{"as_of":"2026-08-08T01:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7990cbe53a91d23f6923dfbb5226a4a2f94039455b9adf8e7fe97b43bbf98aac","coverage":[{"denominator":17,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T22:09:16.309676Z","state":"measured"},{"denominator":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-30T21:04:02.263300Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-06-30T21:05:03.827879Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"cited_work":{"arxiv_id":"2508.07470","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2508.07470","snapshot_observed_at":"2026-06-30T21:05:03.827879Z","title":"Aura: A fine-grained benchmark and decomposed metric for audio-visual reasoning","venue":null,"work_id":"f9245935-9791-45d9-81f4-7cd16ffa1e9f","year":2025},"citing_paper":{"arxiv_id":"2605.14358","last_updated":"2026-05-14T04:35:45Z","snapshot_observed_at":"2026-08-02T19:01:30.832235Z","submitted_at":"2026-05-14T04:35:45Z","title":"Uncovering the Representation Geometry of Minimal Cores in Overcomplete Reasoning Traces","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-06-30T21:04:02.263300Z"},"links":{"cited_paper":"/paper/2508.07470","citing_paper":"/paper/2605.14358"},"observation_digest":"sha256:334fdb221a2e87dd292b6317ab0e70e036bb42e82809e1f23f75ba13bdc4a78e","observation_id":"7d8ab9f7-1791-41e7-8467-231f65af8c49","resolution":{"observed_at":"2026-06-30T21:05:03.829322Z","resolver_source":"arxiv_id","status":"malformed_identifier"},"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/2508.07470/citation-record","integrity":"/paper/2508.07470/integrity","json":"/paper/2508.07470/citation-record.json","paper":"/paper/2508.07470"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.21080","last_updated":"2025-06-26T08:09:16Z","snapshot_observed_at":"2026-08-07T17:47:39.726590Z","submitted_at":"2025-06-26T08:09:16Z","title":"EgoAdapt: Adaptive Multisensory Distillation and Policy Learning for Efficient Egocentric Perception","version":1},"cited_work":{"arxiv_id":"2506.21080","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.21080","snapshot_observed_at":"2026-08-05T22:09:16.733694Z","title":"EgoAdapt: Adaptive Multisensory Distillation and Policy Learning for Efficient Egocentric Perception","venue":"cs.CV","work_id":"e51b7022-bda4-463f-ac8e-d93742d15472","year":2025},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:15.243340Z"},"links":{"cited_paper":"/paper/2506.21080","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:28b7f6d0ca85cf29ae7fe70268605d6c835de303017038c41e58d65e874e9452","observation_id":"bf48b8a6-817a-4536-915f-b4ca919a677b","resolution":{"observed_at":"2026-08-05T22:09:16.793393Z","resolver_source":"local_arxiv","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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T22:09:15.343828Z","title":"Girdhar, R.; El-Nouby, A.; Liu, Z.; Singh, M.; Alwala, K","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:15.343828Z"},"links":{"citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:81b69f3a281d5eda39ef930d06e6632ce15dcaa48c165d9be68841430e9e24b5","observation_id":"3de3c3d9-f400-40bc-8f61-ad4adf1bb35d","resolution":{"observed_at":"2026-08-05T22:09:15.343828Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2011.11760","last_updated":"2020-11-10T21:49:14Z","snapshot_observed_at":"2026-08-06T11:42:54.284269Z","submitted_at":"2020-11-10T21:49:14Z","title":"Multimodal Pretraining for Dense Video Captioning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2011.11760","snapshot_observed_at":"2026-08-05T22:09:15.603717Z","title":"arXiv preprint arXiv:2011.11760","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:15.603717Z"},"links":{"cited_paper":"/paper/2011.11760","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:0a0664a824f5340e522334ae684b73dde86a36130c5b06dc208034e6aa39c1a3","observation_id":"5dc66f6d-baec-4bf6-9559-c827d76c459a","resolution":{"observed_at":"2026-08-05T22:09:15.603717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.20204","last_updated":"2024-06-26T12:31:48Z","snapshot_observed_at":"2026-07-06T18:22:48.671656Z","submitted_at":"2024-05-30T16:07:54Z","title":"Jina CLIP: Your CLIP Model Is Also Your Text Retriever","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.20204","snapshot_observed_at":"2026-08-05T22:09:15.681915Z","title":"In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 13700–13710","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:15.681915Z"},"links":{"cited_paper":"/paper/2405.20204","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:cf6f8bfd4285179fefec63f7e1d9c26459ef8d6673554b323af202be81ce8c95","observation_id":"2b12457c-5b01-447d-ac71-1375b9ea22f4","resolution":{"observed_at":"2026-08-05T22:09:15.681915Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02255","last_updated":"2024-01-21T03:47:06Z","snapshot_observed_at":"2026-07-06T16:27:15.027202Z","submitted_at":"2023-10-03T17:57:24Z","title":"MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.02255","snapshot_observed_at":"2026-08-05T22:09:15.767519Z","title":"arXiv