{"as_of":"2026-08-08T11:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:924bf0b902b927c9c5155986b6972f9b542ce3e4d7ed04ef8396a86c5326288b","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":12,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":12,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":12,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T23:01:49.928203Z","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":"2026-07-03T20:28:55.819781Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.05178","snapshot_observed_at":"2026-08-06T23:01:49.928203Z","title":"Qlip: Text-aligned visual tokenization unifies auto-regressive multimodal understanding and generation.arXiv preprint arXiv:2502.05178, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.20214","last_updated":"2025-07-08T07:46:39Z","snapshot_observed_at":"2026-08-07T21:47:36.945083Z","submitted_at":"2025-06-25T07:57:09Z","title":"UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation","version":2},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-06T23:01:49.928203Z"},"links":{"cited_paper":"/paper/2502.05178","citing_paper":"/paper/2506.20214"},"observation_digest":"sha256:16a9d951d8d0897fcafbf72619beebf1ca6e72387b6b973cedbc46a7c2cc4862","observation_id":"cf687e1a-b5f5-4563-a753-5427cbecb4a8","resolution":{"observed_at":"2026-08-06T23:01:49.928203Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.05178","snapshot_observed_at":"2026-08-06T21:52:26.204540Z","title":"QLIP: text-aligned visual tokenization unifies auto-regressive multimodal understanding and generation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.23115","last_updated":"2025-06-29T06:41:00Z","snapshot_observed_at":"2026-08-07T01:05:19.522559Z","submitted_at":"2025-06-29T06:41:00Z","title":"MoCa: Modality-aware Continual Pre-training Makes Better Bidirectional Multimodal Embeddings","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T21:52:26.204540Z"},"links":{"cited_paper":"/paper/2502.05178","citing_paper":"/paper/2506.23115"},"observation_digest":"sha256:66c56e1df5378a6a649a218137178eeac7d41c7746063c290935499f638800c9","observation_id":"e389c8ad-e413-4311-96c6-dedb6e571120","resolution":{"observed_at":"2026-08-06T21:52:26.204540Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation","version":1},"cited_work":{"arxiv_id":"2502.05178","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.05178","snapshot_observed_at":"2026-07-03T20:28:55.819781Z","title":"arXiv preprint arXiv:2502.05178 (2025) 2, 4, 7, 8 WinTok 15","venue":null,"work_id":"dc94ee65-ac1f-4c4d-a6f8-8c9f3bc865e7","year":2025},"citing_paper":{"arxiv_id":"2605.12500","last_updated":"2026-05-12T17:59:58Z","snapshot_observed_at":"2026-07-06T23:24:13.851504Z","submitted_at":"2026-05-12T17:59:58Z","title":"SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture","version":1},"reference_index":167,"source":"pdf_text","source_observed_at":"2026-05-13T05:12:37.339084Z"},"links":{"cited_paper":"/paper/2502.05178","citing_paper":"/paper/2605.12500"},"observation_digest":"sha256:9e37d8201857f3ce46c0fc38b206fd70afe5bb9036b3e6993a04132978a8c78b","observation_id":"78ce552d-ceb8-4c56-a03b-f1a590da903a","resolution":{"observed_at":"2026-05-13T05:17:18.666961Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation","version":1},"cited_work":{"arxiv_id":"2502.05178","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.05178","snapshot_observed_at":"2026-07-03T20:28:55.819781Z","title":"arXiv preprint arXiv:2502.05178 (2025) 2, 4, 7, 8 WinTok 15","venue":null,"work_id":"dc94ee65-ac1f-4c4d-a6f8-8c9f3bc865e7","year":2025},"citing_paper":{"arxiv_id":"2605.14028","last_updated":"2026-06-04T03:11:29Z","snapshot_observed_at":"2026-07-06T23:25:29.856145Z","submitted_at":"2026-05-13T18:38:51Z","title":"Unified Pix Token And Word Token Generative Language Model","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-30T21:30:45.355012Z"},"links":{"cited_paper":"/paper/2502.05178","citing_paper":"/paper/2605.14028"},"observation_digest":"sha256:c8fdc8af6118f2dfdd4039872ff787abde9b53f2d187b0511a5c0a5baa8ab39a","observation_id":"f6deb1b8-5c81-4bfc-b684-300bf9f9134d","resolution":{"observed_at":"2026-06-30T21:35:04.591361Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation","version":1},"cited_work":{"arxiv_id":"2502.05178","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.05178","snapshot_observed_at":"2026-07-03T20:28:55.819781Z","title":"arXiv