{"as_of":"2026-08-11T03:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9c6138a552b8b7b484a60e8be92b4abdf76907fe2317ad2318511b46ec862d1d","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T09:59:40.094302Z","state":"measured"},{"denominator":35,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":35,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-01T09:59:37.074456Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2607.27109","snapshot_observed_at":"2026-07-30T11:36:58.831274Z","title":"Overview MMAC is a fine-grained evaluation benchmark for free-form audio captioning","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-30T11:36:58.831274Z"},"links":{"cited_paper":"/paper/2607.27109","citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:5fbc20f0cf8f6919c7d4a1ec8c2245431baa524dd214383108b662644e02c84f","observation_id":"a26f578e-b308-4672-ac91-6103ded435d9","resolution":{"observed_at":"2026-07-30T11:36:58.831274Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2607.27109","snapshot_observed_at":"2026-08-01T09:59:37.074456Z","title":"Overview MMAC is a fine-grained evaluation benchmark for free-form audio captioning","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:37.074456Z"},"links":{"cited_paper":"/paper/2607.27109","citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:0a6f060c9c07d419b3929ac8f45edb6c33818f4272db0a893980067d8785f75a","observation_id":"33dc2a45-5619-480f-ac5d-a244681dbbe5","resolution":{"observed_at":"2026-08-01T09:59:37.074456Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2607.27109/citation-record","integrity":"/paper/2607.27109/integrity","json":"/paper/2607.27109/citation-record.json","paper":"/paper/2607.27109"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:59:36.924139Z","title":"With the development of AudioLLMs [1, 2, 3, 4], captions are moving from brief descriptions to more open-ended and fine- grained audio understanding","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:36.924139Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:84b747461dcd43ee60362827c83d0384d9337567a41f75d8afac7aa074a120e3","observation_id":"4df5a8f2-4c4e-4e81-9671-28d979ddf88d","resolution":{"observed_at":"2026-08-01T09:59:36.924139Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2607.27109","snapshot_observed_at":"2026-08-01T09:59:37.074456Z","title":"Overview MMAC is a fine-grained evaluation benchmark for free-form audio captioning","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:37.074456Z"},"links":{"cited_paper":"/paper/2607.27109","citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:0a6f060c9c07d419b3929ac8f45edb6c33818f4272db0a893980067d8785f75a","observation_id":"33dc2a45-5619-480f-ac5d-a244681dbbe5","resolution":{"observed_at":"2026-08-01T09:59:37.074456Z","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":"2026-08-01T09:59:37.225892Z","title":"Describe this audio in detail","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:37.225892Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:eb6d106694f5757a10c01fb3f01c90cc69e7473afd65ceb441ce0dd52c354a0f","observation_id":"4ebe64a4-17a9-4994-8ffb-c20251a3a30d","resolution":{"observed_at":"2026-08-01T09:59:37.225892Z","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":"2026-08-01T09:59:37.352862Z","title":"Fine-grained dimensions are first averaged within each capability category","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:37.352862Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:462cd13c2c4794a59c5627ec2781590fb2991af0a727ec6032c8e880e78a1402","observation_id":"457195ae-7de4-477f-90e5-e6c37cf3068f","resolution":{"observed_at":"2026-08-01T09:59:37.352862Z","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":"2026-08-01T09:59:37.515614Z","title":"MMAC comprises 6 capability categories and 15 fine-grained dimensions and evaluates the coverage and cor- rectness of target information in free-form captions","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:37.515614Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:e9527982364114ef1af81c286d0a5485b1116ccc8f564dd4ed0975105406e6c9","observation_id":"da110d05-a343-443d-accd-34f524c2101f","resolution":{"observed_at":"2026-08-01T09:59:37.515614Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.20215","last_updated":"2025-03-26T04:17:55Z","snapshot_observed_at":"2026-08-06T08:46:20.194739Z","submitted_at":"2025-03-26T04:17:55Z","title":"Qwen2.5-Omni Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.20215","snapshot_observed_at":"2026-08-01T09:59:37.602524Z","title":"Qwen2.5-omni tech- nical report,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:37.602524Z"},"links":{"cited_paper":"/paper/2503.20215","citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:bfdade0a8ff4856474f21a3ec655a4320a83b28e46d87b8c9994e7e85ae0b4f7","observation_id":"4538e26d-3de4-4ec6-a8ed-3361f2c1bed4","resolution":{"observed_at":"2026-08-01T09:59:37.602524Z","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":"2026-08-01T09:59:37.724790Z","title":"Midashenglm: