{"as_of":"2026-08-13T08:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:76d62f6c4050d707b142fda83e592a1fb5a8ddd636f7b8dfe46e728ba7997d4d","coverage":[{"denominator":23,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T17:55:18.085618Z","state":"measured"},{"denominator":32,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":32,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+00:00","state":"measured"},{"denominator":9,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":9,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T11:03:15.179059Z","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":"2026-08-11T04:50:47.026808Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","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":"2026-08-12T11:03:15.179059Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.18622","last_updated":"2024-11-27T18:59:50Z","snapshot_observed_at":"2026-08-12T10:57:34.867885Z","submitted_at":"2024-11-27T18:59:50Z","title":"Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T11:03:15.179059Z"},"links":{"cited_paper":"/paper/2411.12161","citing_paper":"/paper/2411.18622"},"observation_digest":"sha256:8d90b832f27c7e08509a6fbb1005f4ea95afaa69f65e7b977d8a23c2d2dae1fc","observation_id":"7c18c367-36bc-4641-891d-eab4ae5d0ffd","resolution":{"observed_at":"2026-08-12T11:03:15.179059Z","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":"2026-08-12T17:48:40.654604Z","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":"2026-08-11T23:46:09.672963Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.02211","last_updated":"2024-12-03T07:04:10Z","snapshot_observed_at":"2026-08-11T23:41:13.408150Z","submitted_at":"2024-12-03T07:04:10Z","title":"An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T23:46:09.672963Z"},"links":{"cited_paper":"/paper/2411.12161","citing_paper":"/paper/2412.02211"},"observation_digest":"sha256:3a15c34348732218d3f3fc72897abef23e30c15fadafbbbdbb259f754f7179d2","observation_id":"2018affd-7c04-42a5-8a29-c90c66ae80ab","resolution":{"observed_at":"2026-08-11T23:46:09.672963Z","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":"2026-08-12T17:48:40.654604Z","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:b3913ae72ddefe91d0990c5e1cdb214a5dc278e9d2d7ae3bd51ceaac167b9d75","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":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","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":"2026-08-11T22:47:27.989376Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN -LSTM-Based Spatiotemporal Prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03606","last_updated":"2024-12-04T08:15:27Z","snapshot_observed_at":"2026-08-11T22:43:27.015517Z","submitted_at":"2024-12-04T08:15:27Z","title":"Advanced Risk Prediction and Stability Assessment of Banks Using Time Series Transformer Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T22:47:27.989376Z"},"links":{"cited_paper":"/paper/2411.12161","citing_paper":"/paper/2412.03606"},"observation_digest":"sha256:74d5ea05307b16a812f3d117906e37d84653617f9899e6a2fb43a3a964895ec9","observation_id":"09d6112c-0b14-4944-abfd-ecdff4f3042d","resolution":{"observed_at":"2026-08-11T22:47:27.989376Z","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":"2026-08-12T17:48:40.654604Z","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":"2026-08-11T19:54:34.575752Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.06249","last_updated":"2024-12-09T06:47:42Z","snapshot_observed_at":"2026-08-11T19:50:03.366364Z","submitted_at":"2024-12-09T06:47:42Z","title":"Optimizing Multi-Task Learning for Enhanced Performance in Large Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T19:54:34.575752Z"},"links":{"cited_paper":"/paper/2411.12161","citing_paper":"/paper/2412.06249"},"observation_digest":"sha256:187df09d1008f8ee6775ce8c87eedbd74711152609cad73c9db101d3b904d176","observation_id":"a477342e-7dd8-492a-99c1-c6faa1ff1572","resolution":{"observed_at":"2026-08-11T19:54:34.575752Z","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":"2026-08-12T17:48:40.654604Z","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":"2026-08-11T12:12:20.094024Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based SpatiotemporalPrediction","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.14521","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":22,"source":"pdf_text","source_observed_at":"2026-08-11T12:12:20.094024Z"},"links":{"cited_paper":"/paper/2411.12161","citing_paper":"/paper/2412.14521"},"observation_digest":"sha256:46d5b6363e3be8f50066b550f52a695ed2e6f202cfa8af346359965b4284260e","observation_id":"7f69292f-d202-4430-a2b8-c4bdd3f353d9","resolution":{"observed_at":"2026-08-11T12:12:20.094024Z","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":"2026-08-12T17:48:40.654604Z","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":"2026-08-11T10:18:14.560183Z","title":"AdaptiveCache