{"as_of":"2026-08-16T22:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:09daf3fbdcbdc5dfe19b559958233023e5f4822f12841aaf3c9d9c66b05f93cb","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":2,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":2,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T04:36:07.409976Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-10T05:30:23.456663Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-10T05:30:23.456663Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.10169","last_updated":"2023-05-18T13:28:22Z","snapshot_observed_at":"2026-08-16T15:32:22.246849Z","submitted_at":"2023-05-17T12:46:37Z","title":"Few-shot Joint Multimodal Aspect-Sentiment Analysis Based on Generative Multimodal Prompt","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.10169","snapshot_observed_at":"2026-08-12T04:36:07.409976Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.01249","last_updated":"2024-12-02T08:13:40Z","snapshot_observed_at":"2026-08-12T04:29:59.500680Z","submitted_at":"2024-12-02T08:13:40Z","title":"Data Uncertainty-Aware Learning for Multimodal Aspect-based Sentiment Analysis","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-12T04:36:07.409976Z"},"links":{"cited_paper":"/paper/2305.10169","citing_paper":"/paper/2412.01249"},"observation_digest":"sha256:b186ecf021a9bbd3e5332b2fb2318a82d2051e352213a192775b4cc3bcc40e65","observation_id":"cdf9d338-7f85-4dcf-8ec5-23a4985d277a","resolution":{"observed_at":"2026-08-12T04:36:07.409976Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10169","last_updated":"2023-05-18T13:28:22Z","snapshot_observed_at":"2026-08-16T15:32:22.246849Z","submitted_at":"2023-05-17T12:46:37Z","title":"Few-shot Joint Multimodal Aspect-Sentiment Analysis Based on Generative Multimodal Prompt","version":2},"cited_work":{"arxiv_id":"2305.10169","doi":"10.48550/arxiv.2305.10169","metadata_source":"pith","pith_arxiv_id":"2305.10169","snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Few-shot Joint Multimodal Aspect-Sentiment Analysis Based on Generative Multimodal Prompt","venue":"cs.MM","work_id":"c2407e33-0433-4c88-9fc5-38dfe8dc4638","year":2023},"citing_paper":{"arxiv_id":"2507.16854","last_updated":"2025-07-21T11:49:57Z","snapshot_observed_at":"2026-08-15T23:29:22.476756Z","submitted_at":"2025-07-21T11:49:57Z","title":"CLAMP: Contrastive Learning with Adaptive Multi-loss and Progressive Fusion for Multimodal Aspect-Based Sentiment Analysis","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T15:33:00.557656Z"},"links":{"cited_paper":"/paper/2305.10169","citing_paper":"/paper/2507.16854"},"observation_digest":"sha256:9630da68753124e056eb68de23afba1f48db363b86727d84269d0aaf2886e945","observation_id":"64d1c684-43b5-40f6-ad08-fb1ec5670081","resolution":{"observed_at":"2026-08-06T15:33:00.736796Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2305.10169/citation-record","integrity":"/paper/2305.10169/integrity","json":"/paper/2305.10169/citation-record.json","paper":"/paper/2305.10169"},"outbound":[],"paper":{"arxiv_id":"2305.10169","last_updated":"2023-05-18T13:28:22Z","latest_version":2,"primary_category":"cs.MM","snapshot_observed_at":"2026-08-16T15:32:22.246849Z","submitted_at":"2023-05-17T12:46:37Z","title":"Few-shot Joint Multimodal Aspect-Sentiment Analysis Based on Generative Multimodal Prompt"},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2305.10169."}