{"as_of":"2026-08-07T17:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6c596b5d8170591f6ac3a0d8e99cb6f68ec72e8c47ad1fa3b0e6c2e69a539cd1","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":17,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":17,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":17,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T12:12:54.731819Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":56,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":"2305.15005","doi":"10.48550/arxiv.2305.15005","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2305.15005 , year=","venue":"arXiv (Cornell University)","work_id":"9be9a3b0-6688-4088-b463-8f6e2f0f0221","year":2023},"citing_paper":{"arxiv_id":"2309.08532","last_updated":"2025-05-01T11:56:52Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-15T16:50:09Z","title":"EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers","version":3},"reference_index":126,"source":"arxiv_source","source_observed_at":"2026-05-16T06:11:49.475825Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2309.08532"},"observation_digest":"sha256:1aeb27aa4e9d29143ce075e192cbd8bcf677fdf4854ec4bd91e381b545221f07","observation_id":"5206f7e6-0458-452e-bee9-5a8a08ece2fd","resolution":{"observed_at":"2026-05-16T06:11:49.646511Z","resolver_source":"arxiv_id","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":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":"2305.15005","doi":"10.48550/arxiv.2305.15005","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2305.15005 , year=","venue":"arXiv (Cornell University)","work_id":"9be9a3b0-6688-4088-b463-8f6e2f0f0221","year":2023},"citing_paper":{"arxiv_id":"2310.11113","last_updated":"2024-09-07T06:30:56Z","snapshot_observed_at":"2026-07-06T16:34:23.428329Z","submitted_at":"2023-10-17T09:53:03Z","title":"Revisiting Sentiment Analysis for Software Engineering in the Era of Large Language Models","version":3},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-05-24T06:12:38.139005Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2310.11113"},"observation_digest":"sha256:17eece0d821de4b75858fb1ce6b2a0a4c3dd81077b0642d518670e9a437ad902","observation_id":"e5e41f21-9fff-411c-943d-bf45ed0b95bc","resolution":{"observed_at":"2026-05-24T06:13:59.994944Z","resolver_source":"arxiv_id","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":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":"2305.15005","doi":"10.48550/arxiv.2305.15005","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2305.15005 , year=","venue":"arXiv (Cornell University)","work_id":"9be9a3b0-6688-4088-b463-8f6e2f0f0221","year":2023},"citing_paper":{"arxiv_id":"2406.04244","last_updated":"2024-06-06T16:41:39Z","snapshot_observed_at":"2026-07-30T15:43:06.151242Z","submitted_at":"2024-06-06T16:41:39Z","title":"Benchmark Data Contamination of Large Language Models: A Survey","version":1},"reference_index":180,"source":"pdf_text","source_observed_at":"2026-05-22T23:10:40.420241Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2406.04244"},"observation_digest":"sha256:3a8e9796089680bc3c1eb3f4c9cea59c87cb32edddd4925c39823605c65940b4","observation_id":"4aa91919-f772-4dad-8886-38f6ac9667c9","resolution":{"observed_at":"2026-05-22T23:10:41.146636Z","resolver_source":"arxiv_id","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":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-07T12:12:54.731819Z","title":"Sen- timent analysis in the era of large language models: A reality check,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.00312","last_updated":"2025-05-30T23:45:53Z","snapshot_observed_at":"2026-08-07T12:05:29.974731Z","submitted_at":"2025-05-30T23:45:53Z","title":"An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-07T12:12:54.731819Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2506.00312"},"observation_digest":"sha256:6349c5f8bd09628371998f9a02e15f2cc00a4747e8e756d04afcdfa3dd988f1d","observation_id":"adf39d5e-bce4-48db-98d4-7638a0434870","resolution":{"observed_at":"2026-08-07T12:12:54.731819Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-07T11:57:56.793366Z","title":"Sentiment analysis in the era of large language models: A reality check,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01001","last_updated":"2025-06-01T13:13:20Z","snapshot_observed_at":"2026-08-07T11:50:58.394133Z","submitted_at":"2025-06-01T13:13:20Z","title":"FedQuad: Adaptive Layer-wise LoRA Deployment and Activation Quantization for Federated Fine-Tuning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:57:56.793366Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2506.01001"},"observation_digest":"sha256:1fda20fb2a9d836ffd3057486625d37f0f20edbbab195a5afcdbf904cfb86f36","observation_id":"3d752210-7274-478a-9cc0-4b386ecdfb26","resolution":{"observed_at":"2026-08-07T11:57:56.793366Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-07T10:56:26.968791Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.03870","last_updated":"2025-06-04T12:01:17Z","snapshot_observed_at":"2026-08-07T10:51:10.020311Z","submitted_at":"2025-06-04T12:01:17Z","title":"Evaluating Apple Intelligence's Writing Tools for Privacy Against Large Language Model-Based Inference Attacks: Insights from Early