{"as_of":"2026-08-08T15:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a26df7c82fb846663616f2d18693a2df3591c85162ee5a951f71f4e4972109e3","coverage":[{"denominator":23,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T05:15:08.455583Z","state":"measured"},{"denominator":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2607.16316/citation-record","integrity":"/paper/2607.16316/integrity","json":"/paper/2607.16316/citation-record.json","paper":"/paper/2607.16316"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2511.21631","last_updated":"2025-11-27T12:16:54Z","snapshot_observed_at":"2026-07-06T22:37:03.716474Z","submitted_at":"2025-11-26T17:59:08Z","title":"Qwen3-VL Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.21631","snapshot_observed_at":"2026-08-02T05:15:06.080203Z","title":"Qwen3-VL technical report.arXiv preprint arXiv:2511.21631, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:06.080203Z"},"links":{"cited_paper":"/paper/2511.21631","citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:d77674e357ab432c1c99175f04e2239810a25a36a7aa12979af5158923b86b5c","observation_id":"154e6561-452b-4a39-b107-90ea207ebce3","resolution":{"observed_at":"2026-08-02T05:15:06.080203Z","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":"2026-08-02T05:15:06.142977Z","title":"Eddy-VL Embedding 1.9B","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:06.142977Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:77e9ebd416bf87f0ea2cb15b244f66a9e5ee6236c1dd46001c7ff86553925df3","observation_id":"67a9010d-4dd9-4805-993a-f877f53c109c","resolution":{"observed_at":"2026-08-02T05:15:06.142977Z","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":"2026-08-02T05:15:06.244158Z","title":"FlashAttention: Fast and memory-efficient exact attention with IO-awareness","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:06.244158Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:c24ae1ced871017c7945e69272a5bb7c02e01ab2020679569c974f0d2b2d36f3","observation_id":"c7dd6949-ec8d-4e82-bbbb-66fb97fbc756","resolution":{"observed_at":"2026-08-02T05:15:06.244158Z","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":"2026-08-02T05:15:06.396884Z","title":"With limited data for multimodal alignment, let the STRUCTURE guide you","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:06.396884Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:c5006797d1aebb5b4fdc0c0ae6f0d20e1a8460311070f2ecae15fcf8d99737cb","observation_id":"b46c1a4b-afd0-496e-a931-65d20a4d58d4","resolution":{"observed_at":"2026-08-02T05:15:06.396884Z","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":"2026-08-02T05:15:06.518780Z","title":"Evaluation of deep convolu- tional nets for document image classification and retrieval","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:06.518780Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:fe926f426201b234c09a06fa19ef4c10a2c0d16a51554dfcd62cddc762ed55fd","observation_id":"f574acd2-b5aa-4509-91ad-698254da94a6","resolution":{"observed_at":"2026-08-02T05:15:06.518780Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-07-06T04:11:24.157003Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-02T05:15:06.625592Z","title":"Distilling the knowledge in a neural network","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:06.625592Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:f6aa5e909e6c35e463876bc06d97bf04594c24ba165cfc338baf0c8f512ea494","observation_id":"13e44443-c9c9-4f71-8bbb-2cfde7a35629","resolution":{"observed_at":"2026-08-02T05:15:06.625592Z","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":"2026-08-02T05:15:06.744074Z","title":"SugarCrepe: Fixing hackable benchmarks for vision-language compositionality","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:06.744074Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:330e2b2f06cba66b970ee6e3ace09b7330cb8a205f0415659a67b0cc6b4651ce","observation_id":"e3186d75-4cc9-4391-b154-e5fd8124c931","resolution":{"observed_at":"2026-08-02T05:15:06.744074Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.05160","last_updated":"2025-01-02T05:26:47Z","snapshot_observed_at":"2026-07-06T19:29:05.492290Z","submitted_at":"2024-10-07T16:14:05Z","title":"VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.05160","snapshot_observed_at":"2026-08-02T05:15:06.830765Z","title":"VLM2Vec: Training vision-language models for massive multimodal