preprint arXiv:2502.05178 (2025) 2, 4, 7, 8 WinTok 15","venue":null,"work_id":"dc94ee65-ac1f-4c4d-a6f8-8c9f3bc865e7","year":2025},"citing_paper":{"arxiv_id":"2605.18115","last_updated":"2026-05-18T09:24:39Z","snapshot_observed_at":"2026-08-06T04:43:08.432770Z","submitted_at":"2026-05-18T09:24:39Z","title":"WinTok: A Win-Win Hybrid Tokenizer via Decomposing Visual Understanding and Generation with Transferable Tokens","version":1},"reference_index":107,"source":"pdf_text","source_observed_at":"2026-05-20T12:04:19.761430Z"},"links":{"cited_paper":"/paper/2502.05178","citing_paper":"/paper/2605.18115"},"observation_digest":"sha256:9f7d329abc1088f6fefb6e7017fb896f3bf5857e525bce95e31d7c2c5a6dc47b","observation_id":"231eadc4-01d1-4ae1-ba6e-263234ac0b94","resolution":{"observed_at":"2026-05-20T12:08:15.768573Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation","version":1},"cited_work":{"arxiv_id":"2502.05178","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.05178","snapshot_observed_at":"2026-07-03T20:28:55.819781Z","title":"arXiv preprint arXiv:2502.05178 (2025) 2, 4, 7, 8 WinTok 15","venue":null,"work_id":"dc94ee65-ac1f-4c4d-a6f8-8c9f3bc865e7","year":2025},"citing_paper":{"arxiv_id":"2606.03578","last_updated":"2026-06-02T12:47:14Z","snapshot_observed_at":"2026-07-06T23:43:50.943530Z","submitted_at":"2026-06-02T12:47:14Z","title":"Diffusing in the Right Space: A Systematic Study of Latent Diffusability","version":1},"reference_index":113,"source":"arxiv_source","source_observed_at":"2026-06-28T10:44:24.318786Z"},"links":{"cited_paper":"/paper/2502.05178","citing_paper":"/paper/2606.03578"},"observation_digest":"sha256:0831f9f1ab8c6df2e5968ec1d4ec9a3c28c493ad239fec5fda07b6934888c66a","observation_id":"0d553d7d-d8bb-4acb-bb92-f667a5f324c6","resolution":{"observed_at":"2026-07-02T02:36:27.631392Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation","version":1},"cited_work":{"arxiv_id":"2502.05178","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.05178","snapshot_observed_at":"2026-07-03T20:28:55.819781Z","title":"arXiv preprint arXiv:2502.05178 (2025) 2, 4, 7, 8 WinTok 15","venue":null,"work_id":"dc94ee65-ac1f-4c4d-a6f8-8c9f3bc865e7","year":2025},"citing_paper":{"arxiv_id":"2606.11363","last_updated":"2026-06-09T18:43:29Z","snapshot_observed_at":"2026-08-06T10:47:54.873857Z","submitted_at":"2026-06-09T18:43:29Z","title":"NSVQ: Mitigating Codebook Collapse by Stabilizing Encoder Drift in Vector Quantization","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-27T13:18:47.472178Z"},"links":{"cited_paper":"/paper/2502.05178","citing_paper":"/paper/2606.11363"},"observation_digest":"sha256:4427a19ad5173857ff73f5b941d2f4733a1d6d79c126226ccf6334bf722fdd60","observation_id":"b7cfaf30-7abf-4a31-8663-d096ee5faa72","resolution":{"observed_at":"2026-07-03T05:27:39.702114Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation","version":1},"cited_work":{"arxiv_id":"2502.05178","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.05178","snapshot_observed_at":"2026-07-03T20:28:55.819781Z","title":"arXiv preprint arXiv:2502.05178 (2025) 2, 4, 7, 8 WinTok 15","venue":null,"work_id":"dc94ee65-ac1f-4c4d-a6f8-8c9f3bc865e7","year":2025},"citing_paper":{"arxiv_id":"2606.13289","last_updated":"2026-06-11T12:46:07Z","snapshot_observed_at":"2026-08-02T10:42:01.559662Z","submitted_at":"2026-06-11T12:46:07Z","title":"HYDRA-X: Native Unified Multimodal Models with Holistic Visual Tokenizers","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-06-27T07:01:07.362430Z"},"links":{"cited_paper":"/paper/2502.05178","citing_paper":"/paper/2606.13289"},"observation_digest":"sha256:f31cf0dbe3532710d09fcf7635f5bb6fc448276a88450cf1596d22b9a5b424b6","observation_id":"6d93c88c-7d14-4a5d-ae65-d42304fbf072","resolution":{"observed_at":"2026-07-03T14:38:28.819010Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation","version":1},"cited_work":{"arxiv_id":"2502.05178","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.05178","snapshot_observed_at":"2026-07-03T20:28:55.819781Z","title":"arXiv