:50:44.561006Z","title":"Time-Series Load Prediction for Cloud Resource Allocation Using Recurrent Neural Networks,","venue":null,"work_id":"6b4733fb-3065-4327-95f1-98ef927242bf","year":2024},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.143293Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:f6f77c23c71d4f5158973d96b7fe34a9d3a36bc7db776ca67da437e0a74fe91e","observation_id":"92e38247-fa81-462f-9709-eb051258f911","resolution":{"observed_at":"2026-08-11T22:50:44.564753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.06326","last_updated":"2024-11-10T01:26:39Z","snapshot_observed_at":"2026-07-06T19:47:55.814924Z","submitted_at":"2024-11-10T01:26:39Z","title":"Emotion-Aware Interaction Design in Intelligent User Interface Using Multi-Modal Deep Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.06326","snapshot_observed_at":"2026-08-11T22:50:44.146461Z","title":"Emotion-Aware Interaction Design in Intelligent User Interface Using Multi-Modal DeepLearning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.146461Z"},"links":{"cited_paper":"/paper/2411.06326","citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:63698281a5fca3c17d1ae0445d8d25ea161d52b288c7c3fa45b96ee3a9815207","observation_id":"3f97b203-9aed-4c1b-b72d-2f0b8f492fa9","resolution":{"observed_at":"2026-08-11T22:50:44.146461Z","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":"2026-08-11T22:50:44.550260Z","title":"Analyze the Impact of the Epidemic on New York Taxis by Machine Learning Algorithms and Recommendations for Optimal Prediction Algorithms,","venue":null,"work_id":"c273fcf3-1207-432b-a046-05ef94020571","year":2021},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.150138Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:bb59fef4780e02cbf89aadde68a80be308d946bc811fc1faf2c42bcbf0be3634","observation_id":"2461b7c9-febc-4d2d-bb1c-3ece9fc3351d","resolution":{"observed_at":"2026-08-11T22:50:44.554460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.10947","last_updated":"2021-01-06T13:32:14Z","snapshot_observed_at":"2026-08-10T11:37:17.761481Z","submitted_at":"2019-05-27T02:59:06Z","title":"Graph Neural Networks Exponentially Lose Expressive Power for Node Classification","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.10947","snapshot_observed_at":"2026-08-11T22:50:44.153495Z","title":"Graph neural networks exponentially lose expressive power for node classification","venue":null,"work_id":null,"year":1905},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.153495Z"},"links":{"cited_paper":"/paper/1905.10947","citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:ca0412edd91f12d4dbe0d42f2815c0a0e9fefc8de2d84669ab694eb164f6ef15","observation_id":"304f1b92-025f-489d-82c5-aa0b17ace291","resolution":{"observed_at":"2026-08-11T22:50:44.153495Z","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":"2026-08-11T22:50:44.540099Z","title":"Modeling user exposure in recommendation","venue":null,"work_id":"1ec689c2-b764-4cf0-ba69-331d1a59bf43","year":2016},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.157192Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:4d6fda7f6cd8d35233161b769a02ad91851ac30bbc08ee831df96cb8e081a822","observation_id":"d76f31ef-85e9-46ed-9839-bd95598516f8","resolution":{"observed_at":"2026-08-11T22:50:44.543871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T22:50:44.528713Z","title":"Calibration Learning for Few-shot Novel Product Description,","venue":null,"work_id":"0ecfa5df-f681-4f15-b939-c191011af78b","year":null},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.160519Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:96ee7d8a9b763d491a90a8c5e89c35bca81f5565260763083bf77e22648c5679","observation_id":"0de62cea-6da7-49af-a421-12e301eeaac4","resolution":{"observed_at":"2026-08-11T22:50:44.532434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T22:50:44.164261Z","title":"Improving the RAG- based Personalized Discharge Care System by Introducing the Memory Mechanism","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.164261Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:a9f0ec50e7878c559adaedc7c26e73f91ddc1cd4010228a9787c7734703ac26c","observation_id":"cc228f3a-c6cc-497a-b096-55100c3aba5f","resolution":{"observed_at":"2026-08-11T22:50:44.164261Z","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":"2026-08-11T22:50:44.517795Z","title":"Survival prediction across diverse cancer types using neural