{"as_of":"2026-08-16T18:49:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:66b929e60b2f3e017b1633c640634b0d3f8128564171011b456aaf4916b28143","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T05:29:37.615787Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/2412.00408/citation-record","integrity":"/paper/2412.00408/integrity","json":"/paper/2412.00408/citation-record.json","paper":"/paper/2412.00408"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T05:29:38.110581Z","title":"Introducing chatgpt,","venue":null,"work_id":"75ab5403-35e8-4146-90ff-f96f604cf00a","year":2022},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.448144Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:b6687fba575df79bcb3726e9c226338ed468c603a73440e6a2261b35a71e077d","observation_id":"7bebb4af-5443-403c-be28-d0adde046e60","resolution":{"observed_at":"2026-08-12T05:29:38.114220Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:38.098665Z","title":"Multilayer fee dforward networks are universal approximators,","venue":null,"work_id":"cd6f4d0c-b105-4d4f-845c-282b4cba7e25","year":1989},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.453065Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:bb43986149da4ce8b1877908d48aac0e12fe381df3360c552bf98e33b487d152","observation_id":"17fe12d9-4f9a-49e2-9373-22486fc3ee65","resolution":{"observed_at":"2026-08-12T05:29:38.103433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:38.088053Z","title":"Gaussian error linear units (gelus),","venue":null,"work_id":"42d5f27b-b0b1-4980-b827-4622fbdad6ee","year":null},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.456763Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:a7563277dbc5a028931a2d2c7119df615f315af378ea9111b0e657afca5027bb","observation_id":"a27fd3a7-9c59-4a9f-a725-3a438452a92e","resolution":{"observed_at":"2026-08-12T05:29:38.092053Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:38.065266Z","title":"Attention is all you need,","venue":null,"work_id":"d8e7f8fb-faa6-4ffa-a8a0-c843a4241cb7","year":2017},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.465023Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:3cb8dd0ccf1c172fc443b4e42bce569506f63bad4995a9a25ff63fe9df03c4e4","observation_id":"8ef5c3fc-cc90-45ad-a124-20e4552bc641","resolution":{"observed_at":"2026-08-12T05:29:38.069035Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:38.054612Z","title":"Nn-lut: neural approximation of non-linear operations for efficien t transformer inference,","venue":null,"work_id":"c4eb638b-1e1a-48c6-b9e5-ffd1481c4cc5","year":2022},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.469022Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:d6fe5b4fc7295668897eb55079d0f0a67ba1ebc7b3d169e0fdd1acab70750500","observation_id":"001de6c2-d927-48a7-b27f-39b88dcd746c","resolution":{"observed_at":"2026-08-12T05:29:38.058539Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:38.043376Z","title":"Peano -vit: Power- efficient approximations of non-linearities in vision tran sformers,","venue":null,"work_id":"78016e15-e239-4a93-b5f8-28dac7ca284c","year":2024},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.473207Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:875bf9b0b8af708a1fb9526b9a77c4ed8ba93b2891337be869a081fab7c4b45d","observation_id":"15a99da5-fb92-4b93-bd92-72807d773b2c","resolution":{"observed_at":"2026-08-12T05:29:38.047464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:38.031353Z","title":"Ml-pla c: Multiplierless piecewise linear approximation for nonlin ear function evaluation,","venue":null,"work_id":"a7817477-72d1-49a2-9283-df18d7be4772","year":2022},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.476852Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:b1b661e4cd702a943d8af427c0d496ff8f6cb739e22d22d0f0368a6be0d4f43b","observation_id":"2db7d1a4-4099-4687-baef-952d9d2e3770","resolution":{"observed_at":"2026-08-12T05:29:38.035951Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:38.020477Z","title":"Hardware-efficient softmax approximation for self-attention