{"as_of":"2026-08-18T18:24:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7cd2920060e4eaf4b7f002f585b5dbaa041a249b1a98fbe25fd218f15fdd12aa","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T01:40:35.589014Z","state":"measured"},{"denominator":25,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":25,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+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/2607.27251/citation-record","integrity":"/paper/2607.27251/integrity","json":"/paper/2607.27251/citation-record.json","paper":"/paper/2607.27251"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T01:40:35.525411Z","title":"Graph- transformer-based surrogate model for accelerated converter circuit topology design,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.525411Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:21d4dbdae4496b2b24ad3f8abfb4f552ebb7b7401104a46f8d3376829626078b","observation_id":"bee97df0-eafe-451e-8997-3902c28b6e75","resolution":{"observed_at":"2026-08-01T01:40:35.525411Z","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":"2026-08-01T01:40:35.529080Z","title":"Transformer for partial differ- ential equations’ operator learning,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.529080Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:f19e4d26c9ba355e1f59302d78687882a88f6cf41da84a144dcc174a5664b2e3","observation_id":"1fc4f562-e575-4302-b780-28dc2210756e","resolution":{"observed_at":"2026-08-01T01:40:35.529080Z","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":"2026-08-01T01:40:35.531773Z","title":"Transformer self-attention encoder–decoder with mul- timodal deep learning for response time series forecasting and digital twin support in wind structural health monitoring,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.531773Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:ce941c90de72d91bacd043f4838cec363c55d2a9ebf63afeb1d4eaf0db2635c3","observation_id":"ae87756c-37a7-45fe-9168-48471d5be9b9","resolution":{"observed_at":"2026-08-01T01:40:35.531773Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.02891","last_updated":"2025-05-19T02:25:48Z","snapshot_observed_at":"2026-08-17T02:39:30.990431Z","submitted_at":"2025-02-26T22:34:44Z","title":"Vision Transformers on the Edge: A Comprehensive Survey of Model Compression and Acceleration Strategies","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.02891","snapshot_observed_at":"2026-08-01T01:40:35.534293Z","title":"Vision transformers on the edge: A comprehensive survey of model compression and acceleration strategies,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.534293Z"},"links":{"cited_paper":"/paper/2503.02891","citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:20a5f4b53616308fd3bc64a80ee566bd3efa444e02870b7136d4f6ecf6467ee5","observation_id":"c94813b9-f159-4d2e-a088-eafa2fc2eff9","resolution":{"observed_at":"2026-08-01T01:40:35.534293Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.04372","last_updated":"2025-03-26T06:49:33Z","snapshot_observed_at":"2026-08-17T00:42:09.985672Z","submitted_at":"2024-12-05T17:49:10Z","title":"Distributed Inference with Minimal Off-Chip Traffic for Transformers on Low-Power MCUs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.04372","snapshot_observed_at":"2026-08-01T01:40:35.537730Z","title":"Distributed inference with minimal off-chip traffic for transformers on low-power mcus,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.537730Z"},"links":{"cited_paper":"/paper/2412.04372","citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:356c3c42cbe258c44f8207040fd5c9f7624229f24164a04eaaff8fe718af8705","observation_id":"17ad0fae-e27d-4055-8559-ff1b7e85a0d8","resolution":{"observed_at":"2026-08-01T01:40:35.537730Z","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":"2026-08-01T01:40:35.540909Z","title":"Flashattention: Fast and memory-efficient exact attention with io-awareness,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.540909Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:04320e5e7df3294a72cb4ac42a0d58c7811b54119ca0d95dbff2efe77dc12309","observation_id":"4742e89f-8c88-4da2-9979-3e4d4620bf74","resolution":{"observed_at":"2026-08-01T01:40:35.540909Z","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":"2026-08-01T01:40:35.544054Z","title":"Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.544054Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:43090e359661c4c4c719cdd85d881ee503a66054fd87ca4fe94bd06610c5620d","observation_id":"b2f9f678-1fa0-4cf9-bbde-31890c96db21","resolution":{"observed_at":"2026-08-01T01:40:35.544054Z","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":"2026-08-01T01:40:35.546660Z","title":"Universal transformers,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.546660Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:e70e8a3147bd2f680f41c3e4a5a99999d8f4710ef0f2225aca4c6099c38271e4","observation_id":"945a2ba9-d4e5-414b-874e-0f644efec5e6","resolution":{"observed_at":"2026-08-01T01:40:35.546660Z","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":"2026-08-01T01:40:35.549069Z","title":"Learning both weights and connections for efficient neural networks,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.549069Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:804f77e7c648f46ee7e482588d37c1ed56713659c386d48ff96c71448a1bcaa7","observation_id":"542e06d5-9bb7-4490-ab46-9d9b60168b21","resolution":{"observed_at":"2026-08-01T01:40:35.549069Z","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":"2026-08-01T01:40:35.551583Z","title":"Transformers are rnns: Fast autoregressive transformers with linear attention,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.551583Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:6f4133b31bccc6e74b34b163c8b617ced965a0073684f954e4dc3d8e6c32862b","observation_id":"e5bca91d-8549-4341-a4e2-81686c004cd7","resolution":{"observed_at":"2026-08-01T01:40:35.551583Z","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":"2026-08-01T01:40:35.554025Z","title":"Dynamicvit: Efficient vision transformers with dynamic token sparsification,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.554025Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:469a468df1af0d803e5c9e59a1a4a3f94b3810fe42ed25c5c329c28eb98f18b9","observation_id":"cd673d35-f257-4139-96cc-b4d1250e9ad2","resolution":{"observed_at":"2026-08-01T01:40:35.554025Z","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":"2026-08-01T01:40:35.556405Z","title":"Token merging: Your vit but