{"as_of":"2026-08-16T06:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f0e611811b17baee21bdb48a1749de957727d4468f40e287f50bdfc2e7a9ee46","coverage":[{"denominator":16,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T19:54:42.529392Z","state":"measured"},{"denominator":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"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":[],"links":{"evidence":"/evidence","html":"/paper/2411.10183/citation-record","integrity":"/paper/2411.10183/integrity","json":"/paper/2411.10183/citation-record.json","paper":"/paper/2411.10183"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T19:54:42.465801Z","title":"Training language models to follow instructions with human feedback,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.465801Z"},"links":{"citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:d0c24adce63fe5586cb4d386f2ea4df4a431eb78a6bb100963cabe5e52de8c48","observation_id":"59e36181-0e9f-4932-9507-d1e8149697b1","resolution":{"observed_at":"2026-08-12T19:54:42.465801Z","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":"2026-08-12T19:54:42.678510Z","title":"Manigan: Text-guided image manipulation,","venue":null,"work_id":"6e8c62fc-568e-4d6b-8787-351f8193b84c","year":2020},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.470176Z"},"links":{"citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:4e008b19d57c440c2e3bb23550e6c4c62eef4f23decbb2f222c2e1915dc0cf27","observation_id":"a0d5c683-8111-43e9-93a9-130cd7213da4","resolution":{"observed_at":"2026-08-12T19:54:42.682442Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-12T19:54:42.474766Z","title":"Unpaired image-to-image translation using cycle-consistent adversarial networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.474766Z"},"links":{"citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:b8862b120b5e31ac15932afcf2143b06a6ac956a48bc481d9ff075fc87869162","observation_id":"27e1e406-4bc2-4ce7-b72c-32ea8e07ed2a","resolution":{"observed_at":"2026-08-12T19:54:42.474766Z","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":"2026-08-12T19:54:42.478533Z","title":"High- resolution image synthesis with latent diffusion models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.478533Z"},"links":{"citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:7bf946c564c0000ae1f75711c6fea32f73042e61e5bbc84a6b59b7043d3e4681","observation_id":"9e669340-ef06-44cc-b87f-bd161c177e01","resolution":{"observed_at":"2026-08-12T19:54:42.478533Z","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":"2026-08-12T19:54:42.483989Z","title":"Photorealistic text-to-image diffusion models with deep language understanding,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.483989Z"},"links":{"citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:5c54fcdaa2a64062760801e78b088faa28390e10932bea8d6fdd3a17bd423425","observation_id":"9b6c6e34-fcb1-450b-af34-91336205b16c","resolution":{"observed_at":"2026-08-12T19:54:42.483989Z","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":"2026-08-12T19:54:42.488583Z","title":"Microsoft coco: Common objects in context,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.488583Z"},"links":{"citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:dd190159de42e9d92aceb7dfcd229a16b7c5d82578eb9d4bbe510d471bfb2b6d","observation_id":"76eb0e26-c0e6-4b4a-831a-58bf917d342a","resolution":{"observed_at":"2026-08-12T19:54:42.488583Z","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":"2026-08-12T19:54:42.493087Z","title":"The caltech-ucsd birds-200-2011 dataset,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.493087Z"},"links":{"citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:fa5de9b4bd4dd07646bed974ab70a0336bb100a6665ddd478d627044899db1d7","observation_id":"9945f1e4-f41c-42b2-ba2c-a52286b0d781","resolution":{"observed_at":"2026-08-12T19:54:42.493087Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.14896","last_updated":"2023-07-06T11:53:19Z","snapshot_observed_at":"2026-08-13T13:55:48.903163Z","submitted_at":"2022-10-26T17:54:20Z","title":"DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.14896","snapshot_observed_at":"2026-08-12T19:54:42.497045Z","title":"Diffusiondb: A large-scale prompt gallery dataset for text-to- image generative models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.497045Z"},"links":{"cited_paper":"/paper/2210.14896","citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:7f55be52cca529986f2bf4fab526736cc65b40829348d583275261a54c393cc9","observation_id":"dfb46f02-7a86-42d8-b605-bfc4e4db71e3","resolution":{"observed_at":"2026-08-12T19:54:42.497045Z","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":"2026-08-12T19:54:42.501323Z","title":"Gans trained by a two time-scale update rule converge to a local nash