{"as_of":"2026-08-17T22:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:77b98326a6d0a06d8c150d98f1c004cb054104cd3fa922fee985ac7d801e2936","coverage":[{"denominator":46,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":46,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T05:13:23.656049Z","state":"measured"},{"denominator":46,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":46,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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/2504.21292/citation-record","integrity":"/paper/2504.21292/integrity","json":"/paper/2504.21292/citation-record.json","paper":"/paper/2504.21292"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:13:25.902215Z","title":"Butterworth","venue":null,"work_id":"18dadfb4-f7b4-41a2-8787-e780b7a27889","year":1930},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.175746Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:c2c02b1ac04763e52d0ab16c808fad7571b199e46c607cf913a4ef37428e0914","observation_id":"43f91412-12f4-402c-b694-21aad15dec5f","resolution":{"observed_at":"2026-08-16T05:13:25.966795Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.02347","last_updated":"2024-12-18T10:45:06Z","snapshot_observed_at":"2026-08-16T13:46:16.128088Z","submitted_at":"2024-06-04T14:23:27Z","title":"Flash Diffusion: Accelerating Any Conditional Diffusion Model for Few Steps Image Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.02347","snapshot_observed_at":"2026-08-16T05:13:23.186771Z","title":"Flash diffusion: Accelerating any conditional diffusion model for few steps image generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.186771Z"},"links":{"cited_paper":"/paper/2406.02347","citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:52dc4b8d459b6992fbb7d26aa9a46508f92789f6e5b57852740d2da0c2521c00","observation_id":"e7d4d3cd-aa4a-4d6e-911a-ec62119f8453","resolution":{"observed_at":"2026-08-16T05:13:23.186771Z","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":"2026-08-16T05:13:25.888994Z","title":"Pixart-Σ: Weak-to-strong training of diffusion transformer for 4k text-to-image generation","venue":null,"work_id":"e36c3713-a48d-416e-97ad-668a09028bc8","year":2024},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.191134Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:2970c7f4d6b25260d35fc7b82e771c96afd23525942999e689e0d555c8dc6293","observation_id":"220a54da-d045-4b39-bcaa-13504f7f157c","resolution":{"observed_at":"2026-08-16T05:13:25.893786Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:25.875613Z","title":"Simple baselines for image restoration","venue":null,"work_id":"3f7b7c81-6a72-4148-abfe-9a8bd73cc010","year":2022},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.195286Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:e8d5fdbddd19cc0ba66fe67ad42eef38ef1b9e5d294ab254193406240728d8e7","observation_id":"169f7757-9882-407c-b96c-0bd968dab5b0","resolution":{"observed_at":"2026-08-16T05:13:25.881518Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.16821","last_updated":"2024-04-29T20:24:30Z","snapshot_observed_at":"2026-08-17T14:16:52.244007Z","submitted_at":"2024-04-25T17:59:19Z","title":"How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.16821","snapshot_observed_at":"2026-08-16T05:13:23.201201Z","title":"How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.201201Z"},"links":{"cited_paper":"/paper/2404.16821","citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:cdab0882bd64609d8db1ca8d104ac651633b3d2e96d5dc3923c7a281290ffb6e","observation_id":"440b074c-1963-43e2-8844-b4f6b1ab1a7f","resolution":{"observed_at":"2026-08-16T05:13:23.201201Z","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":"2026-08-16T05:13:25.775456Z","title":"Rifegan: Rich feature generation for text-to-image synthesis from prior knowledge","venue":null,"work_id":"2ea62ee1-49b4-4d8e-bb23-2b052500bc6c","year":2020},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.205603Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:abbca9904a5d4a87cf4c3249ea047037ccd05d28a5ce80aa616735011df8c906","observation_id":"8ecd76a3-1904-4344-9473-7ae4d76bd0b5","resolution":{"observed_at":"2026-08-16T05:13:25.826809Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:25.762282Z","title":"Kaplan, and Enrico