Efficient audio understanding with general audio captions,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:37.724790Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:95ba059a5dd90f9d4c1a76cea6e4b4fbbcb2e3da4c5ddeb320180e662589f73c","observation_id":"a9cb9266-893e-485d-81c3-4b35982de869","resolution":{"observed_at":"2026-08-01T09:59:37.724790Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.15804","last_updated":"2026-04-21T03:35:14Z","snapshot_observed_at":"2026-08-10T14:43:33.791354Z","submitted_at":"2026-04-17T08:05:46Z","title":"Qwen3.5-Omni Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.15804","snapshot_observed_at":"2026-08-01T09:59:37.878210Z","title":"Qwen3. 5-omni technical report,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:37.878210Z"},"links":{"cited_paper":"/paper/2604.15804","citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:7c328fef8ea854013b2781ffbba975d3390c9aa9c14721c0c2b396894db6274c","observation_id":"a66660a1-e030-4b13-8f54-1c65590f6c64","resolution":{"observed_at":"2026-08-01T09:59:37.878210Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.16632","last_updated":"2025-08-27T16:42:11Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-22T14:23:55Z","title":"Step-Audio 2 Technical Report","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.16632","snapshot_observed_at":"2026-08-01T09:59:38.033277Z","title":"Step-audio 2 technical report,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:38.033277Z"},"links":{"cited_paper":"/paper/2507.16632","citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:14bc5ecc8d7c82c71a664362286952094b8b4850e93fe68455eb9cfe1052fcf2","observation_id":"01bdb891-2d6c-4875-bf15-5b1f57c14925","resolution":{"observed_at":"2026-08-01T09:59:38.033277Z","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":"2026-08-01T09:59:38.202483Z","title":"Wavcaps: A chatgpt-assisted weakly-labelled audio captioning dataset for audio-language multimodal research,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:38.202483Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:1751fdca143c565d543a22a6fa07031d99f02aefb4ae5d42e841cf8f42f25c03","observation_id":"5ca77e76-f96c-4760-9395-668feb1d181b","resolution":{"observed_at":"2026-08-01T09:59:38.202483Z","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":"2026-08-01T09:59:38.365610Z","title":"Audiocaps: Generating captions for audios in the wild,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:38.365610Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:104294bb4a156c76c771c63a508c91170e31d54724fa6f4341552a5a596e551a","observation_id":"fc00fe66-ec57-4814-93cc-77dd1b99c26f","resolution":{"observed_at":"2026-08-01T09:59:38.365610Z","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":"2026-08-01T09:59:38.532284Z","title":"Clotho: An audio captioning dataset,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:38.532284Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:e3fc37ba03b531da04b127589ef405a00f9d08c66aebbb5f34c061f3833a413f","observation_id":"f0a623c7-9f0c-452c-b461-77f1938847e5","resolution":{"observed_at":"2026-08-01T09:59:38.532284Z","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":"2026-08-01T09:59:38.649753Z","title":"Mmau: A massive multi-task audio understanding and reasoning bench- mark,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:38.649753Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:77a6b94f9239b1a1adc474bdbaf7cb6af13022631ec0ca3dc66a2c2e97169e56","observation_id":"d54386a7-ab99-4a16-9be1-0c793ecfb129","resolution":{"observed_at":"2026-08-01T09:59:38.649753Z","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":"2026-08-01T09:59:38.741274Z","title":"Mmar: A chal- lenging benchmark for deep reasoning in speech, audio, music, and their mix,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:38.741274Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:3d157cd0b7046006e4b01845ca5f956bf863d90557be1324f762a21b3ea7519e","observation_id":"3fd35f9f-6b1c-412c-88b8-c60e5a01d0c1","resolution":{"observed_at":"2026-08-01T09:59:38.741274Z","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":"2026-08-01T09:59:38.821754Z","title":"Omni- captioner: Data pipeline, models, and benchmark for omni de- tailed perception,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:38.821754Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:d66f8b4520a9abe428386d03365d9b135c440467736f9d9a2a6c5cb5a4760d52","observation_id":"32a8f721-39f8-4df6-8a9d-2f322c4f6eb2","resolution":{"observed_at":"2026-08-01T09:59:38.821754Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.10905","last_updated":"2026-04-13T02:11:56Z","snapshot_observed_at":"2026-08-10T07:51:32.790882Z","submitted_at":"2026-04-13T02:11:56Z","title":"Audio