equilibrium,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.501323Z"},"links":{"citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:ba8f855002a905765c595dc180c05fd9b83afc96921d3b0820e1c3120ecd425e","observation_id":"ca985a11-068e-45e9-a019-3c82f2c0b846","resolution":{"observed_at":"2026-08-12T19:54:42.501323Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08718","last_updated":"2022-03-23T19:47:21Z","snapshot_observed_at":"2026-07-06T11:01:02.207193Z","submitted_at":"2021-04-18T05:00:29Z","title":"CLIPScore: A Reference-free Evaluation Metric for Image Captioning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08718","snapshot_observed_at":"2026-08-12T19:54:42.505048Z","title":"Clipscore: A reference-free evaluation metric for image captioning,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.505048Z"},"links":{"cited_paper":"/paper/2104.08718","citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:fbb25ee97e0bd66fd38043a2e6e8c4c5bd4b299471484f8cd3e7b4feb7acd96b","observation_id":"52aa3298-4076-4ac3-8e9f-b977db37caee","resolution":{"observed_at":"2026-08-12T19:54:42.505048Z","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":"2026-08-12T19:54:42.509243Z","title":"Learning transferable visual models from natural language supervision,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.509243Z"},"links":{"citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:e9e8514a477b9f5911c1d204b5491104cc689c89db255fdd8b8af6e8723c78de","observation_id":"326edf4f-de19-4c23-8210-299b58136bd6","resolution":{"observed_at":"2026-08-12T19:54:42.509243Z","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":"2026-08-12T19:54:42.619654Z","title":"Maniqa: Multi-dimension attention network for no-reference image quality assessment,","venue":null,"work_id":"bbe7a5bb-cd52-43e8-a7bb-f4444539fd48","year":2022},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.512992Z"},"links":{"citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:aef587f55802b477cb38018ffd720e56efdfb1e78c7433ddf8883f95eeef8233","observation_id":"bb05ecb7-969c-4455-b32c-5e5e1f6be4ef","resolution":{"observed_at":"2026-08-12T19:54:42.625826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.05977","last_updated":"2023-12-28T14:13:35Z","snapshot_observed_at":"2026-08-13T12:04:07.414191Z","submitted_at":"2023-04-12T16:58:13Z","title":"ImageReward: Learning and Evaluating Human Preferences for Text-to-Image Generation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.05977","snapshot_observed_at":"2026-08-12T19:54:42.516786Z","title":"Imagereward: Learning and evaluating human preferences for text-to- image generation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.516786Z"},"links":{"cited_paper":"/paper/2304.05977","citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:341ab43199c3a5d1f9837f0f96056791c331cb5abd2153414328ff1aa07c78e9","observation_id":"6a16cdf1-f185-4c77-9d59-042e2ea74df1","resolution":{"observed_at":"2026-08-12T19:54:42.516786Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2208.10442","last_updated":"2022-08-31T02:26:45Z","snapshot_observed_at":"2026-08-13T14:40:51.995893Z","submitted_at":"2022-08-22T16:55:04Z","title":"Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.10442","snapshot_observed_at":"2026-08-12T19:54:42.521365Z","title":"Image as a foreign language: Beit pretraining for all vision and vision-language tasks,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.521365Z"},"links":{"cited_paper":"/paper/2208.10442","citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:0fafa9f1be4c965cd2214b6983bdacd8dda6062e4b739274870090b70a6f9023","observation_id":"7e13e8d9-2fa7-4c44-8b52-07db5136489c","resolution":{"observed_at":"2026-08-12T19:54:42.521365Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-13T14:19:26.598265Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-12T19:54:42.525433Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale,","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.525433Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:5d0689589ff110de69b0f11b60ae00abfeb0f886d3df1ef837cc4495605b650e","observation_id":"096d89bc-7cd3-4476-811a-827ad5502dab","resolution":{"observed_at":"2026-08-12T19:54:42.525433Z","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":"2026-08-12T19:54:42.529392Z","title":"Attention is all you need,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T19:54:42.529392Z"},"links":{"citing_paper":"/paper/2411.10183"},"observation_digest":"sha256:b473273e0465aac2722f222ad18c8626e99fa2ff91dff402c0e9631fe8dd37ab","observation_id":"7c3d6c14-fe95-45b3-87cb-44f768a1a5f6","resolution":{"observed_at":"2026-08-12T19:54:42.529392Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.10183","last_updated":"2024-11-15T13:32:23Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-15T02:18:24.493062Z","submitted_at":"2024-11-15T13:32:23Z","title":"Visual question answering based evaluation metrics for text-to-image generation"},"reference_resolution":{"displayed":16,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":0,"verified_fuzzy":2},"total_outbound_references":16},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2411.10183."}