Shippole","venue":null,"work_id":"2d406df6-e5e5-4d70-8501-a87c367082b8","year":2024},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.209601Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:ec68e71d701b5e3fffec867893372de2cdf8d08a5d0355abf364d70d5f3ed183","observation_id":"9e648e70-1a8d-44ae-82f3-57e171ad2ce1","resolution":{"observed_at":"2026-08-16T05:13:25.766066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:25.647508Z","title":"Transformers are ssms: Generalized models and efficient algorithms through structured state space duality","venue":null,"work_id":"ac6ef2a9-8ec1-43ee-89ab-77f4bf0abcef","year":null},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.214499Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:a71cd4d3745b4a69298228b9857dd97a88c8adf65d3fc72c13d7af6a83568f4c","observation_id":"e65840dc-93dc-4a1b-9366-1da507335c6a","resolution":{"observed_at":"2026-08-16T05:13:25.753001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:25.483879Z","title":"Taming transformers for high-resolution image synthesis","venue":null,"work_id":"cc1aa036-c377-4db4-8378-ab1d5bea4cd7","year":2021},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.218081Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:03c555943c4f753a5bead7976640f38955d53d2b22c649068f8ff3d3ee139a31","observation_id":"3477e814-f06d-4785-829d-e2b3f3615f3c","resolution":{"observed_at":"2026-08-16T05:13:25.488215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.00752","last_updated":"2024-05-31T17:55:27Z","snapshot_observed_at":"2026-08-17T20:47:46.242385Z","submitted_at":"2023-12-01T18:01:34Z","title":"Mamba: Linear-Time Sequence Modeling with Selective State Spaces","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.00752","snapshot_observed_at":"2026-08-16T05:13:23.222435Z","title":"Mamba: Linear-time sequence model- ing with selective state spaces","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.222435Z"},"links":{"cited_paper":"/paper/2312.00752","citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:f128d91e216f966bc4eff472cbe6568dcbee0aa54181101874f17e11db20555c","observation_id":"7f555d8b-8d37-4321-95c9-af2e28228302","resolution":{"observed_at":"2026-08-16T05:13:23.222435Z","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":"2026-08-16T05:13:25.471132Z","title":"Efficient diffu- sion training via min-snr weighting strategy","venue":null,"work_id":"4d7e868e-6616-4156-80b5-b09fb5a5a944","year":2023},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.253133Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:d07360c0ab9c989aa44485ac3929f4ff7ceefe1a237fc13d7e4a783360f13746","observation_id":"dc921f8e-2e7f-4f71-96c6-c1639c4f77c4","resolution":{"observed_at":"2026-08-16T05:13:25.476244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:25.308589Z","title":"Neighborhood attention transformer","venue":null,"work_id":"a89da4a1-976f-4a3d-b12b-aab48a417635","year":2023},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.295471Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:193591538ab1ff54e24710156b8212a835c3badb40b4501b657ba117e7f2cc92","observation_id":"9128077e-87c4-4fbd-84c8-1b3d9b7bab7d","resolution":{"observed_at":"2026-08-16T05:13:25.357697Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:13:23.316049Z","title":"Classifier-free diffusion guidance","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.316049Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:d5f39846ed08ceb5ce8dd7c1f8648796278fbcbc327a3e8663866552863a29cd","observation_id":"0e58f682-61d2-46eb-86ce-b6238bac75e0","resolution":{"observed_at":"2026-08-16T05:13:23.316049Z","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":"2026-08-16T05:13:25.288792Z","title":"Denoising diffu- sion probabilistic models","venue":null,"work_id":"f2985917-6b63-4698-a5c9-d63aeb497b75","year":2020},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.319834Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:c6c111ecb7e9ee8c3c48873242d5781f9a98137cbf8366e24a02c9a4a32cc9ec","observation_id":"b893b62c-f6a4-4858-a5d3-6ea4f831a3bd","resolution":{"observed_at":"2026-08-16T05:13:25.292563Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:25.196913Z","title":"Alias-free generative adversarial networks","venue":null,"work_id":"de5d6643-89f1-40fe-9fc1-5b22c78f2fc7","year":2021},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.323490Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:b8e9244e1f95f4210bb63cb857d93eae220888393189ffa41968ddfad8d1a7c6","observation_id":"276fecd5-2493-48d6-8fef-42d232e4358d","resolution":{"observed_at":"2026-08-16T05:13:25.234747Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:25.184840Z","title":"Elucidating