{"as_of":"2026-08-12T05:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0906be3b431cf3260ec44e72f6d77c9acdd01f21cc94844c94983a13706bcf9e","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T16:57:40.220447Z","state":"measured"},{"denominator":29,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":29,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+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":"2026-08-10T16:57:40.132049Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-10T16:57:40.277512Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"cited_work":{"arxiv_id":"2501.13968","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.13968","snapshot_observed_at":"2026-08-10T16:57:40.277512Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","venue":"cs.CV","work_id":"bd4bcc87-6039-4ff6-a43c-69de4491f853","year":2025},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.132049Z"},"links":{"cited_paper":"/paper/2501.13968","citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:1b4b3e213494001ee7dec78b8ded3bd044974d8783ee2a4077220d82a21c51b4","observation_id":"4edf11c0-9397-4947-9e03-8c2a32eca81f","resolution":{"observed_at":"2026-08-10T16:57:40.283137Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.13968/citation-record","integrity":"/paper/2501.13968/integrity","json":"/paper/2501.13968/citation-record.json","paper":"/paper/2501.13968"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"cited_work":{"arxiv_id":"2501.13968","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.13968","snapshot_observed_at":"2026-08-10T16:57:40.277512Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","venue":"cs.CV","work_id":"bd4bcc87-6039-4ff6-a43c-69de4491f853","year":2025},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.132049Z"},"links":{"cited_paper":"/paper/2501.13968","citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:1b4b3e213494001ee7dec78b8ded3bd044974d8783ee2a4077220d82a21c51b4","observation_id":"4edf11c0-9397-4947-9e03-8c2a32eca81f","resolution":{"observed_at":"2026-08-10T16:57:40.283137Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.508169Z","title":"a photo of a white sports car driving down a road with mountains in the background","venue":null,"work_id":"a884d337-92d5-4f4a-8b49-186130d3dbbd","year":null},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.137070Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:07c81fc6994be08a586f1b06e1620fe2070d0b962b6905dc052957b7e45bd278","observation_id":"5b0e660d-3969-4043-a195-9994178447e4","resolution":{"observed_at":"2026-08-10T16:57:40.511729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.499351Z","title":"brown” with “white","venue":null,"work_id":"487b874c-6361-4ab9-a957-5e1caad7a84e","year":null},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.140531Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:09329ad9a54139f6c2160d6d9f95364a5c8c0cb2a0836374f215dd8f4ce23e1d","observation_id":"08e91e37-79da-4e44-a82f-01bf29932ff0","resolution":{"observed_at":"2026-08-10T16:57:40.502344Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.490293Z","title":"Our method enhances the ability to generate diverse and high-quality training examples, advancing the capabili- ties of the CIR model","venue":null,"work_id":"7eeeb8b8-c31f-4aa6-92ff-e5dacc90cc8c","year":null},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.144186Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:337b276fbeffbc19fd3fab697cf42ef606568bd2238bc4ae847a76f1ce86550c","observation_id":"94bfc19c-04cb-45b1-82e4-acc372c17601","resolution":{"observed_at":"2026-08-10T16:57:40.493633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.05644","last_updated":"2021-02-10T18:56:41Z","snapshot_observed_at":"2026-08-11T14:30:10.438247Z","submitted_at":"2021-02-10T18:56:41Z","title":"Training Vision Transformers for Image Retrieval","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.05644","snapshot_observed_at":"2026-08-10T16:57:40.147683Z","title":"Training vision transformers for image retrieval,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.147683Z"},"links":{"cited_paper":"/paper/2102.05644","citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:e8fc126d8fa16324b22a2b4d32d1d166739fdfa0f8906538486f8df300bfb9aa","observation_id":"07d81f0f-2041-4108-b269-6725a2a47e8a","resolution":{"observed_at":"2026-08-10T16:57:40.147683Z","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":"2026-08-10T16:57:40.482019Z","title":"Boosting vision transformers for image re- trieval,","venue":null,"work_id":"6a1ea5d5-b51a-4647-804d-245ba12a253f","year":2023},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.151833Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:e3f6b7fa11ea288f7d59de1a794e11647621ba2401ee5eb4d500e9f74f7a3abf","observation_id":"7aa29a4c-e84b-4720-944d-3d7af6b7a816","resolution":{"observed_at":"2026-08-10T16:57:40.484747Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.473338Z","title":"Pic2Word: Mapping pictures to words for zero-shot composed image re- trieval,","venue":null,"work_id":"8d10f4a4-d428-42b1-af0c-46d18a2c220c","year":2023},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.155557Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:19c0e3decf4cc0252227097711597ab1c31bb7f8b92a95f1fb1364302f2f39ee","observation_id":"17925d01-f870-4b97-bdd9-f687d91c0dbe","resolution":{"observed_at":"2026-08-10T16:57:40.476505Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.464143Z","title":"Zero-shot composed image retrieval with textual