preprint arXiv:2310.02255","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:15.767519Z"},"links":{"cited_paper":"/paper/2310.02255","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:5ff628157e459a798164ea2dbf2ba229795305028ca655f722da1cbcc45b29ea","observation_id":"32fe63cb-5832-4136-91ac-6194506ec5c5","resolution":{"observed_at":"2026-08-05T22:09:15.767519Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.05424","last_updated":"2024-06-10T01:36:53Z","snapshot_observed_at":"2026-07-06T15:40:24.127663Z","submitted_at":"2023-06-08T17:59:56Z","title":"Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.05424","snapshot_observed_at":"2026-08-05T22:09:15.844231Z","title":"arXiv preprint arXiv:2306.05424","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:15.844231Z"},"links":{"cited_paper":"/paper/2306.05424","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:d463d06d3c99d0e47171b5d11af89db75907af4593ef89301725008a0f5b5352","observation_id":"6ce1a547-b414-41aa-948d-4eef6ec84102","resolution":{"observed_at":"2026-08-05T22:09:15.844231Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-05T22:09:16.061859Z","title":"In Proceedings of the IEEE/CVF inter- national conference on computer vision, 1686–1697","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:16.061859Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:7fee52133d991764853213407bfb642e652b45bf00c2242344abb4fe6d1538eb","observation_id":"04d8c846-5ee5-46db-86a6-f8a3f6ead5d3","resolution":{"observed_at":"2026-08-05T22:09:16.061859Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.04933","last_updated":"2024-07-11T12:03:35Z","snapshot_observed_at":"2026-08-01T14:51:24.361620Z","submitted_at":"2024-04-07T12:14:42Z","title":"UniMD: Towards Unifying Moment Retrieval and Temporal Action Detection","version":2},"cited_work":{"arxiv_id":"2404.04933","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.04933","snapshot_observed_at":"2026-08-05T22:09:16.453207Z","title":"UniMD: Towards Unifying Moment Retrieval and Temporal Action Detection","venue":"cs.CV","work_id":"599906f3-ca0b-4adf-8d0e-d86931ab6588","year":2024},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:16.128976Z"},"links":{"cited_paper":"/paper/2404.04933","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:a9db7a5ea56f4acfaca80a2368273b063ca5f8e3e4adda6dd81a3e379dd42b3d","observation_id":"b8227ad1-5869-42b2-abee-d7d250b9f5d2","resolution":{"observed_at":"2026-08-05T22:09:16.487647Z","resolver_source":"local_arxiv","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":"2203.01225","last_updated":"2022-11-02T05:25:06Z","snapshot_observed_at":"2026-07-30T11:11:52.165985Z","submitted_at":"2022-03-02T16:34:09Z","title":"Video Question Answering: Datasets, Algorithms and Challenges","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.01225","snapshot_observed_at":"2026-08-05T22:09:16.203189Z","title":"arXiv preprint arXiv:2203.01225","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:16.203189Z"},"links":{"cited_paper":"/paper/2203.01225","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:dcc322340a56390f216bb184df943f38daaa1c3a368c52c391825c2b5dcca48f","observation_id":"0b428c00-5abe-47ad-9039-1b4c412a6a56","resolution":{"observed_at":"2026-08-05T22:09:16.203189Z","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":"2026-08-05T22:09:16.932312Z","title":"In Inter- national Conference on Learning Representations (ICLR)","venue":null,"work_id":"d85980b5-98af-4d0a-af29-57588d846c54","year":2024},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:16.309676Z"},"links":{"citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:99b45f9ed01a4e83de049addde4b2496d8250b1ede273b1311d389a92f848747","observation_id":"3deea570-b5f0-447b-afb2-615e92829ac0","resolution":{"observed_at":"2026-08-05T22:09:17.047351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.08835","last_updated":"2024-07-03T18:05:02Z","snapshot_observed_at":"2026-08-04T18:08:42.450729Z","submitted_at":"2023-11-15T10:22:35Z","title":"Correlation-Guided Query-Dependency Calibration for Video Temporal Grounding","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.08835","snapshot_observed_at":"2026-08-05T22:09:15.943570Z","title":"In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 3195–3204","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:15.943570Z"},"links":{"cited_paper":"/paper/2311.08835","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:44eb6c462da8fe6869d28682a04a7e2016860a7cf0ded47f7301118ec39b4eeb","observation_id":"9838723f-089b-415e-9c58-314d24b06794","resolution":{"observed_at":"2026-08-05T22:09:15.943570Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.03905","last_updated":"2023-09-11T20:25:16Z","snapshot_observed_at":"2026-07-06T16:15:50.904062Z","submitted_at":"2023-09-07T17:59:45Z","title":"ImageBind-LLM: Multi-modality Instruction Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.03905","snapshot_observed_at":"2026-08-05T22:09:15.507027Z","title":"In Proceedings of the 37th International Confer- ence on Machine Learning (ICML), 3929–3938","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:15.507027Z"},"links":{"cited_paper":"/paper/2309.03905","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:71e2a1f2f7632a0512fe937ea389918c55c84889a0a4d280c32086717c750651","observation_id":"92a9f263-beb7-438d-bfcf-52840dfc59a3","resolution":{"observed_at":"2026-08-05T22:09:15.507027Z","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":"2026-08-05T22:09:17.117820Z","title":"In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 11287–11297","venue":null,"work_id":"a535b26a-12b9-42be-a8fc-5d48e4227452","year":2025},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:15.424425Z"},"links":{"citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:08b77e141991de28f603d6cff1eafb187fe227a1b0e8bdea846a259f0ce83b2c","observation_id":"ad6c6200-5aad-49e1-8cbb-e7cb7e6f0e10","resolution":{"observed_at":"2026-08-05T22:09:17.257252Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.14906","last_updated":"2024-07-15T16:42:22Z","snapshot_observed_at":"2026-08-06T09:24:20.916176Z","submitted_at":"2023-11-25T02:46:12Z","title":"AutoEval-Video: An Automatic Benchmark for Assessing Large Vision Language Models in Open-Ended Video Question Answering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.14906","snapshot_observed_at":"2026-08-05T22:09:14.941204Z","title":"In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), 5558–5570","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:14.941204Z"},"links":{"cited_paper":"/paper/2311.14906","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:9f482ca3c6ca1478bb5f8c9aaa8e2d02a37b49599277408a6196a6b0451e79b4","observation_id":"15aa2a3b-5e70-45df-922d-dd1d97003e78","resolution":{"observed_at":"2026-08-05T22:09:14.941204Z","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":"2026-08-05T22:09:17.327510Z","title":"See https://vicuna","venue":null,"work_id":"24b6a493-cbc4-4d9b-a6dd-fef965616364","year":2023},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:15.153338Z"},"links":{"citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:938e69cd76f5036d26505f3751fed70ef8f33e93d05db53e0b27abe619419011","observation_id":"ea2b809f-564d-4508-92df-bd75ce360936","resolution":{"observed_at":"2026-08-05T22:09:17.434401Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.07476","last_updated":"2024-10-30T06:49:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-06-11T17:22:23Z","title":"VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.07476","snapshot_observed_at":"2026-08-05T22:09:15.067940Z","title":"arXiv preprint arXiv:2406.07476","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:15.067940Z"},"links":{"cited_paper":"/paper/2406.07476","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:b59e7d1b7967c31b14ffdd3177f5002c4fdc855a52acb84988e7fc389e7d779f","observation_id":"ce3dab9b-d7de-4e10-903b-f2b647d01ca7","resolution":{"observed_at":"2026-08-05T22:09:15.067940Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.15339","last_updated":"2023-12-28T02:57:22Z","snapshot_observed_at":"2026-07-06T16:37:27.609912Z","submitted_at":"2023-10-23T20:08:30Z","title":"Non-invertible Symmetries in 2D from Type IIB String Theory","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.15339","snapshot_observed_at":"2026-08-05T22:09:14.844607Z","title":"InProceedings of the Com- puter Vision and Pattern Recognition Conference , 24817– 24826","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-05T22:09:14.844607Z"},"links":{"cited_paper":"/paper/2310.15339","citing_paper":"/paper/2508.07470"},"observation_digest":"sha256:9a7c1921c57ac74fcef9e87f587ee97bbeca8e75be23f2379e5d860a7b5fdc6d","observation_id":"de74c809-b302-4a26-9fd4-f05ed2a14e2f","resolution":{"observed_at":"2026-08-05T22:09:14.844607Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2508.07470","last_updated":"2025-08-21T16:39:49Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T09:50:14.288346Z","submitted_at":"2025-08-10T20:06:42Z","title":"AURA: A Fine-Grained Benchmark and Decomposed Metric for Audio-Visual Reasoning"},"reference_resolution":{"displayed":17,"state_counts":{"malformed_identifier":0,"metadata_mismatch":2,"parse_uncertain":0,"unresolved":12,"verified_exact":0,"verified_fuzzy":3},"total_outbound_references":17},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 1 inbound Pith citation observation for arXiv:2508.07470."}