the design space of diffusion-based generative models","venue":null,"work_id":"e1c7ca84-63e7-4251-b8e3-3288de3fac20","year":2022},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.327206Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:be77161ebeadb766af0b3c4c30d1e377826122d1d01a8b551600bcdf65db2cc0","observation_id":"dc756dc6-b5a3-493c-b60f-4c5aff047ddb","resolution":{"observed_at":"2026-08-16T05:13:25.188853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:25.173718Z","title":"Analyzing and improving the training dynamics of diffusion models","venue":null,"work_id":"5f0dedeb-7915-4971-afa5-8e851c5bd78d","year":2024},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.331790Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:2960ed7336316276ed839f7a51bfee03cc19534ebd181ff1a3730526f76735d9","observation_id":"0df50b9b-cae6-40b6-abb7-9f8afa36dd61","resolution":{"observed_at":"2026-08-16T05:13:25.177483Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:25.058695Z","title":null,"venue":null,"work_id":"c67eac5a-f176-4c61-813c-b513be17b860","year":2024},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.335657Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:81725a99723fe09bec484bc8cfe9e21a98ebc6c33e010a905bf7d8936df92424","observation_id":"c1d3fd5d-3da1-48e3-b490-3f3eba1f5e13","resolution":{"observed_at":"2026-08-16T05:13:25.165990Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.986326Z","title":null,"venue":null,"work_id":"f52089ea-b451-45bf-aa22-ff5cfeb5db2d","year":2019},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.338982Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:17d6416e4a6a2ae9ab9cac095fa874bf9afdd108c845bf4ef0a180eb2112149f","observation_id":"ed7de0cd-bf6a-4282-b846-6cf3b8ffe322","resolution":{"observed_at":"2026-08-16T05:13:24.990278Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02747","last_updated":"2025-02-26T10:49:33Z","snapshot_observed_at":"2026-08-16T14:03:56.951368Z","submitted_at":"2024-04-03T13:44:41Z","title":"Faster Diffusion via Temporal Attention Decomposition","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02747","snapshot_observed_at":"2026-08-16T05:13:23.342919Z","title":"Faster diffu- sion via temporal attention decomposition","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.342919Z"},"links":{"cited_paper":"/paper/2404.02747","citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:973ed7ffeb0de89bbcaa591d907723771a51ae96200157b0331a0b1e29146cad","observation_id":"2a2049d4-7da3-4801-a954-26c1e83f79c0","resolution":{"observed_at":"2026-08-16T05:13:23.342919Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.02097","last_updated":"2024-10-17T08:09:37Z","snapshot_observed_at":"2026-08-16T13:21:40.483131Z","submitted_at":"2024-09-03T17:54:39Z","title":"LinFusion: 1 GPU, 1 Minute, 16K Image","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.02097","snapshot_observed_at":"2026-08-16T05:13:23.346402Z","title":"Linfusion: 1 gpu, 1 minute, 16k image","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.346402Z"},"links":{"cited_paper":"/paper/2409.02097","citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:4a15ffdcaf8fa9ed951f3a43519e27c1a18fc235fb1f1c670f7ef98839971607","observation_id":"1ce73f91-59b4-402d-b201-ec65c663fcb5","resolution":{"observed_at":"2026-08-16T05:13:23.346402Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.05744","last_updated":"2022-12-05T15:37:39Z","snapshot_observed_at":"2026-08-16T17:35:32.144393Z","submitted_at":"2021-12-10T18:55:50Z","title":"More Control for Free! Image Synthesis with Semantic Diffusion Guidance","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.05744","snapshot_observed_at":"2026-08-16T05:13:23.400547Z","title":"More control for free! image synthesis with semantic diffusion guidance","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.400547Z"},"links":{"cited_paper":"/paper/2112.05744","citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:e23e50439784eddbcf0c27bcd9f117debcc9e29170b19e92239a1e47c864e920","observation_id":"01f18ee4-3953-4363-bca3-0481593350fc","resolution":{"observed_at":"2026-08-16T05:13:23.400547Z","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":"2026-08-16T05:13:24.971505Z","title":"Swin transformer: Hierarchical vision transformer using shifted