networks,","venue":null,"work_id":"54c78fc3-6baa-47e3-9db3-97736458af87","year":2023},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.481157Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:e101c37e00e93bd8e10c753b2abffe0793b3c7ccdb6cc78efdb55492bdf57217","observation_id":"9e67dbf1-c9dd-445c-9a4e-8a3e2754d0ff","resolution":{"observed_at":"2026-08-12T05:29:38.024459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:38.008755Z","title":"Softermax: Hardware/software co-design of an efficient so ftmax for transformers,","venue":null,"work_id":"6d62190a-3c35-4678-bfd8-69678abc671b","year":2021},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.485427Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:2c300b19e17a8c34d7159bc69a66587e0cef128b610f5eaa6b9f909ef32478d6","observation_id":"d42dc450-5846-4d6b-a88c-bbaa94cd3f8c","resolution":{"observed_at":"2026-08-12T05:29:38.013000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.997809Z","title":"A fast, compact approximation of th e exponential function,","venue":null,"work_id":"161744d6-5488-43f7-92cb-6a8f9b53fd95","year":1999},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.490152Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:d2e3a3bc46fe90c93004417e9157c0aa254be4f5beb9c4e0c65d3e4c4420a4c8","observation_id":"5c25f0dc-bc70-4d9d-a311-f15c930ce600","resolution":{"observed_at":"2026-08-12T05:29:38.001612Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.986824Z","title":"Ieee standard for floating-point arithmetic,","venue":null,"work_id":"62525aad-0429-49c4-b295-c554c27feeef","year":2019},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.494268Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:3b317cd3837b525b800e3412bd62f5ed1b8a9532bf642c3afbc255cb5b9f3252","observation_id":"cdd3c068-a7cd-4dff-9dd9-2d10817a1a5d","resolution":{"observed_at":"2026-08-12T05:29:37.991218Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.975644Z","title":"Simple multiple precision algorithms for exponential functions [tips and t ricks],","venue":null,"work_id":"b584ee9a-c432-409d-ba81-3a43b70bfbba","year":2022},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.499181Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:0bb4df5105887e7f8c039b557f0f807dad150e7b276f0bad3b81652f0be09233","observation_id":"014f5894-5357-4b22-a43b-da46000178cc","resolution":{"observed_at":"2026-08-12T05:29:37.979714Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.964485Z","title":"TensorFlow: Large-scale machine learning on heterogeneo us systems,","venue":null,"work_id":"549dece7-de81-4da4-ad1e-9f131bfc4812","year":2015},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.503106Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:acf15ad538cc2d1d7022a9ade434b6d87610dddbae437521cd34f6a89475c559","observation_id":"d1bdd336-8b50-4d0a-88a0-99b313757c2f","resolution":{"observed_at":"2026-08-12T05:29:37.968195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.953180Z","title":"Visionfive 2 datasheet,","venue":null,"work_id":"f44734df-a78b-46b8-817c-59e45189030b","year":2023},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.507159Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:22c79f74bef19d3d74e796e74a66db58de4618f75c0216064be7541b0079431e","observation_id":"dd447936-5613-4999-aa2c-16e9c3fcebde","resolution":{"observed_at":"2026-08-12T05:29:37.957459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.940378Z","title":"Imagenet: A large-scale hierarchical image database,","venue":null,"work_id":"6f510cbe-1593-4774-a2e7-c0b071a78eda","year":2009},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.511331Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:e49e7669392d46028c33144406101063aaf1a28a9a43bb6df0baf2d2dfc4f795","observation_id":"d904b55f-d98c-4412-8ef1-2244d0143884","resolution":{"observed_at":"2026-08-12T05:29:37.945020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.929514Z","title":"Libr ispeech: An asr corpus based on public domain audio books,","venue":null,"work_id":"56ecf3ad-d1ab-4b3f-91da-be191f301473","year":2015},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.515571Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:9e3099773e1db39705457676adcdc05876ec98b6e8b6b47cccd2e95f55d957a7","observation_id":"5f3a642f-07a0-47ad-bec3-b032d43d572c","resolution":{"observed_at":"2026-08-12T05:29:37.933297Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.917997Z","title":"Hellaswag: Can a machine really finish your sentence?","venue":null,"work_id":"04b1592c-2b39-4342-8e40-514f68fd574f","year":2019},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.520316Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:24ee2b34342c66fc8983042d35f5c461f71d780e7f3ea5589debfaf680642a21","observation_id":"a3ba0686-f42a-4d3f-97a0-95a3480484d9","resolution":{"observed_at":"2026-08-12T05:29:37.922472Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.906498Z","title":"Raspberry pi 5,","venue":null,"work_id":"a0d8920b-0e57-433e-aa3e-588f14181e38","year":2024},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.523898Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:5cce3a3960439e93ce5a510c417f15d6197fd2027dda03129c20361bf8541493","observation_id":"e368a388-75e3-49ea-b84d-e9b8bcb960f7","resolution":{"observed_at":"2026-08-12T05:29:37.910570Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.896494Z","title":"Raspberry pi zero 2 w,","venue":null,"work_id":"3df62706-909e-4a80-8dcc-0fb98c9390c9","year":2024},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.527415Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:3e1f55d10d6e76063950ead8e2e4cb014bb372a9d3873308e8faefed983e6a4e","observation_id":"0d556b6e-3a99-4fcd-908f-bd3811cb25e7","resolution":{"observed_at":"2026-08-12T05:29:37.900076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.885635Z","title":"Amd epyc™ 7002 series processors: A new standard for the modern data center,","venue":null,"work_id":"65a05435-7552-48d1-9701-9a3442fcf9bb","year":2020},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.531394Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:cd3ac488a28d833844286211f549f0033a90d1fdcab18e10094f1cc565ddcd17","observation_id":"a02bb970-a875-4145-8510-9bf095d0ccfa","resolution":{"observed_at":"2026-08-12T05:29:37.889489Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.873765Z","title":"An image is worth 16x16 words: Trans- formers for image recognition at scale,","venue":null,"work_id":"883b9895-a731-4826-8f7c-89a108c30a96","year":2021},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.535136Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:98f9f0e78c1590ac0c7117e4b0e3b2b1f71a4550bb257b0183452c1f0e820951","observation_id":"0ab505c7-5705-408f-88e5-86b8efddbab5","resolution":{"observed_at":"2026-08-12T05:29:37.877739Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.862513Z","title":"Swin transformer: Hierarchical vision transforme r using shifted windows,","venue":null,"work_id":"11d0fe38-8851-4755-b1bd-594231354c64","year":2021},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.539390Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:df19aad4cedefe5d7b66c018f9c5d5500137c88e299df69b9ea01d1ee1f8c8fd","observation_id":"f6d1516f-c6c5-4093-8a67-293300577062","resolution":{"observed_at":"2026-08-12T05:29:37.866725Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.851219Z","title":"A convnet for the 2020s,","venue":null,"work_id":"14025e58-4417-4f59-b281-8b76878bd8b5","year":2022},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.543186Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:f55f1c29b5496d61bc427dbd06d3956eaa555f191be4360fc012c11c95ad2fd1","observation_id":"a09ba3f3-7585-4b53-aa20-2de8f2de3126","resolution":{"observed_at":"2026-08-12T05:29:37.854922Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.840455Z","title":"Y olov8,","venue":null,"work_id":"175dfa4f-dcb3-4cfa-98d1-0c4d6d16e16b","year":2022},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.546579Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:99d8e4de4063b4989bf3ea7d0658fd21243dfc9eb78261db845e10f8af6508fa","observation_id":"25c3fcb9-6002-4ab1-a6c5-012b054b6a01","resolution":{"observed_at":"2026-08-12T05:29:37.844373Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.12156","last_updated":"2023-06-21T10:08:29Z","snapshot_observed_at":"2026-08-16T15:22:17.250833Z","submitted_at":"2023-06-21T10:08:29Z","title":"Fast Segment Anything","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.12156","snapshot_observed_at":"2026-08-12T05:29:37.549859Z","title":"Fast segment