embedding tasks","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:06.830765Z"},"links":{"cited_paper":"/paper/2410.05160","citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:c0e358c8901e0c457223431ff34fc7136f3b937a94feedf8b8c9b316d084a424","observation_id":"563d6d1d-0ad0-45b8-b168-792c9ffef967","resolution":{"observed_at":"2026-08-02T05:15:06.830765Z","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":"2026-08-02T05:15:06.903783Z","title":"Korean Image Captioning Dataset (ai hub dataset no","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:06.903783Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:0f0c18b2faa39a0443bba46a472fb9792e0032cda58fff6ba86723832ea88b41","observation_id":"d28c07ae-dd08-4db2-9c2d-1b980ec138a8","resolution":{"observed_at":"2026-08-02T05:15:06.903783Z","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":"2026-08-02T05:15:06.971719Z","title":"Similarity of neural network representations revisited","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:06.971719Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:89a30fe600251f8a490cab59fdcb3f2041b76b543aaf93f8c655ba4242a6417c","observation_id":"b2d70048-07b6-48b9-914f-a0080d4384ba","resolution":{"observed_at":"2026-08-02T05:15:06.971719Z","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":"2026-08-02T05:15:07.075107Z","title":"Matryoshka representation learning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:07.075107Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:756c05e16baaa8ec0aba052fb0cd3cbe2b7fb955b81de4484cf5485761603798","observation_id":"c9506c1e-5d5d-4ece-84e2-6236eea7b3f1","resolution":{"observed_at":"2026-08-02T05:15:07.075107Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.04720","last_updated":"2026-01-19T09:03:26Z","snapshot_observed_at":"2026-07-06T22:41:05.793337Z","submitted_at":"2026-01-08T08:36:06Z","title":"Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.04720","snapshot_observed_at":"2026-08-02T05:15:07.209490Z","title":"Qwen3-VL- Embedding and Qwen3-VL-Reranker: A unified framework for state-of-the-art multimodal retrieval and ranking.arXiv preprint arXiv:2601.04720, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:07.209490Z"},"links":{"cited_paper":"/paper/2601.04720","citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:e3cfcbf29ee3221d98d75282192b0ec090ad17bc1471d9bdd716e51c94522c12","observation_id":"97b1c02b-9a0a-4e70-a318-a840abea2f27","resolution":{"observed_at":"2026-08-02T05:15:07.209490Z","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":"2026-08-02T05:15:07.337388Z","title":"Lawrence Zitnick","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:07.337388Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:b540608867096647859acdaa67f84f7542d6b2687af318593c7fe287f3670608","observation_id":"1359d9fe-fd01-46a4-823d-c3fbdbcb22f6","resolution":{"observed_at":"2026-08-02T05:15:07.337388Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.04590","last_updated":"2025-07-07T00:51:57Z","snapshot_observed_at":"2026-08-02T08:05:44.477432Z","submitted_at":"2025-07-07T00:51:57Z","title":"VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.04590","snapshot_observed_at":"2026-08-02T05:15:07.473420Z","title":"VLM2Vec- V2: Advancing multimodal embedding for videos, images, and visual documents.Transac- tions on Machine Learning Research, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:07.473420Z"},"links":{"cited_paper":"/paper/2507.04590","citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:584ee23f0bebc49bf87ea3e32ebf03657468ec73e2833fb9a22ffd7a87c2b74a","observation_id":"4696e332-5fff-4ef7-865f-d2c2a64da1f2","resolution":{"observed_at":"2026-08-02T05:15:07.473420Z","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":"2026-08-02T05:15:07.616036Z","title":"AI Hub (korean public ai training data portal)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:07.616036Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:b16e79453488305ac831362bdc8ca178095f24eadb64d21b8e0b2b2299d2791f","observation_id":"beb8be55-3efe-4a0b-8aa9-3b8ea445758b","resolution":{"observed_at":"2026-08-02T05:15:07.616036Z","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":"2026-08-02T05:15:07.806039Z","title":"CORD: A consolidated receipt dataset for post-OCR