windows","venue":null,"work_id":"73283c52-667a-4de5-abac-5f46d50aa9d4","year":2021},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.443728Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:14f10be5679ca694abe78da55cc5329978b13f4fb877e5921588bbce7b3d7ebe","observation_id":"92f33a93-d365-4541-8bdb-b352ccbbbc7f","resolution":{"observed_at":"2026-08-16T05:13:24.977269Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T05:13:23.467486Z","title":"Token caching for diffusion transformer acceleration","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.467486Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:769f3e25510f30657e90dc5f1d4882b26d9d96d69ffcf6df06cde67655ae59ed","observation_id":"802b7057-62c9-4fdc-9369-eaf4b656c76c","resolution":{"observed_at":"2026-08-16T05:13:23.467486Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.01095","last_updated":"2025-05-19T07:56:56Z","snapshot_observed_at":"2026-08-17T21:34:28.362812Z","submitted_at":"2022-11-02T13:14:30Z","title":"DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.01095","snapshot_observed_at":"2026-08-16T05:13:23.478064Z","title":"Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.478064Z"},"links":{"cited_paper":"/paper/2211.01095","citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:046a20318566df101f8c4c5e5018771325b0afcbd9f7113345ecd492b0170c50","observation_id":"7197f8be-b6cb-47d8-b49d-0f910cb3ef38","resolution":{"observed_at":"2026-08-16T05:13:23.478064Z","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":"2026-08-16T05:13:24.803213Z","title":"Understanding the effective receptive field in deep convolu- tional neural networks","venue":null,"work_id":"1c3c7141-dda4-44a1-8235-4fda5fc02349","year":2016},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.483044Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:0a86d681a1fd0530c6b658018c0b08446cd30b18e96e19c8489e0429ce84c572","observation_id":"313f2e72-1254-4b13-b288-9f7b931c9127","resolution":{"observed_at":"2026-08-16T05:13:24.909520Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.792352Z","title":"Kingma, Stefano Ermon, Jonathan Ho, and Tim Salimans","venue":null,"work_id":"219c86e1-65f8-4343-a6a7-092126e2726f","year":2023},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.486050Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:9c968806fed3169203140ad924af0bb21f431fe260b16745d8b6230aa98fa4c1","observation_id":"3f35b6bf-8c54-48d5-a74c-a2a3273b5b27","resolution":{"observed_at":"2026-08-16T05:13:24.796516Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.779548Z","title":"GLIDE: towards photorealistic image gen- eration and editing with text-guided diffusion models","venue":null,"work_id":"29064b18-e6c7-4408-9565-b9a4b72d5413","year":2022},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.489064Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:788c6469bff8084318fabe0eb90dbe346a90d9a0c34db4e5760b025f14d85fc6","observation_id":"0c64192b-3673-4ed4-b1b7-c66a021043c2","resolution":{"observed_at":"2026-08-16T05:13:24.783837Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.618026Z","title":null,"venue":null,"work_id":"629a3517-6391-4eb5-ac9e-fff547f26713","year":2024},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.492387Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:32f4a56d7704243cbf0403a6b17d78b5e8075104c6c48c9f792d330cdd08c596","observation_id":"e388da6e-fc73-4bbc-ab5e-6d73dff89b34","resolution":{"observed_at":"2026-08-16T05:13:24.698053Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.606991Z","title":"Scalable diffusion models with transformers","venue":null,"work_id":"21ac7078-dbc1-4eb3-a7e0-a9af75faadb3","year":2023},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.495465Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:4edaba6f332f019e3c43fc0f5b7f669ef8d7c994512efb6ad3c6f4ccdbfa91ee","observation_id":"040c90cb-ab5f-4c65-adbb-043919e320f1","resolution":{"observed_at":"2026-08-16T05:13:24.610380Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.01952","last_updated":"2023-07-04T23:04:57Z","snapshot_observed_at":"2026-08-14T22:54:08.184266Z","submitted_at":"2023-07-04T23:04:57Z","title":"SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.01952","snapshot_observed_at":"2026-08-16T05:13:23.498577Z","title":"SDXL: improving latent diffusion models for high-resolution image