anything,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.549859Z"},"links":{"cited_paper":"/paper/2306.12156","citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:20c44c038563e5bf8903fcaf7b0e46234f516430609ad3fb2e8c051cf9c542bc","observation_id":"21145929-d4e0-4600-8ff3-a95640d11108","resolution":{"observed_at":"2026-08-12T05:29:37.549859Z","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":"2026-08-12T05:29:37.827577Z","title":"Robust speech recognition via large-scale w eak supervi- sion,","venue":null,"work_id":"c6a29af5-0b48-443d-84e6-278215fb2276","year":2023},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.554340Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:3e852a09c65f324756088539e4aa8577f4636405048c4e3343f9b6aaccac2451","observation_id":"bd2e5eaf-e328-44fb-8bbe-f5f344e4a1a5","resolution":{"observed_at":"2026-08-12T05:29:37.832419Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.814721Z","title":"Opt: Open pre-trained transformer langua ge models,","venue":null,"work_id":"bf795efa-cc76-4c69-9517-e804975c3363","year":null},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.558954Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:be4b3be5797256cca8cc30756cfceffe73b88a8d802226b3d244f6eb105344bf","observation_id":"dabd77da-3ae0-472a-b36d-e676ddd6a677","resolution":{"observed_at":"2026-08-12T05:29:37.819326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.790046Z","title":"Language models are few-shot l earners,","venue":null,"work_id":"f978f2de-f403-4a0b-bd11-befe0103cc82","year":null},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.568200Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:842a0ae980ab56d442ff35ff944a19160826bcec3eb9b1cce7b95a264121b168","observation_id":"29ef1638-31db-457f-a112-f5aa68dc4be6","resolution":{"observed_at":"2026-08-12T05:29:37.794351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.767642Z","title":"Language models are unsupervised multitask learners,","venue":null,"work_id":"001b1077-eeae-44a9-9e4c-5001bad16c3e","year":2019},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.577303Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:1412a06a3ea8766792f0d77df21fea747c112c635918ad25f158755b2f06d30f","observation_id":"d9ae364c-633f-4afe-824e-961a60ff270e","resolution":{"observed_at":"2026-08-12T05:29:37.771327Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.756356Z","title":null,"venue":null,"work_id":"6e2b3209-c767-4972-a6ce-28af2c82b5f7","year":2011},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.581597Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:5b03820d646f153de7cf5252eb45b8c11aa02525651c95b2a4134f3d53a20422","observation_id":"7b5174ed-19ba-4865-965b-a92db533715f","resolution":{"observed_at":"2026-08-12T05:29:37.760009Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.743516Z","title":"Computer multiplication and division using binary logarithms,","venue":null,"work_id":"429a0167-6c4a-4c80-8e69-7d0783c95b21","year":1962},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.585846Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:f74de9bc39bdee4112df67a41fe12148e857b84028e18566b15bcd80afa93c67","observation_id":"828ab826-8a23-4d3a-abf2-9652ee2b1985","resolution":{"observed_at":"2026-08-12T05:29:37.748330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.730633Z","title":"sqrt implementation in fdlibm,","venue":null,"work_id":"b045104c-d8cc-4e9b-9519-f4fae97684ee","year":null},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.590366Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:546dddff45e88455911cede2bb33b8cd75f1dc833ffc0eba395f487825223523","observation_id":"7e80b562-036d-4ea6-854a-dd19ab565820","resolution":{"observed_at":"2026-08-12T05:29:37.735477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.719329Z","title":"Fast inverse square root,","venue":null,"work_id":"673d1183-6b03-47f1-ab91-0c4ef2793cf2","year":null},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.594965Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:b3967d415e789853984ecd2619a7dbc00e574ca5f14705717f9af12cd4ad2393","observation_id":"6b74f9a1-f8f6-4d06-829f-ef96d0bafe96","resolution":{"observed_at":"2026-08-12T05:29:37.722908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.707404Z","title":"Aifes: A next-generation edge ai framewo