parsing","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:07.806039Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:199d33cceffff1e35e9784846e08ed329eed9fbdaea47975de9d8f5f0a16053e","observation_id":"aa3e834b-9554-4aac-a4d8-c4d66fe6e90d","resolution":{"observed_at":"2026-08-02T05:15:07.806039Z","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":"2026-08-02T05:15:07.943330Z","title":"Relational knowledge distillation","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:07.943330Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:fb40cc0b289f6c3eeaede74e1f83372765a506196ee0f5dddf66e48f600e5389","observation_id":"5fef0d74-1944-4c89-af3d-7a6c5afe9d85","resolution":{"observed_at":"2026-08-02T05:15:07.943330Z","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":"2026-08-02T05:15:08.073770Z","title":"Qwen3-VL-Embedding-2B.https://huggingface.co/Qwen/ Qwen3-VL-Embedding-2B, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:08.073770Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:4df6aaf098c6e3a0212e32be6f3c0e5ae05bdcbbdd171d2ac59612c95a02484e","observation_id":"4d1cb976-6544-40f9-9e55-0e55d54bc43e","resolution":{"observed_at":"2026-08-02T05:15:08.073770Z","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":"2026-08-02T05:15:08.145964Z","title":"Winoground: Probing vision and language models for visio-linguistic compositionality","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:08.145964Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:9b2cf1640fb94d24a024536cf11448511bf55c65095924d65cb614ee06f8b645","observation_id":"8ff266fe-52f5-456a-905b-6cec89546894","resolution":{"observed_at":"2026-08-02T05:15:08.145964Z","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":"2026-08-02T05:15:08.224995Z","title":"SUN database: Large-scale scene recognition from abbey to zoo","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:08.224995Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:b754eec1e20d5abbfd3f0108d3b7f77d9756a196a8337468e15d97e9894f5e9c","observation_id":"3bd65173-dc16-4d54-90d1-c01d724a06c5","resolution":{"observed_at":"2026-08-02T05:15:08.224995Z","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":"2026-08-02T05:15:08.273881Z","title":"When and why vision-language models behave like bags-of-words, and what to do about it? InICLR, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:08.273881Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:6791413797214c3831199f5211965cec0f653043ad06eacca770871cf00c9c58","observation_id":"32c90110-76c5-45d2-9976-3c1f6309dc94","resolution":{"observed_at":"2026-08-02T05:15:08.273881Z","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":"2026-08-02T05:15:08.385785Z","title":"MR2-bench: Going beyond matching to reasoning in multimodal retrieval.arXiv preprint arXiv:2509.26378, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:08.385785Z"},"links":{"citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:5168420ea8c4982264e6adad37a90437d11953d213d37d89d52f6e7a77d820d2","observation_id":"b70fe2da-0fe6-4071-a673-012155ebf6e8","resolution":{"observed_at":"2026-08-02T05:15:08.385785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.11824","last_updated":"2024-04-30T09:06:04Z","snapshot_observed_at":"2026-07-06T17:18:40.469815Z","submitted_at":"2024-01-22T10:37:59Z","title":"Rethinking Centered Kernel Alignment in Knowledge Distillation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.11824","snapshot_observed_at":"2026-08-02T05:15:08.455583Z","title":"Rethinking centered kernel alignment in knowledge distillation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-02T05:15:08.455583Z"},"links":{"cited_paper":"/paper/2401.11824","citing_paper":"/paper/2607.16316"},"observation_digest":"sha256:f59479a0e721698a659a91471fa8a80968abbece038cbd50186ca8ba852253d6","observation_id":"ac9d0cfb-aad1-47cc-8bad-e0598e30e3e0","resolution":{"observed_at":"2026-08-02T05:15:08.455583Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.16316","last_updated":"2026-07-15T04:36:19Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T10:50:09.828842Z","submitted_at":"2026-07-15T04:36:19Z","title":"Eddy-VL 1.9B: Structural Pruning and Layered Distillation for Edge-Deployable Multimodal Embedding"},"reference_resolution":{"displayed":23,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":23,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":23},"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 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2607.16316."}