synthesis","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.498577Z"},"links":{"cited_paper":"/paper/2307.01952","citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:c3206a751918ef5d136f98f927bdf64c915f8716a503c80691c415aecbcdf623","observation_id":"1f5361bb-6d0f-4b23-9c71-7a5fe37ed309","resolution":{"observed_at":"2026-08-16T05:13:23.498577Z","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":"2026-08-16T05:13:24.529512Z","title":"Proakis and Dimitris G","venue":null,"work_id":"9d97e47b-b23e-45cb-937a-223eb816deb4","year":1996},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.501853Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:6d6fd1fc6afe439dc9401a77cfebd208379768d55b4c5331f8617e9b277fe0be","observation_id":"e177a634-6f2c-4dd4-91ea-a04dbae4060b","resolution":{"observed_at":"2026-08-16T05:13:24.599543Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.467624Z","title":"High-resolution image synthesis with latent diffusion models","venue":null,"work_id":"be85eb98-d402-436a-9a83-51537d63bff9","year":2022},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.505803Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:e21fefaa787d07ce41e6bc485fe08e7acb110314ff597e61e880add3c3df4c32","observation_id":"4ada7950-00d7-4029-86d5-61379ccc04e1","resolution":{"observed_at":"2026-08-16T05:13:24.471349Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.456738Z","title":"U-net: Convolutional networks for biomedical image segmentation","venue":null,"work_id":"d50ecec1-ebcb-4135-92d0-cca57beb8c95","year":2015},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.510755Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:4235592fe2349202c05fc73f8482c9fd347428c56ea3ea221a408cfd74a9ee94","observation_id":"7d6c679d-5c39-44c9-90d8-a29cd4d030c9","resolution":{"observed_at":"2026-08-16T05:13:24.460101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.11487","last_updated":"2022-05-23T17:42:53Z","snapshot_observed_at":"2026-08-17T05:51:02.087480Z","submitted_at":"2022-05-23T17:42:53Z","title":"Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.11487","snapshot_observed_at":"2026-08-16T05:13:23.516270Z","title":"Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.516270Z"},"links":{"cited_paper":"/paper/2205.11487","citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:d81041fe5a7eac26638243428d9a00dffb0a8964ab083ad64f6932ab8dc055b0","observation_id":"cb1efbf7-1a4d-4add-8d42-1bac940b4e41","resolution":{"observed_at":"2026-08-16T05:13:23.516270Z","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":"2026-08-16T05:13:24.437937Z","title":"Stylegan-t: Unlocking the power of gans for fast large-scale text-to-image synthesis","venue":null,"work_id":"52f2922f-a6e5-41e3-b60f-37a14041d01d","year":2023},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.536075Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:5d31504ac14dae53db2f4700f6917a97e465dec08a9cc6b54dc2eca15c9196b5","observation_id":"0402eedd-cd4d-4700-bfb4-7ab1194bf52a","resolution":{"observed_at":"2026-08-16T05:13:24.448438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.390060Z","title":"Laion-5b: A large-scale dataset for training ai models","venue":null,"work_id":"d972a49a-8b81-4dc9-8527-699f87385e7a","year":2022},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.569300Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:4c8d545d1ab58039ec49854d9de7fd3e3affb3fa8420d031ce3e2b7741768985","observation_id":"5316c712-2f78-461b-a5b7-49061dc37d3e","resolution":{"observed_at":"2026-08-16T05:13:24.409166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.01425","last_updated":"2024-07-01T16:14:37Z","snapshot_observed_at":"2026-08-16T13:38:03.111467Z","submitted_at":"2024-07-01T16:14:37Z","title":"FORA: Fast-Forward Caching in Diffusion Transformer Acceleration","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.01425","snapshot_observed_at":"2026-08-16T05:13:23.602018Z","title":"Fora: Fast-forward caching in diffusion transformer acceleration","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.602018Z"},"links":{"cited_paper":"/paper/2407.01425","citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:c39d85117f9c2c7e89f739de36abb83646626b2a29076cec5edc3f93c29d9976","observation_id":"aceb1237-0934-4799-880e-361589e470fe","resolution":{"observed_at":"2026-08-16T05:13:23.602018Z","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":"2026-08-16T05:13:24.380009Z","title":"Denoising diffusion implicit