ManagementforComplexStorageSystemsUsingCNN-LSTM-Based SpatiotemporalPrediction,","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":10,"source":"pdf_text","source_observed_at":"2026-08-11T10:18:14.560183Z"},"links":{"cited_paper":"/paper/2411.12161","citing_paper":"/paper/2412.16837"},"observation_digest":"sha256:ff2089ac7328cbee4cb01b54c082ca48f9de2cd159a9167000ac5ee5ee1fea34","observation_id":"f804fe01-46e0-4682-bacd-b5952bdb11b1","resolution":{"observed_at":"2026-08-11T10:18:14.560183Z","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":"2026-08-12T17:48:40.654604Z","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":"2026-08-11T05:38:37.619518Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.17314","last_updated":"2024-12-23T06:14:15Z","snapshot_observed_at":"2026-08-11T05:33:22.138242Z","submitted_at":"2024-12-23T06:14:15Z","title":"Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXt","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T05:38:37.619518Z"},"links":{"cited_paper":"/paper/2411.12161","citing_paper":"/paper/2412.17314"},"observation_digest":"sha256:af143a031f9d45eb4d04032a2cd56f5abd9d274faa8710b2b033a7dc0d83460c","observation_id":"8329ccef-e337-4e22-a450-a86af2e8b282","resolution":{"observed_at":"2026-08-11T05:38:37.619518Z","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":"2026-08-12T17:48:40.654604Z","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":"2411.12161","doi":null,"metadata_source":"pith","pith_arxiv_id":"2411.12161","snapshot_observed_at":"2026-08-11T04:50:47.026808Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","venue":"cs.DC","work_id":"b3c18ff9-5afc-413d-9056-17e88cc32b8a","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":21,"source":"pdf_text","source_observed_at":"2026-08-11T04:50:46.921755Z"},"links":{"cited_paper":"/paper/2411.12161","citing_paper":"/paper/2412.18321"},"observation_digest":"sha256:4614cc738c8d9b5b2ea43d65321a63d97256dbc0bf8dc11fdfd8265b23561f6d","observation_id":"d6d660ce-a0f5-4742-a450-5bbd0a54960a","resolution":{"observed_at":"2026-08-11T04:50:47.034262Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.12161/citation-record","integrity":"/paper/2411.12161/integrity","json":"/paper/2411.12161/citation-record.json","paper":"/paper/2411.12161"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T17:55:18.409173Z","title":"An Intelligent Caching Approach in Mobile Edge Computing Environment,","venue":null,"work_id":"39947177-b2b9-4f4b-b5d9-17ff9bcede2d","year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:17.983450Z"},"links":{"citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:42fa4aa306c713119045e237dd732e09d792aaf5977ef55f5814f4e33ede024c","observation_id":"452bb4bb-519c-407d-80e5-7caa6c6e7bb8","resolution":{"observed_at":"2026-08-12T17:55:18.413104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T17:55:18.395587Z","title":"STRCacheML: A Machine Learning-Assisted Content Caching Policy for Streaming Services,","venue":null,"work_id":"104ce266-f938-4379-a3a6-f43c690cf641","year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:17.991158Z"},"links":{"citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:4fc171695678203f88b6ac9381d9a7b902842516faecfd74031c357f26cb67eb","observation_id":"c4e22c1a-fa49-4258-b611-97cad2c22ba0","resolution":{"observed_at":"2026-08-12T17:55:18.400105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.19211","last_updated":"2024-10-24T23:43:50Z","snapshot_observed_at":"2026-08-12T22:15:29.045785Z","submitted_at":"2024-10-24T23:43:50Z","title":"Predicting Liquidity Coverage Ratio with Gated Recurrent Units: A Deep Learning Model for Risk Management","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.19211","snapshot_observed_at":"2026-08-12T17:55:17.996178Z","title":"Predicting Liquidity Coverage Ratio with Gated Recurrent Units: A Deep Learning Model for Risk Management,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:17.996178Z"},"links":{"cited_paper":"/paper/2410.19211","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:a520112fd147a9c717ba9a6099fb18228b6a116cb3d9817dd56db7351890118c","observation_id":"9bb47e28-f1d5-4dd9-a322-c1aacb4fbed3","resolution":{"observed_at":"2026-08-12T17:55:17.996178Z","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":"2026-08-12T17:55:18.001652Z","title":"Survival prediction across diverse cancer types using neural