inversion,","venue":null,"work_id":"73f51e76-a053-4425-bbd6-fa3108b8264a","year":2023},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.158737Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:e67c126633d2cee57d5623fad604baad7e1125d57daa10d782d21b2b78ab6d08","observation_id":"2852dba5-3164-4acc-ac2c-1650d5ad23c5","resolution":{"observed_at":"2026-08-10T16:57:40.467756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.454011Z","title":"CompoDiff: Versatile composed image retrieval with latent diffusion,","venue":null,"work_id":"9f86ff39-87f1-4706-8cec-6bd922a39c31","year":2024},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.161949Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:eaa95a16bdcfcf033c0112a48a0bce64be2b2bda47e809df129799511f10a794","observation_id":"30423673-fe39-44ad-806e-30e8455204d5","resolution":{"observed_at":"2026-08-10T16:57:40.458053Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.444329Z","title":"Language-only training of zero-shot com- posed image retrieval,","venue":null,"work_id":"181b77cc-dc45-4113-be82-86050dd41bda","year":2024},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.165773Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:d041143a30cdf593265a3c39f0c6949827eefa77ff9b6fa0a36ac2799f04f59c","observation_id":"fc9ad6b3-5952-4c5d-a63d-347ea887ecc9","resolution":{"observed_at":"2026-08-10T16:57:40.447699Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.434600Z","title":"Composed image retrieval using contrastive learning and task-oriented clip-based features,","venue":null,"work_id":"0ce3f2a7-3f0c-4cf9-8988-a66e66c2f148","year":2023},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.168456Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:b851fcd0512a263bae3b5228663033e588b9f94ef571a0f6d6eb33d0f0f11c19","observation_id":"cfcc2ee0-6c58-40cd-83c7-ffafe47756fd","resolution":{"observed_at":"2026-08-10T16:57:40.438266Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.425654Z","title":"Zero-shot composed image re- trieval considering query-target relationship leveraging masked image-text pairs,","venue":null,"work_id":"ba5c4a02-7164-4cbc-ae77-f94ce14e9df8","year":2024},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.171105Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:387eaedc7e2f637c991309f9bbe77ae2cd31b23d888ad9168ffd184faa9c548c","observation_id":"501c022d-6793-461b-a593-6ba7587aa729","resolution":{"observed_at":"2026-08-10T16:57:40.428724Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.416840Z","title":"SPIRIT: Style-guided patch interaction for fashion image retrieval with text feedback,","venue":null,"work_id":"2bc96076-0979-415a-aef2-a65a6ff69c5d","year":2024},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.173998Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:4ead150d5b5b191dc791dc4767072c5ea8d2ac2dbbea6b5fd8e57742f0648454","observation_id":"28e37264-e373-411a-a8cc-c6039f6123dd","resolution":{"observed_at":"2026-08-10T16:57:40.419963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.408374Z","title":"Real20m: A large-scale e-commerce dataset for cross-domain retrieval,","venue":null,"work_id":"db7a83dd-2d91-4a2f-8756-b495e3bf2d10","year":2023},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.176804Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:1a70506b350aa15d1793d0bf83c648c2ad54972d116ff61e0733b5455f5123fd","observation_id":"c21c461f-2325-4c2e-9ee6-c77b01892c28","resolution":{"observed_at":"2026-08-10T16:57:40.411434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.400103Z","title":"Fashion retrieval via graph reasoning networks on a similarity pyramid,","venue":null,"work_id":"56f1ff22-1dc6-46af-83bb-09bf625783d8","year":2019},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.180143Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:17dfd075611581ec4b2491756e0e6f1adfa0465f0c48573d3b5d8f620169adf1","observation_id":"81414cbf-27a0-47f1-9a06-666b5719fd47","resolution":{"observed_at":"2026-08-10T16:57:40.403062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.391676Z","title":"Fashion IQ: A new dataset towards retrieving images by natural language feedback,","venue":null,"work_id":"ae293c46-8acb-4c78-b06d-ae6a3c7c4315","year":2021},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.182830Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:23a509d3962c36881499b98aa2cfe9fd41c0125611d154dd65c2e001fb740007","observation_id":"d46b7bcd-2a25-4a85-929b-f5f2bc7451ab","resolution":{"observed_at":"2026-08-10T16:57:40.394609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.381922Z","title":"Image retrieval on real-life images with pre-trained vision-and-language models,","venue":null,"work_id":"2730f7b7-239e-4a05-afc6-ca1844f3560e","year":2021},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.185651Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:e7242787fd1e5e087c55666bf42a9099af02b4570ee2d9ca8cbd7a1e4856e440","observation_id":"73eefc11-040d-4cf4-99ff-29ab3457780c","resolution":{"observed_at":"2026-08-10T16:57:40.385349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.371340Z","title":"CoVR: Learning composed video retrieval from web video captions,","venue":null,"work_id":"f5abc254-a258-4720-a0ec-bd2f669a18e5","year":2024},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.188424Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:3b7053ffa55ab3e115c38f731b3b34249579246c25cac1d40b79bd4fa5bb4acf","observation_id":"1eb72149-c167-42e2-ba6d-db6beafa0416","resolution":{"observed_at":"2026-08-10T16:57:40.374902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.361484Z","title":"LANCE: Stress-testing visual models by generating language-guided counterfactual images,","venue":null,"work_id":"cef4aac8-ab70-4da5-b156-8b79e9f0e93d","year":2023},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.191277Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:9f054a7a1b2a49cba1362cd1f6623ac169d51f1c3070ab667e3e171c050ca55e","observation_id":"7674adeb-479c-4bf5-85f8-a7e858541cec","resolution":{"observed_at":"2026-08-10T16:57:40.365101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.350647Z","title":"Reinforcing pre-trained models using coun- terfactual images,","venue":null,"work_id":"6cad8c1c-2a47-4d39-bf1a-dbc7418f8ace","year":2024},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.194008Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:76f9ee2a2ef8d6a63e703332165533668f0c786b9ae61cfb5308096b86186126","observation_id":"c34c55b5-1247-4f1d-85b0-4a9a87580161","resolution":{"observed_at":"2026-08-10T16:57:40.354646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.339540Z","title":"COCO- counterfactuals: Automatically constructed counterfactual ex- amples for image-text pairs,","venue":null,"work_id":"a8cce455-cc1e-4e60-b9bf-fe2bc7244bdd","year":2023},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.196780Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:7bf85e4e5325bb55d3ce4ad4b9769fd5215849964654746aac039681dd6e2e56","observation_id":"3ff2cae5-9e07-48c6-9602-d1d1b1dd7f1f","resolution":{"observed_at":"2026-08-10T16:57:40.343516Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.328140Z","title":"BLIP-2: Bootstrapping language-image pre-training with frozen image encoders and large language models,","venue":null,"work_id":"33f1780d-598b-4ca8-8442-84cdcae69a43","year":2023},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.200940Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:dad863dd90792cf45026d810c926304022c8485a5b3d170a4931c745e491114e","observation_id":"f7ec77bb-43db-4a51-9efd-41bfc6d8531a","resolution":{"observed_at":"2026-08-10T16:57:40.331826Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.318808Z","title":"High-resolution image synthe- sis with latent diffusion models,","venue":null,"work_id":"e031ba75-df02-4f28-a542-69916b90db3b","year":2022},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.204190Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:dbb495470a6e7aaad70bfb812f9206bbb7d31c23afb04129b090e267b1d68ab6","observation_id":"98606195-7b55-4067-9c05-9bd12f1c97b0","resolution":{"observed_at":"2026-08-10T16:57:40.322057Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.309283Z","title":"Prompt-to-prompt image edit- ing with cross-attention control,","venue":null,"work_id":"20632825-9b09-488c-b69f-ab1590bf663b","year":2023},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.207587Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:fe5fd84b48f1a8f8932e4b8a6ba2710cc51fb9fecb9868e9eeee4996d6200fa4","observation_id":"fd00cff7-b180-425d-9b74-44633b12cecf","resolution":{"observed_at":"2026-08-10T16:57:40.312673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.299582Z","title":"Null-text inversion for editing real im- ages using guided diffusion models,","venue":null,"work_id":"e27b515f-93a8-41c7-9134-39f0fa441865","year":2023},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.210619Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:3b4b964095c61b82be7a02b6a0afe779978fc3639285a6ed8bf6f3062b2e7d64","observation_id":"fa4cbd17-630b-4716-a7c3-4fd2048771f2","resolution":{"observed_at":"2026-08-10T16:57:40.302708Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:57:40.290165Z","title":"A corpus for reasoning about natural language grounded in photographs,","venue":null,"work_id":"e330af9f-f841-46cd-acbe-dd4a93aaaac4","year":2019},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.213762Z"},"links":{"citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:170297c30f221f20742a5105d9e5044394e781397c6947d1f774352513b69428","observation_id":"8b8599da-0aa4-4e8a-a8e9-cd67ff32306c","resolution":{"observed_at":"2026-08-10T16:57:40.293193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-10T16:57:40.216955Z","title":"LLaMA: Open and efficient foundation language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.216955Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:1c71fa3d7a8264bed0595f75e16d32640d9b3657692bdfa1e3bda00ea817e74c","observation_id":"7fcadd6d-4fe2-45b6-929a-2aeb83c6e542","resolution":{"observed_at":"2026-08-10T16:57:40.216955Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-11T08:20:29.798517Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-10T16:57:40.220447Z","title":"LoRA: Low-rank adaptation of large language models,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T16:57:40.220447Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2501.13968"},"observation_digest":"sha256:e5f0d92baeebf4b6c49a29e9b577b88ee87073d60197ee3bbc31a1498eb82833","observation_id":"e4745d61-ed07-4b6e-98be-c91f4e6f6fab","resolution":{"observed_at":"2026-08-10T16:57:40.220447Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.13968","last_updated":"2025-01-22T07:18:46Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-10T16:51:55.973700Z","submitted_at":"2025-01-22T07:18:46Z","title":"Triplet Synthesis For Enhancing Composed Image Retrieval via Counterfactual Image Generation"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":24},"total_outbound_references":28},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 1 inbound Pith citation observation for arXiv:2501.13968."}