Flamingo Next: Next-Generation Open Audio-Language Models for Speech, Sound, and Music","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.10905","snapshot_observed_at":"2026-08-01T09:59:38.877892Z","title":"Audio flamingo next: Next-generation open audio-language models for speech, sound, and music,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:38.877892Z"},"links":{"cited_paper":"/paper/2604.10905","citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:7de2101cebe1423bfe889cbac08932ba5729b35a3156b890552811c67849e3dd","observation_id":"15e8ee66-d3cb-4d2d-85ab-0b6bb9d42045","resolution":{"observed_at":"2026-08-01T09:59:38.877892Z","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":"2026-08-01T09:59:38.964974Z","title":"Secap: Speech emotion captioning with large language model,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:38.964974Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:b8729efe08b34f3f8862f0455ccddcfa8c3f3792f9dd79e832c1a6d6745769ba","observation_id":"50680b97-8baf-4b2d-a749-9cf712a1c33b","resolution":{"observed_at":"2026-08-01T09:59:38.964974Z","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":"2026-08-01T09:59:39.052102Z","title":"MMSU: A massive multi-task spoken language understanding and reason- ing benchmark,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.052102Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:6986d5605b9b465415f337f98f7bad145a936031872ebb68f9446e4d7e63695a","observation_id":"97cf3800-31bf-44e1-9a05-1fa0d8b901e3","resolution":{"observed_at":"2026-08-01T09:59:39.052102Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01710","last_updated":"2025-03-03T16:23:10Z","snapshot_observed_at":"2026-07-06T20:45:50.730195Z","submitted_at":"2025-03-03T16:23:10Z","title":"Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.01710","snapshot_observed_at":"2026-08-01T09:59:39.136823Z","title":"Spark-tts: An efficient llm-based text-to-speech model with single-stream decoupled speech tokens,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.136823Z"},"links":{"cited_paper":"/paper/2503.01710","citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:913de9fde9fa13fc1172ddb14a5e674c9d1caefbaa2c64f9ba70da4d9aed268b","observation_id":"3c693153-dad8-4601-af31-ad398c47d5ec","resolution":{"observed_at":"2026-08-01T09:59:39.136823Z","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":"2026-08-01T09:59:39.206954Z","title":"speechocean762: An open-source non-native english speech corpus for pronuncia- tion assessment,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.206954Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:bb6ad7d2cd75e88a7e47fb2e6643ffbd0b12c843ff1122be37ed089620746f58","observation_id":"f63db418-9cfa-4023-ada0-145a761ef7d2","resolution":{"observed_at":"2026-08-01T09:59:39.206954Z","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":"2026-08-01T09:59:39.270332Z","title":"Childman- darin: A comprehensive mandarin speech dataset for young children aged 3-5,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.270332Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:e3d22cce35b126ba449ccd7dd91564b813e428c5b53153eadc1850479bddb45d","observation_id":"415f8c7a-8eaa-4b13-a064-94b4dd13eb7a","resolution":{"observed_at":"2026-08-01T09:59:39.270332Z","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":"2026-08-01T09:59:39.354679Z","title":"Seniortalk: A chinese conversation dataset with rich annotations for super- aged seniors,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.354679Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:ab114eb3d0c13561042829cf4ba0bb7a130fde6a107c187a03f5ab64849c6386","observation_id":"87861c04-79c7-4f37-8865-a0c9a206f123","resolution":{"observed_at":"2026-08-01T09:59:39.354679Z","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":"2026-08-01T09:59:39.411641Z","title":"Gi- gaspeech: An evolving, multi-domain asr corpus with 10,000 hours of transcribed audio,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.411641Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:201d75c99ac84279a29072a42dc78fa62269cf8ed7bd189c19f08d32a90c37d6","observation_id":"520b7c69-5b58-4530-9bc9-a26e1c276a85","resolution":{"observed_at":"2026-08-01T09:59:39.411641Z","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":"2026-08-01T09:59:39.494330Z","title":"Recent ad- vances in speech language models: A survey,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.494330Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:53cfd5d4496daaa518b6c01a703f2262ac830f8f5e629bfbf7db95d556491ae8","observation_id":"7436b06f-52c5-4b9e-8c40-47e9d1c11b32","resolution":{"observed_at":"2026-08-01T09:59:39.494330Z","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":"2026-08-01T09:59:39.574241Z","title":"Audio