networks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.001652Z"},"links":{"citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:505ecf582bc4e46cc0c7954fdc8f3ff0d58cec2989cbb1254a848ef9d9ed1ea0","observation_id":"ca88b440-24eb-4afb-94e6-a21dc7bfe4ed","resolution":{"observed_at":"2026-08-12T17:55:18.001652Z","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":"2026-08-12T17:55:18.006167Z","title":"Financial Risk Analysis Using Integrated Data and Transformer-Based Deep Learning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.006167Z"},"links":{"citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:d39b054376ba4a4e7a42ca91a8b1bd54194fea7d0f961fc4e573ce06b288b90d","observation_id":"5b9194bf-dd2b-4c4d-bc36-aeba1a2c98cb","resolution":{"observed_at":"2026-08-12T17:55:18.006167Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13099","last_updated":"2024-10-17T00:05:05Z","snapshot_observed_at":"2026-08-12T22:21:25.320218Z","submitted_at":"2024-10-17T00:05:05Z","title":"Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13099","snapshot_observed_at":"2026-08-12T17:55:18.010791Z","title":"Adversarial Neural Networks in Medical Imaging Advancements and Challenges in Semantic Segmentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.010791Z"},"links":{"cited_paper":"/paper/2410.13099","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:cbd611ce94059d78c5d4686b57c8133951f9e696bbe9d4d78094da5d6059de59","observation_id":"d4e513ad-e6f2-4e45-8a76-ec29526045f1","resolution":{"observed_at":"2026-08-12T17:55:18.010791Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.20792","last_updated":"2024-10-28T07:17:45Z","snapshot_observed_at":"2026-08-12T22:14:02.055159Z","submitted_at":"2024-10-28T07:17:45Z","title":"Deep Learning for Medical Text Processing: BERT Model Fine-Tuning and Comparative Study","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.20792","snapshot_observed_at":"2026-08-12T17:55:18.015238Z","title":"Deep Learning for Medical Text Processing: BERT Model Fine-Tuning and Comparative Study,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.015238Z"},"links":{"cited_paper":"/paper/2410.20792","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:14d15b5f3813df7ba6462ad059364f372f53b218a20f3becec69e88bc01dc04f","observation_id":"1d9e6b9f-d04e-4eb3-ae9e-b668c840f867","resolution":{"observed_at":"2026-08-12T17:55:18.015238Z","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":"2026-08-12T17:55:18.362848Z","title":"How to Cache Important Contents for Multi-modal Service in Dynamic Networks: A DRL-based Caching Scheme,","venue":null,"work_id":"aa80bff9-fe21-4869-9fc8-7f660b706356","year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.019210Z"},"links":{"citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:5c319087c96dc5702aa813ba7dc0d2344bf1d1779c061a72414fe5b8a2c567f4","observation_id":"19ccac88-1acd-4cf5-be63-693c7cd68b1a","resolution":{"observed_at":"2026-08-12T17:55:18.367928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.17586","last_updated":"2024-10-23T06:20:37Z","snapshot_observed_at":"2026-08-12T22:17:01.545477Z","submitted_at":"2024-10-23T06:20:37Z","title":"Efficient and Aesthetic UI Design with a Deep Learning-Based Interface Generation Tree Algorithm","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.17586","snapshot_observed_at":"2026-08-12T17:55:18.022734Z","title":"Efficient and Aesthetic UI Design with a Deep Learning-Based Interface Generation Tree Algorithm,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.022734Z"},"links":{"cited_paper":"/paper/2410.17586","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:deb455313e3bfc7e2803b133187e16b5e1a4919aeb44cc57aa4861db2e7cc343","observation_id":"492cdbc8-2cee-4df3-aac4-5daeaf08e682","resolution":{"observed_at":"2026-08-12T17:55:18.022734Z","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":"2026-08-12T17:55:18.346511Z","title":"Research on Intelligent System of Medical Image Recognition and Disease Diagnosis Based on Big Data,","venue":null,"work_id":"d2bf0a7d-a815-4abf-81a2-c16e2ac194bd","year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.027111Z"},"links":{"citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:abfb3a2d9db2c9b73275895e0fbc4444bb370fcb197fe2198b6e1abf88c9cd6d","observation_id":"e9e025e3-9aae-4027-9d0b-37401c73ec44","resolution":{"observed_at":"2026-08-12T17:55:18.351162Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.24046","last_updated":"2024-10-31T15:42:24Z","snapshot_observed_at":"2026-08-12T22:10:34.371726Z","submitted_at":"2024-10-31T15:42:24Z","title":"Deep Learning with HM-VGG: AI Strategies for Multi-modal Image Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.24046","snapshot_observed_at":"2026-08-12T17:55:18.031207Z","title":"Deep