models","venue":null,"work_id":"ff3a4aef-9c64-48dd-86ea-4e969568e3fa","year":2021},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.623244Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:e4b2bb493c6070eb25b67b1679c71c12a9edc4c5b15e577ab4ef059c06825a91","observation_id":"06d5847f-c57a-4677-a417-f2782a359fe2","resolution":{"observed_at":"2026-08-16T05:13:24.383639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.368744Z","title":"Kingma, Ab- hishek Kumar, Stefano Ermon, and Ben Poole","venue":null,"work_id":"b8d6f969-11ee-40ea-9367-5a381ae890d9","year":null},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.627787Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:036c5d040baf375fc01be7b157a1f2fe431eb170d78bf4462d2e99f88fbf9bd2","observation_id":"4d3724bb-943a-4a00-a707-cbcc5c8072b7","resolution":{"observed_at":"2026-08-16T05:13:24.373164Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.343968Z","title":"Expos- ing flaws of generative model evaluation metrics and their unfair treatment of diffusion models","venue":null,"work_id":"f41ef806-24e0-4cb2-9de3-177d0b0ee39a","year":2023},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.632240Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:83a8e3452991a65daff9a387186db5b0b9018916aa7df0113b7bc088711321ab","observation_id":"fadae87b-05bb-47df-b0bc-1a559cbd99cf","resolution":{"observed_at":"2026-08-16T05:13:24.360969Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.281807Z","title":"Rethinking the incep- tion architecture for computer vision","venue":null,"work_id":"3c139be1-d3d7-4244-9ee6-e3c791e80ed0","year":null},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.636363Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:66b8f578226ed9d4b6e5f55306f25e0f4f35fac294c634821b46fc3c9af92677","observation_id":"28217a4f-e2fc-4163-a21f-bae3f5197bd8","resolution":{"observed_at":"2026-08-16T05:13:24.297407Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.270788Z","title":"text2image-multi-prompt: A multi-prompt dataset for text-to-image generation","venue":null,"work_id":"4d1a2d11-36a9-4a3b-b939-ebf282ec4fc9","year":2023},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.640562Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:71a4bd345a2bff7d3bbe41d311892e6d7aeafb275633f46d933e1a7e18136db8","observation_id":"8a4571b2-d12c-44a4-a198-c91a29bdb008","resolution":{"observed_at":"2026-08-16T05:13:24.274251Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.110087Z","title":"Attention is all you need","venue":null,"work_id":"8c2f81c0-6826-4241-b393-c984341d583c","year":2017},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.644724Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:ffc9ab6bb0511575e9dec7cc720e052befed1df57803e217b951e71e9d90c94a","observation_id":"b0c7b602-70d8-4380-82dd-ab6acfa35708","resolution":{"observed_at":"2026-08-16T05:13:24.192012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:24.100113Z","title":"midjourney-v5-202304-clean","venue":null,"work_id":"31987792-00c1-4898-afa0-9c6ed3909a5b","year":2023},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.651842Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:2d30516ee871ac2394a579260546e0a26cc43bed1bc8f7419eb541de09a8acf0","observation_id":"dfeb0648-83c3-4146-9757-7b50c9b77d56","resolution":{"observed_at":"2026-08-16T05:13:24.103327Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-16T05:13:23.989933Z","title":"Ditfastattn: Attention compression for diffusion transformer models","venue":null,"work_id":"3da1261b-0ff1-4467-9396-406afdd41c55","year":2024},"citing_paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-16T05:13:23.656049Z"},"links":{"citing_paper":"/paper/2504.21292"},"observation_digest":"sha256:e7c6b738baf6e71253a6453b449f33940849e323f68b84738dd2cac4cedb9071","observation_id":"c6cdd0fa-bf29-46d7-8663-a87e6a4ae62c","resolution":{"observed_at":"2026-08-16T05:13:24.091649Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.21292","last_updated":"2025-04-30T03:57:28Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T05:04:53.767198Z","submitted_at":"2025-04-30T03:57:28Z","title":"Can We Achieve Efficient Diffusion without Self-Attention? Distilling Self-Attention into Convolutions"},"reference_resolution":{"displayed":46,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":15,"verified_exact":0,"verified_fuzzy":31},"total_outbound_references":46},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2504.21292."}