rk,","venue":null,"work_id":"9552c6df-a444-488a-b845-d566b00bcb35","year":2024},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.599442Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:3f2d992ffa287f3db9de9a0cc2c12c4b51832526921c2c4176c8eeeccba84898","observation_id":"a91fe7c1-ab1f-4d05-bb05-237a16963929","resolution":{"observed_at":"2026-08-12T05:29:37.711434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.695275Z","title":"C ompiling kb- sized machine learning models to tiny iot devices,","venue":null,"work_id":"b4c77129-abef-4a6e-a685-b1f1c094c3ed","year":2019},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.603792Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:67e1761724b1969d2293b175c2f61badae00fe050dd49bc2783ff96f6331b4d1","observation_id":"b8913d59-8ff0-4605-b9f4-663d9633e825","resolution":{"observed_at":"2026-08-12T05:29:37.699553Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.681700Z","title":"Fast approximations of expon ential and loga- rithm functions combined with efficient storage/retrieval for combustion kinetics calculations,","venue":null,"work_id":"9892f4f8-0f52-482f-a3da-be16177f4e43","year":2018},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.608100Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:1ea49afda4040ad6576d6d83e53b3c9a665e468183dea9e5d055c41a1e744f77","observation_id":"02529958-b4cf-4d72-8433-67f2e6f072fc","resolution":{"observed_at":"2026-08-12T05:29:37.686827Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.669858Z","title":"Two-pass softmax algorit hm,","venue":null,"work_id":"b3526fa7-130b-460d-b019-b8bb8bb925aa","year":2020},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.612236Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:6447e156fb43e3fb9a3d7e86e986ae490fb09316eab91be315c4f515be61cf1e","observation_id":"af1fe935-f520-4d96-971e-0ce81fb7af7a","resolution":{"observed_at":"2026-08-12T05:29:37.673758Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.656219Z","title":null,"venue":null,"work_id":"8f5af158-d4e3-49d4-be60-f82bf177a3cd","year":1980},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.615787Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:22d90d6a49111f30e689162f88c6eb0a4287198f79527dfb6cf9c026dc5cec5c","observation_id":"1c8bc1d8-5f0b-48e5-a8dd-aaf58f78435a","resolution":{"observed_at":"2026-08-12T05:29:37.661110Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.778983Z","title":"Available: https://arxiv.org/abs/2005","venue":null,"work_id":"4e1f6de8-8b07-423e-ab44-425a48c5f7ff","year":2005},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.572901Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:24019524fe96e469491b88a1f764b18fb74412ea68d72ad69ff227fbf18e754a","observation_id":"6bab3e4e-c2d6-4e71-a72c-9b2c84c04894","resolution":{"observed_at":"2026-08-12T05:29:37.782911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:37.802008Z","title":"Available: https://arxiv.org/abs/2205","venue":null,"work_id":"382b3bf9-7685-4a84-87f2-bd11b8daff45","year":null},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.563919Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:e25f9f94d00a476344339f57457616a76bf2bd939f240be6f42a2bd5077628c4","observation_id":"f3a75dd2-d26f-4767-8f61-a30a5c823124","resolution":{"observed_at":"2026-08-12T05:29:37.806700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T05:29:38.076474Z","title":"Available: https://arxiv.org/abs/1606","venue":null,"work_id":"539a1ed0-ac7f-498a-9733-5aa63dec4e6a","year":null},"citing_paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-12T05:29:37.460891Z"},"links":{"citing_paper":"/paper/2412.00408"},"observation_digest":"sha256:1f87ae57d6c9ceda30c3dc2bd9e70cbd2b770e6fbaebc69e8be7380842547a26","observation_id":"91dd5b4a-4e16-46ba-adb9-20515d988059","resolution":{"observed_at":"2026-08-12T05:29:38.080912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.00408","last_updated":"2024-11-30T09:26:56Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-12T05:22:57.020739Z","submitted_at":"2024-11-30T09:26:56Z","title":"QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":0,"verified_fuzzy":38},"total_outbound_references":41},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2412.00408."}