Learning with HM- VGG: AI Strategies for Multi-modal Image Analysis,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.031207Z"},"links":{"cited_paper":"/paper/2410.24046","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:7a9bc1f4a94f5bc867f0f98de86fca5f4c53e2130cb4d6509537a8d709b26af2","observation_id":"11c34667-3e37-4c52-a71e-876bb8657b63","resolution":{"observed_at":"2026-08-12T17:55:18.031207Z","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":"2026-08-12T17:55:18.332763Z","title":"A Systematic Study on the Privacy Protection Mechanism of Natural Language Processing in Medical Health Records,","venue":null,"work_id":"a16ff315-3fab-464e-8d22-668dea469176","year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.035961Z"},"links":{"citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:3d9906c6ac08188481d1ac310553fdddf75865ea43027afda245c89c88099eab","observation_id":"eeb4720f-f4c4-4ceb-89b5-126bb0c4b420","resolution":{"observed_at":"2026-08-12T17:55:18.337318Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.14165","last_updated":"2024-10-18T04:13:51Z","snapshot_observed_at":"2026-08-12T22:20:23.616311Z","submitted_at":"2024-10-18T04:13:51Z","title":"Automated Genre-Aware Article Scoring and Feedback Using Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.14165","snapshot_observed_at":"2026-08-12T17:55:18.040512Z","title":"Automated Genre-Aware Article Scoring and Feedback Using Large Language Models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.040512Z"},"links":{"cited_paper":"/paper/2410.14165","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:92669f696317fc221d3db5d8803b198aad9475efadc14a4e7f7da7f3eeea0496","observation_id":"1a13b766-32c3-4dd5-acb3-0d36dfefcbd0","resolution":{"observed_at":"2026-08-12T17:55:18.040512Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.15026","last_updated":"2024-10-19T07:49:21Z","snapshot_observed_at":"2026-08-12T22:19:35.621330Z","submitted_at":"2024-10-19T07:49:21Z","title":"A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.15026","snapshot_observed_at":"2026-08-12T17:55:18.044764Z","title":"A Recommendation Model Utilizing Separation Embedding and Self- Attention for Feature Mining,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.044764Z"},"links":{"cited_paper":"/paper/2410.15026","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:26f33681f6ec16528bb62011f7cb55aa49bbbcf39e30b684aa081f6f769bab8a","observation_id":"53f067ed-11c4-42f2-af8e-09c91b720fca","resolution":{"observed_at":"2026-08-12T17:55:18.044764Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.14167","last_updated":"2024-10-18T04:17:49Z","snapshot_observed_at":"2026-08-12T22:20:23.375046Z","submitted_at":"2024-10-18T04:17:49Z","title":"Optimizing Retrieval-Augmented Generation with Elasticsearch for Enhanced Question-Answering Systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.14167","snapshot_observed_at":"2026-08-12T17:55:18.049432Z","title":"Optimizing Retrieval-Augmented Generation with Elasticsearch for Enhanced Question-Answering Systems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.049432Z"},"links":{"cited_paper":"/paper/2410.14167","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:2886ed90467f99b6c6c8b08cfd3006e0882a249c78c06c5af4b281a63dcff892","observation_id":"bb48289a-7f9e-4ee4-99cb-a5e08c6360d8","resolution":{"observed_at":"2026-08-12T17:55:18.049432Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.17617","last_updated":"2024-10-23T07:14:37Z","snapshot_observed_at":"2026-08-12T22:16:59.566986Z","submitted_at":"2024-10-23T07:14:37Z","title":"Self-Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.17617","snapshot_observed_at":"2026-08-12T17:55:18.053627Z","title":"Self- Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.053627Z"},"links":{"cited_paper":"/paper/2410.17617","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:fba40f5dfb7c89b27ddbf02055026d96bb9d8304e49e7543892327b65f9d3f3c","observation_id":"d0974288-6add-4e88-9dea-899d33314667","resolution":{"observed_at":"2026-08-12T17:55:18.053627Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.03572","last_updated":"2024-11-06T00:23:55Z","snapshot_observed_at":"2026-08-12T22:06:52.154746Z","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":"2026-08-12T17:55:18.057584Z","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":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.057584Z"},"links":{"cited_paper":"/paper/2411.03572","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:07408f64ef87246d451c5a838d835fee7c17cd94356ca089051cb16fa3eca6f9","observation_id":"30badd69-1c17-4663-a888-760331d05734","resolution":{"observed_at":"2026-08-12T17:55:18.057584Z","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":"2026-08-12T17:55:18.319085Z","title":"Transformers