faster,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.556405Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:19160969fc3fe41e38e6702322d1b7f2c596cd37e50f0446a750c213f337f5ff","observation_id":"659803c7-0531-4ef4-ba02-ac00639a4396","resolution":{"observed_at":"2026-08-01T01:40:35.556405Z","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":"2026-08-01T01:40:35.558720Z","title":"Glam: Efficient scaling of language models with mixture- of-experts,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.558720Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:83f0d5aace9fb4256196734100f6b7af6957ee65731b9a89d0f4ff136bbff77b","observation_id":"66521b6d-6f86-4e83-bd1d-302acb32bc8d","resolution":{"observed_at":"2026-08-01T01:40:35.558720Z","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":"2026-08-01T01:40:35.561426Z","title":"Albert: A lite bert for self-supervised learning of language representa- tions,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.561426Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:4424e5d462c9a182c5fab6c401edfd3a767b47b3777b89359572cbd7962616fd","observation_id":"65b1d6bb-5761-4ec6-a019-29ea8c02359e","resolution":{"observed_at":"2026-08-01T01:40:35.561426Z","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":"2026-08-01T01:40:35.563717Z","title":"Looped transformers are better at learning learning algorithms,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.563717Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:fc42d713e66f020a1bc948fdb64432564c042932721e6881440d26af66711276","observation_id":"50d24429-d807-430e-94dc-126abb4cf15a","resolution":{"observed_at":"2026-08-01T01:40:35.563717Z","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":"2026-08-01T01:40:35.566070Z","title":"Tiny recursive models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.566070Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:816f1afdb9207a74f04a882384c69573bdfa5673a299d5b40d26462a95c3febc","observation_id":"8cf7525b-0ec9-40dc-a6fc-5e28ef29e3ef","resolution":{"observed_at":"2026-08-01T01:40:35.566070Z","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":"2026-08-01T01:40:35.568539Z","title":"Distilling the knowledge in a neural network,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.568539Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:d727178db931dab04935174a0b7e1da65472fa9b1ac5a9238dd94ab6ef5933d8","observation_id":"e2badded-6a0b-4b8e-8cd1-201b3423c16f","resolution":{"observed_at":"2026-08-01T01:40:35.568539Z","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":"2026-08-01T01:40:35.571375Z","title":"Lora: Low-rank adaptation of large language models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.571375Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:fec1f313c43e07a3a47eb7686c5eea54f0d4f59cba152d4728f5778c0489b016","observation_id":"3a05d6fe-a253-40e8-b729-04b324ede22d","resolution":{"observed_at":"2026-08-01T01:40:35.571375Z","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":"2026-08-01T01:40:35.573821Z","title":"Flashattention-2: Faster attention with better parallelism,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.573821Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:79a0c9aa293ec88c8eb22690c673d95c6e1e6dcedbc2ecc7c97914909ce43339","observation_id":"edbce6f5-7102-42eb-b0b8-066a76f885bb","resolution":{"observed_at":"2026-08-01T01:40:35.573821Z","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":"2026-08-01T01:40:35.576336Z","title":"Tensorrt-llm,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.576336Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:6bc492d6c301b5296213489ac587b4c29369cd52e112f362f7b9c88434beee35","observation_id":"8489a90f-d4d0-4693-af5b-a513d2cf8ffc","resolution":{"observed_at":"2026-08-01T01:40:35.576336Z","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":"2026-08-01T01:40:35.579148Z","title":"Efficiently modeling long sequences with structured state spaces,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.579148Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:665de9f54f710ca520bb3b636df24e87ef5f08d97124cb89a7019d78b700130b","observation_id":"31756b30-8315-4520-92c4-fc38f3456875","resolution":{"observed_at":"2026-08-01T01:40:35.579148Z","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":"2026-08-01T01:40:35.581674Z","title":"Mamba: Linear-time sequence modeling with selective state spaces,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.581674Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:9ebef5017af5e4c66f2df9038e6dc09c435233e9d3b3b6aa396a86708b1b1a9d","observation_id":"fed19c49-d5ee-474b-8a5a-651080776d7f","resolution":{"observed_at":"2026-08-01T01:40:35.581674Z","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":"2026-08-01T01:40:35.584070Z","title":"Mixtral of experts,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.584070Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:aab0c1249375715fba3066b9d0f83cd1d60f23006cfd51fc7ae33ad0557b39f5","observation_id":"e523f8d5-7d2a-4fb4-8a8d-afd7cc36e37c","resolution":{"observed_at":"2026-08-01T01:40:35.584070Z","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":"2026-08-01T01:40:35.586584Z","title":"Deep clustering based boundary-decoder net for inter and intra layer stress prediction of heterogeneous integrated ic chip,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.586584Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:ea19fb4ee2fa7014c004497c5f6c4b36a0d9a103763f23988d2047400744cd03","observation_id":"290db4a9-ba58-4b28-86a6-f69ea3e2e708","resolution":{"observed_at":"2026-08-01T01:40:35.586584Z","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":"2026-08-01T01:40:35.589014Z","title":"Inverse prediction of capacitor multiphysics dynamic parameters using deep generative model,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T01:40:35.589014Z"},"links":{"citing_paper":"/paper/2607.27251"},"observation_digest":"sha256:e5d7d3fbb7c695cf56bf4e1025006b6cadc10296d0d04250cdb08a00f875801d","observation_id":"7135ae85-14cb-4f4a-a162-b1f4cc4c4517","resolution":{"observed_at":"2026-08-01T01:40:35.589014Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.27251","last_updated":"2026-07-28T13:58:37Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T16:19:41.566216Z","submitted_at":"2026-07-28T13:58:37Z","title":"Recursive transformers for semiconductor thermo-mechanical reliability"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":25,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":25},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2607.27251."}