Datasets","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-07T10:56:26.968791Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2506.03870"},"observation_digest":"sha256:117432b1432b23336724b88405cdeea7096c95c7f041fa168e38bb95273a73c2","observation_id":"c8efe1ec-8dab-4059-81e6-ace721226b17","resolution":{"observed_at":"2026-08-07T10:56:26.968791Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-06T23:28:13.454752Z","title":"Can large language models provide faithful explana- tions for fake news detection?","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.17878","last_updated":"2025-06-22T02:39:27Z","snapshot_observed_at":"2026-08-06T23:21:16.454744Z","submitted_at":"2025-06-22T02:39:27Z","title":"Towards Robust Fact-Checking: A Multi-Agent System with Advanced Evidence Retrieval","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T23:28:13.454752Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2506.17878"},"observation_digest":"sha256:46693c7daf1ffa7598d9d2f7d417f778b4ebbc50f9df5930e9471373e91172db","observation_id":"24b547af-44cd-4425-a524-8bf432fdf6a3","resolution":{"observed_at":"2026-08-06T23:28:13.454752Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-06T22:33:30.213045Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.21288","last_updated":"2025-06-26T14:09:41Z","snapshot_observed_at":"2026-08-06T22:25:11.524521Z","submitted_at":"2025-06-26T14:09:41Z","title":"Small Encoders Can Rival Large Decoders in Detecting Groundedness","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-06T22:33:30.213045Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2506.21288"},"observation_digest":"sha256:c951af186d6746f94397bbf7c4ed163774da5c6b43cfc06f9d85578bef41526a","observation_id":"e79aaf74-4d4a-488c-9a63-86230b60558b","resolution":{"observed_at":"2026-08-06T22:33:30.213045Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-06T15:20:38.735819Z","title":"Sentiment analysis in the era of large language models: A reality check","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.16217","last_updated":"2025-08-29T18:45:22Z","snapshot_observed_at":"2026-08-06T15:12:57.737368Z","submitted_at":"2025-07-22T04:21:03Z","title":"Towards Compute-Optimal Many-Shot In-Context Learning","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T15:20:38.735819Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2507.16217"},"observation_digest":"sha256:f429a2def3109723d4d4c535dd447e0117201487b127fe640daf1d622bb869e4","observation_id":"5fa91c2f-1b3f-41cd-8f40-a19b62036401","resolution":{"observed_at":"2026-08-06T15:20:38.735819Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-05T19:46:11.605271Z","title":"Ziems, et al., Can large language models be consistently trusted for factuality detection?, arXiv preprint arXiv:2305.15005 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.11823","last_updated":"2025-08-15T21:57:27Z","snapshot_observed_at":"2026-08-05T19:46:10.670948Z","submitted_at":"2025-08-15T21:57:27Z","title":"Hallucination Detection and Mitigation in Scientific Text Simplification using Ensemble Approaches: DS@GT at CLEF 2025 SimpleText","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T19:46:11.605271Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2508.11823"},"observation_digest":"sha256:8111680c7eea149200852696af145958e9742bed21091868681b1887495c270c","observation_id":"77b1db83-f1ef-4734-82e2-95e740bc0d3c","resolution":{"observed_at":"2026-08-05T19:46:11.605271Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-04T05:46:08.884428Z","title":"Sentiment analysis in the era of large language models: A reality check.arXiv preprint arXiv:2305.15005,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.26775","last_updated":"2026-03-24T18:07:40Z","snapshot_observed_at":"2026-08-07T01:27:24.549627Z","submitted_at":"2026-03-24T18:07:40Z","title":"Learning to Select Visual In-Context Demonstrations","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-04T05:46:08.884428Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2603.26775"},"observation_digest":"sha256:200581e36e1bbfbabbc39a1968541df762dfad8f2b2af539fce13915738804c7","observation_id":"d3d81936-741d-4939-822e-eb5e0150f823","resolution":{"observed_at":"2026-08-04T05:46:08.884428Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":"2305.15005","doi":"10.48550/arxiv.2305.15005","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2305.15005 , year=","venue":"arXiv (Cornell University)","work_id":"9be9a3b0-6688-4088-b463-8f6e2f0f0221","year":2023},"citing_paper":{"arxiv_id":"2604.07369","last_updated":"2026-04-07T05:29:13Z","snapshot_observed_at":"2026-07-06T22:55:37.787732Z","submitted_at":"2026-04-07T05:29:13Z","title":"The Role of Emotional Stimuli and Intensity in Shaping Large Language Model Behavior","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T20:10:12.204925Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2604.07369"},"observation_digest":"sha256:84ff91a2cd9918f6aa0f8150b0be837bdcd27fe41f5763a3e0531cb58d97a02f","observation_id":"b7009859-b6e1-4ed8-a09f-c860eca5bf17","resolution":{"observed_at":"2026-05-10T22:10:50.142881Z","resolver_source":"arxiv_id","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":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":"2305.15005","doi":"10.48550/arxiv.2305.15005","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2305.15005 , year=","venue":"arXiv (Cornell University)","work_id":"9be9a3b0-6688-4088-b463-8f6e2f0f0221","year":2023},"citing_paper":{"arxiv_id":"2604.11312","last_updated":"2026-04-15T13:43:50Z","snapshot_observed_at":"2026-07-06T22:59:45.139155Z","submitted_at":"2026-04-13T11:16:58Z","title":"Network Effects and Agreement Drift in LLM Debates","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-10T15:50:20.833398Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2604.11312"},"observation_digest":"sha256:b7e068260fcdf11a4a56d072a6a0e4c4a8b28aa395b88cef52c571701080ce8e","observation_id":"e346d1f4-f5a2-44de-a3bf-94ee588238ce","resolution":{"observed_at":"2026-05-11T09:46:08.016896Z","resolver_source":"arxiv_id","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":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":"2305.15005","doi":"10.48550/arxiv.2305.15005","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2305.15005 , year=","venue":"arXiv (Cornell University)","work_id":"9be9a3b0-6688-4088-b463-8f6e2f0f0221","year":2023},"citing_paper":{"arxiv_id":"2604.15547","last_updated":"2026-04-16T21:52:11Z","snapshot_observed_at":"2026-08-02T19:53:23.399369Z","submitted_at":"2026-04-16T21:52:11Z","title":"Consistency Analysis of Sentiment Predictions using Syntactic & Semantic Context Assessment Summarization (SSAS)","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-10T10:55:20.435471Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2604.15547"},"observation_digest":"sha256:a3a0865e64a5f9ece8cc4405d2d7d1af9db94ce84b0f1f099ba3913b83401926","observation_id":"a8f074d1-bcd4-4647-b581-1e628f6e9915","resolution":{"observed_at":"2026-05-10T11:00:03.734725Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":"2305.15005","doi":"10.48550/arxiv.2305.15005","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2305.15005 , year=","venue":"arXiv (Cornell University)","work_id":"9be9a3b0-6688-4088-b463-8f6e2f0f0221","year":2023},"citing_paper":{"arxiv_id":"2604.17569","last_updated":"2026-04-19T18:20:05Z","snapshot_observed_at":"2026-07-30T05:57:10.385626Z","submitted_at":"2026-04-19T18:20:05Z","title":"MAPLE: A Meta-learning Framework for Cross-Prompt Essay Scoring","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-05-10T05:58:17.974995Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2604.17569"},"observation_digest":"sha256:ee4b861e140c93e426271e838f880be25fbb9ac25b27c433323b6cda1bc7767f","observation_id":"f1b27fec-7cf7-4002-a4ec-bd00abb25244","resolution":{"observed_at":"2026-05-10T06:01:13.426966Z","resolver_source":"arxiv_id","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":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":"2305.15005","doi":"10.48550/arxiv.2305.15005","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2305.15005 , year=","venue":"arXiv (Cornell University)","work_id":"9be9a3b0-6688-4088-b463-8f6e2f0f0221","year":2023},"citing_paper":{"arxiv_id":"2604.18955","last_updated":"2026-04-21T01:05:52Z","snapshot_observed_at":"2026-07-06T23:05:44.499005Z","submitted_at":"2026-04-21T01:05:52Z","title":"Assessing Capabilities of Large Language Models in Social Media Analytics: A Multi-task Quest","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-05-10T03:20:12.777878Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2604.18955"},"observation_digest":"sha256:9b6f6c853bbef19069eca11a3bee5fa79a8bca8eadab01dc5393f179fb6f60b5","observation_id":"381f3b79-d54f-4210-afc4-8eaff7c58a96","resolution":{"observed_at":"2026-05-11T12:41:01.802868Z","resolver_source":"arxiv_id","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":"2305.15005","last_updated":"2023-05-24T10:45:25Z","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check","version":1},"cited_work":{"arxiv_id":"2305.15005","doi":"10.48550/arxiv.2305.15005","metadata_source":"arxiv_reference","pith_arxiv_id":"2305.15005","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2305.15005 , year=","venue":"arXiv (Cornell University)","work_id":"9be9a3b0-6688-4088-b463-8f6e2f0f0221","year":2023},"citing_paper":{"arxiv_id":"2605.06423","last_updated":"2026-05-07T15:29:10Z","snapshot_observed_at":"2026-07-06T23:18:55.724335Z","submitted_at":"2026-05-07T15:29:10Z","title":"Pop Quiz Attack: Black-box Membership Inference Attacks Against Large Language Models","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-08T09:14:12.034025Z"},"links":{"cited_paper":"/paper/2305.15005","citing_paper":"/paper/2605.06423"},"observation_digest":"sha256:d2ea255d6f2ab037f98f280135530d649233ad8ce04930ace0e8b5e778d725fa","observation_id":"8f9a8f03-cc47-4887-9ad4-60ed49e95a4d","resolution":{"observed_at":"2026-05-11T20:26:09.099112Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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"}}],"links":{"evidence":"/evidence","html":"/paper/2305.15005/citation-record","integrity":"/paper/2305.15005/integrity","json":"/paper/2305.15005/citation-record.json","paper":"/paper/2305.15005"},"outbound":[],"paper":{"arxiv_id":"2305.15005","last_updated":"2023-05-24T10:45:25Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-04T21:30:36.804528Z","submitted_at":"2023-05-24T10:45:25Z","title":"Sentiment Analysis in the Era of Large Language Models: A Reality Check"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2305.15005."}