in Opinion Mining: Addressing Semantic Complexity and Model Challenges in NLP,","venue":null,"work_id":"e82a8eb0-826f-4f99-b24f-95754d2ab359","year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.061985Z"},"links":{"citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:96a8eb0bbff49aaf9fb8d2ffdc21615ac63ff55e29db1b617f101b5365c4ba3b","observation_id":"54d82cac-3527-4c3b-bf06-9d5486b32fd8","resolution":{"observed_at":"2026-08-12T17:55:18.323381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.14327","last_updated":"2024-10-08T07:14:04Z","snapshot_observed_at":"2026-08-12T22:40:16.837795Z","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":"2026-08-12T17:55:18.066981Z","title":"Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Mining","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.066981Z"},"links":{"cited_paper":"/paper/2409.14327","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:d7d46c2c66b050c6cd0dab0d52c9a0a36f1f42186ba8278ad28ef0848135b90e","observation_id":"067dcd06-e3e5-4130-809e-e3ffc6533b70","resolution":{"observed_at":"2026-08-12T17:55:18.066981Z","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":"2026-08-12T17:55:18.305572Z","title":"Leveraging Deep Learning Techniques for Enhanced Analysis of Medical Textual Data,","venue":null,"work_id":"7e60cbca-84d3-427e-841c-40fd08230d5f","year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.071686Z"},"links":{"citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:6e4f6e2f8085bc1b49295ab0d6fd8a155cfe372ec61bc9f3029d12b69d60763b","observation_id":"a4c98a06-a969-42ec-b689-d40078988962","resolution":{"observed_at":"2026-08-12T17:55:18.309844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12259","last_updated":"2024-10-16T05:58:08Z","snapshot_observed_at":"2026-08-12T22:22:09.181633Z","submitted_at":"2024-10-16T05:58:08Z","title":"Optimizing YOLOv5s Object Detection through Knowledge Distillation algorithm","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12259","snapshot_observed_at":"2026-08-12T17:55:18.076703Z","title":"Optimizing YOLOv5s Object Detection through Knowledge Distillation Algorithm,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.076703Z"},"links":{"cited_paper":"/paper/2410.12259","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:ed46781cc902e9051e18eaa22924c94f72563a9141d3f7fa8118cc2ced21b419","observation_id":"31d9a537-49a2-421b-98f9-0d48cae8ac29","resolution":{"observed_at":"2026-08-12T17:55:18.076703Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.08553","last_updated":"2024-10-11T06:05:10Z","snapshot_observed_at":"2026-08-12T22:25:43.694685Z","submitted_at":"2024-10-11T06:05:10Z","title":"Balancing Innovation and Privacy: Data Security Strategies in Natural Language Processing Applications","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.08553","snapshot_observed_at":"2026-08-12T17:55:18.081089Z","title":"Balancing Innovation and Privacy: Data Security Strategies in Natural Language Processing Applications,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.081089Z"},"links":{"cited_paper":"/paper/2410.08553","citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:29bc0f36b28151f7f655ed1156a395cd7819376b74f956dbc8f39f950ea58f96","observation_id":"cb5f0b3d-0edd-4813-bc1e-582df3ea0f3f","resolution":{"observed_at":"2026-08-12T17:55:18.081089Z","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":"2026-08-12T17:55:18.289744Z","title":"RC-RNN: Reconfigurable Cache Architecture for Storage Systems Using Recurrent Neural Networks,","venue":null,"work_id":"820616fc-2fd0-44c3-ba49-97aa2a5a7ebb","year":2021},"citing_paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T17:55:18.085618Z"},"links":{"citing_paper":"/paper/2411.12161"},"observation_digest":"sha256:c7d14d65c7cd637935e1c864bfc331bbfe9bfc60387f6258bfe36e22cc507af8","observation_id":"1abfa638-6780-4403-86a7-e43708bf1a1a","resolution":{"observed_at":"2026-08-12T17:55:18.295874Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2411.12161","last_updated":"2024-11-19T01:55:26Z","latest_version":1,"primary_category":"cs.DC","snapshot_observed_at":"2026-08-12T17:48:40.654604Z","submitted_at":"2024-11-19T01:55:26Z","title":"Adaptive Cache Management for Complex Storage Systems Using CNN-LSTM-Based Spatiotemporal Prediction"},"reference_resolution":{"displayed":23,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":15,"verified_exact":0,"verified_fuzzy":8},"total_outbound_references":23},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 9 inbound Pith citation observations for arXiv:2411.12161."}