networks,","venue":null,"work_id":"91b1fa9f-df18-4198-b01b-99fb1d84784f","year":2024},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.167558Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:211ce3607a0298f48f8aa99a3c88038d5cbe319e1ea485c2137151ab4c2dd151","observation_id":"732a1bb4-d21b-48a4-9396-e94ef6a7f669","resolution":{"observed_at":"2026-08-11T22:50:44.521180Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T22:50:44.170868Z","title":"Research on Large Scene Adaptive Feature Extraction Based on Deep Learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.170868Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:d04f65f3b8f88d2dca484d4bc3429b7f42331593d9a3b511daff16ee5e6caa46","observation_id":"0fda3d79-54bf-4662-ab1c-5f0041996134","resolution":{"observed_at":"2026-08-11T22:50:44.170868Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1205.2618","last_updated":"2012-05-09T18:25:09Z","snapshot_observed_at":"2026-07-06T02:47:58.266745Z","submitted_at":"2012-05-09T18:25:09Z","title":"BPR: Bayesian Personalized Ranking from Implicit Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1205.2618","snapshot_observed_at":"2026-08-11T22:50:44.174222Z","title":"BPR: Bayesian personalized ranking from implicit feedback","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.174222Z"},"links":{"cited_paper":"/paper/1205.2618","citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:d5fe07ca94b346e10848bb4f4c82596e07717befa2ddc299c2e0fc75f94baa08","observation_id":"9a339832-2450-461e-97b4-ed19e4dcd149","resolution":{"observed_at":"2026-08-11T22:50:44.174222Z","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":"2026-08-11T22:50:44.506902Z","title":"Comparison of Tree-Based Feature Selection Algorithms on Biological Omics Dataset,","venue":null,"work_id":"79dd51f0-ea18-48e1-a317-002b2c25977f","year":null},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.178031Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:489fe6cb825f8ce4bf311938e0a40ceb871ab466a7fb085e550f6d74c6a201cc","observation_id":"e2c3fcf4-3652-4753-b4b2-73aee5638db5","resolution":{"observed_at":"2026-08-11T22:50:44.510509Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T22:50:44.496605Z","title":"Adaptive ReceptiveField U-ShapedTemporalConvolutionalNetworkfor Vulgar ActionSegmentation,","venue":null,"work_id":"0dce7196-c180-4855-af7b-1cfcebed504a","year":2023},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.181598Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:3f0d03a1c5a34b0b3b17962f5e4cd83253bd7197ca941238e31f56f2f8fa887e","observation_id":"66aa6768-df3a-471a-86ff-8daa755fdebd","resolution":{"observed_at":"2026-08-11T22:50:44.500196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T22:50:44.486010Z","title":"Neural graph collaborative filtering","venue":null,"work_id":"beb7d35f-cf0d-40c0-8c3a-824c8f5828db","year":2019},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.185038Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:52973cd0a0f7202270c437a55f7403c5e1a64a2e5f10ea38e510b4c8bb09c112","observation_id":"c4d118ab-58ed-47cf-8c21-ff9770587c05","resolution":{"observed_at":"2026-08-11T22:50:44.489831Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T22:50:44.471616Z","title":"LightGCN: Simplifying and powering graph convolution network for recommendation","venue":null,"work_id":"7f206e70-dd84-413a-a43e-21e2b394abeb","year":2020},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.188511Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:40be62c13c450c7eb7013c7e6499f0d9263fb11c7ab7096f6b5a9e43df3dcb3e","observation_id":"a6364e55-250c-4c4d-bdcd-df89b8f04263","resolution":{"observed_at":"2026-08-11T22:50:44.477649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+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":"2026-08-11T22:50:44.191695Z","title":"Fine-Grained Imbalanced Leukocyte Classification With Global-Local Attention Transformer,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T22:50:44.191695Z"},"links":{"citing_paper":"/paper/2412.03097"},"observation_digest":"sha256:daf1eb09e8a3e4906ba9f2523602606852edb92835f789b12963c0531a4990d6","observation_id":"475a9691-a1be-4741-9a7e-c8d3661dafa0","resolution":{"observed_at":"2026-08-11T22:50:44.191695Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.03097","last_updated":"2024-12-04T07:50:27Z","latest_version":1,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-11T22:44:25.707722Z","submitted_at":"2024-12-04T07:50:27Z","title":"Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing"},"reference_resolution":{"displayed":24,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":0,"verified_fuzzy":12},"total_outbound_references":24},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 7 inbound Pith citation observations for arXiv:2412.03097."}