set: An on- tology and human-labeled dataset for audio events,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.574241Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:948cf2927659e77e221fbe248efcf04e5e45aad78e80ca485ef19201df2af293","observation_id":"360e4d38-1518-40b6-8b6a-fa193003d94a","resolution":{"observed_at":"2026-08-01T09:59:39.574241Z","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":"2026-08-01T09:59:39.640780Z","title":"Esc: Dataset for environmental sound classi- fication,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.640780Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:1ebc89f4299615a2af684ec69f67a9276eef37334677a0f1998963efd4e26b86","observation_id":"d605888a-3331-46f1-aeb1-23d53d3ffba0","resolution":{"observed_at":"2026-08-01T09:59:39.640780Z","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":"2026-08-01T09:59:39.735325Z","title":"Fsd50k: an open dataset of human-labeled sound events,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.735325Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:7c330d5f1afba135c8c62db478118ae4fc6e582cba9263f0ec23e7fbf5ff064e","observation_id":"176197ea-f851-4f4e-87f1-1cb4f261c4e7","resolution":{"observed_at":"2026-08-01T09:59:39.735325Z","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":"2026-08-01T09:59:39.779993Z","title":"Kespeech: An open source speech dataset of mandarin and its eight sub- dialects,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.779993Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:879d758f1af495a804f40d00dd0fd93efaf4e62743a4a220cb35ccb180743477","observation_id":"5547dc01-76ca-49ba-a192-4d64127443e2","resolution":{"observed_at":"2026-08-01T09:59:39.779993Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.17765","last_updated":"2025-09-22T13:26:24Z","snapshot_observed_at":"2026-08-11T00:14:34.061687Z","submitted_at":"2025-09-22T13:26:24Z","title":"Qwen3-Omni Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.17765","snapshot_observed_at":"2026-08-01T09:59:39.833234Z","title":"Qwen3-omni technical report,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.833234Z"},"links":{"cited_paper":"/paper/2509.17765","citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:811913aa530116ae88eb5be9a7c9cbf8615329da82170f5856477ae932e1f8c6","observation_id":"2ec54b8f-1607-4a82-8cbe-ac8cc6ab211c","resolution":{"observed_at":"2026-08-01T09:59:39.833234Z","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":"2026-08-01T09:59:39.904828Z","title":"Coig-cqia: Qual- ity is all you need for chinese instruction fine-tuning,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.904828Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:07f869acc9e98d173bc4fb50584bf84020154b913d60d49052c7f81317b5f64f","observation_id":"c05541b1-a981-4e64-b355-7a994614cc3a","resolution":{"observed_at":"2026-08-01T09:59:39.904828Z","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":"2026-08-01T09:59:39.954691Z","title":"Mustard: Mastering uniform synthesis of theorem and proof data,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:39.954691Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:f78df9b481e2f861ef81b2e09e4c1b76562d06d44ca12b732fa4326f07f60c6d","observation_id":"fcbc62df-6379-4001-b08f-c0c8a0356ae0","resolution":{"observed_at":"2026-08-01T09:59:39.954691Z","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":"2026-08-01T09:59:40.019480Z","title":"Indextts2: A break- through in emotionally expressive and duration-controlled auto-regressive zero-shot text-to-speech,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:40.019480Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:b15297c1205deee39f1679fe4b92c02ccbf9d17341c06dab5f8630385a1bf1b3","observation_id":"2a062c1b-e461-4751-9cf6-359854244a11","resolution":{"observed_at":"2026-08-01T09:59:40.019480Z","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":"2026-08-01T09:59:40.094302Z","title":"The problem ofm rankings,","venue":null,"work_id":null,"year":1939},"citing_paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-01T09:59:40.094302Z"},"links":{"citing_paper":"/paper/2607.27109"},"observation_digest":"sha256:ae54f0de4ccece5800dd33a0399180bc867b43e83b245ef8f59b746046ca24a9","observation_id":"9a34e2e1-d804-4004-a826-4dbfd3230fec","resolution":{"observed_at":"2026-08-01T09:59:40.094302Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.27109","last_updated":"2026-07-30T02:37:20Z","latest_version":2,"primary_category":"cs.SD","snapshot_observed_at":"2026-08-06T10:29:34.142993Z","submitted_at":"2026-07-29T16:38:08Z","title":"MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":33,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":33},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 2 inbound Pith citation observations for arXiv:2607.27109."}