preprint arXiv:2502.05178 (2025) 2, 4, 7, 8 WinTok 15","venue":null,"work_id":"dc94ee65-ac1f-4c4d-a6f8-8c9f3bc865e7","year":2025},"citing_paper":{"arxiv_id":"2606.18249","last_updated":"2026-06-17T18:39:52Z","snapshot_observed_at":"2026-07-06T23:53:45.117607Z","submitted_at":"2026-06-16T17:59:22Z","title":"Unified Multimodal Autoregressive Modeling with Shared Context-Visual Tokenizer is Key to Unification","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-06-27T01:18:03.846908Z"},"links":{"cited_paper":"/paper/2502.05178","citing_paper":"/paper/2606.18249"},"observation_digest":"sha256:5c6c3c8974557e448ca41a74d4b52a16692a81efb48761fb640445f10c0b99f3","observation_id":"3d54901a-9046-4a6d-9181-a448ae5835b3","resolution":{"observed_at":"2026-07-03T20:28:55.821216Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.05178","snapshot_observed_at":"2026-08-01T05:45:53.491983Z","title":"Qlip: Text-aligned visual tokenization unifies auto-regressive multimodal understanding and generation.arXiv preprint arXiv:2502.05178, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.22148","last_updated":"2026-07-24T09:47:32Z","snapshot_observed_at":"2026-08-07T04:11:15.831910Z","submitted_at":"2026-07-24T09:47:32Z","title":"dRAE: Representation Autoencoder with Hyper-Spherical Codes","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-01T05:45:53.491983Z"},"links":{"cited_paper":"/paper/2502.05178","citing_paper":"/paper/2607.22148"},"observation_digest":"sha256:a8e6f6c16daef82ea6340dd0e25c51a3cebc39d9060d4c7ee893d6281b7b6a45","observation_id":"aff2e8d0-fbac-4880-9063-09d70c87d728","resolution":{"observed_at":"2026-08-01T05:45:53.491983Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.05178","snapshot_observed_at":"2026-08-01T04:29:50.752053Z","title":"arXiv preprint arXiv:2502.05178 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22531","last_updated":"2026-07-24T17:59:39Z","snapshot_observed_at":"2026-08-07T13:04:18.211748Z","submitted_at":"2026-07-24T17:59:39Z","title":"Twins: Learn to Predict Unified Representations with Focal Loss","version":1},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-01T04:29:50.752053Z"},"links":{"cited_paper":"/paper/2502.05178","citing_paper":"/paper/2607.22531"},"observation_digest":"sha256:c91460c675209d21d05cdcfb177861af8235abcaca95da97f7fc4f01b2167e4e","observation_id":"63171561-62da-4f9d-9d63-c7eec9039483","resolution":{"observed_at":"2026-08-01T04:29:50.752053Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.05178","snapshot_observed_at":"2026-08-06T11:55:28.219048Z","title":"Qlip: Text-aligned visual tokenization unifies auto-regressive multimodal understanding and generation.arXiv preprint arXiv:2502.05178, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.05000","last_updated":"2026-08-06T17:18:02Z","snapshot_observed_at":"2026-08-08T10:16:39.182387Z","submitted_at":"2026-08-05T16:09:25Z","title":"Towards Physics of Multimodal Pretraining: Knowledge Flow, Modality Synergy, Early Unification, and Recipes","version":1},"reference_index":157,"source":"pdf_text","source_observed_at":"2026-08-06T11:55:28.219048Z"},"links":{"cited_paper":"/paper/2502.05178","citing_paper":"/paper/2608.05000"},"observation_digest":"sha256:7088e8f998aca35f9669894b2d7b43ad28e83af6fb602372068cf8fd0f57a2c9","observation_id":"dc275fa0-7300-4446-9dc3-cc9c0a1d4d35","resolution":{"observed_at":"2026-08-06T11:55:28.219048Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2502.05178/citation-record","integrity":"/paper/2502.05178/integrity","json":"/paper/2502.05178/citation-record.json","paper":"/paper/2502.05178"},"outbound":[],"paper":{"arxiv_id":"2502.05178","last_updated":"2025-02-07T18:59:57Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-07-06T20:33:01.960703Z","submitted_at":"2025-02-07T18:59:57Z","title":"QLIP: Text-Aligned Visual Tokenization Unifies Auto-Regressive Multimodal Understanding and Generation"},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2502.05178."}