{"as_of":"2026-08-08T05:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ba7ce6836f19f421213733b69d7938fdbab22ce15efaa6ffc3ad52261d024e1a","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T16:57:33.640328Z","state":"measured"},{"denominator":47,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":47,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2507.12205/citation-record","integrity":"/paper/2507.12205/integrity","json":"/paper/2507.12205/citation-record.json","paper":"/paper/2507.12205"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:57:37.205875Z","title":"https://docs.nvidia.com/cuda/cublas/index","venue":null,"work_id":"9735f825-c4a7-4230-a727-a1b306c7340d","year":2024},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:28.542169Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:2e4f509eec3879588a5c3ab818422e9fba365c0670b38bc3d196c2b3f4473821","observation_id":"48a63018-7cf9-4643-95a2-162f8bdf7e07","resolution":{"observed_at":"2026-08-06T16:57:37.211118Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.191494Z","title":"M., Buluç, A., Williams, S., and Y ang, C.Optimizing sparse matrix- multiple vectors multiplication for nuclear configuration interaction calculations","venue":null,"work_id":"2ac918a7-ceb8-4346-847d-5c98d7c48f31","year":2014},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:28.646996Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:ce6aff4c19ea18a0c3087cdbc62fcc89aa939fbd8d699a9f685ec0e375af839f","observation_id":"e74c6229-dcd0-44da-bda5-5477f16a7be9","resolution":{"observed_at":"2026-08-06T16:57:37.196281Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.176189Z","title":"Fast sparse matrix-vector multiplication on gpus for graph applications","venue":null,"work_id":"1b0ed1b1-8f5a-4283-a6f5-1e06fd8ea602","year":2014},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:28.754124Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:f672b39f2d703ecf848b3f949e095ab3d74f4405f1dfdc95d10cf0238c5a0460","observation_id":"c97a557a-fac1-401c-aa9a-0df47fb8909c","resolution":{"observed_at":"2026-08-06T16:57:37.181182Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.162080Z","title":"Efficient sparse matrix-vector multiplication on cuda","venue":null,"work_id":"5471b523-0fda-4521-93cc-a860e26a7b43","year":2008},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:28.828409Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:bbbd43f5631b5e64b80caf120c3c1a7fc9206af8ae5533d3eaec18692fd5d34d","observation_id":"490c7c82-b1d0-472b-95b2-eeab2e50fd88","resolution":{"observed_at":"2026-08-06T16:57:37.166702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.147320Z","title":"On the relations between ilus and factored approx- imate inverses","venue":null,"work_id":"53f6ccbf-07ff-4051-b659-e90089d31d15","year":2002},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:28.901761Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:4a6baa443ee316aa948ea2d43130c6a63d312b6062262fcc04c1e9bae93ec414","observation_id":"3464eca1-787c-4aea-a21d-876979d64e4f","resolution":{"observed_at":"2026-08-06T16:57:37.151931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.133475Z","title":"In SC22: International Conference for High Performance Computing, Networking, Storage and Analysis (2022), IEEE, pp","venue":null,"work_id":"7c772533-a19d-4ef3-b71a-28aee3d5606e","year":2022},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:28.999888Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:7f907c9ac1a00b300343b3188f4903ecbbabc38192817a0d4552f6617f30ab71","observation_id":"cde669b4-9605-4140-bbfd-e8e2ff075da4","resolution":{"observed_at":"2026-08-06T16:57:37.137985Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.118375Z","title":"Scaling algorithms for weighted matching in general graphs","venue":null,"work_id":"7f2e99a9-49b7-4dec-bb93-8a8190093047","year":2018},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:29.073778Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:922b35d1eca29075512ef6bf08e09abc3f42381909adf7d01b54c5b6e92a6bbe","observation_id":"603493ed-e13f-4a82-9779-850e44bf4070","resolution":{"observed_at":"2026-08-06T16:57:37.123188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.103058Z","title":"Spinfer: Leveraging low-level sparsity for efficient large language model inference on gpus","venue":null,"work_id":"c604b1ff-e45b-44fb-98aa-8acc42eb78f9","year":2025},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:29.142189Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:ce30c538cfcc83780810bd872b5e6613b6e7f0cc50e1aec21f75c501f16a3601","observation_id":"ba33c097-54d3-4f54-97a3-a3bb9d37a992","resolution":{"observed_at":"2026-08-06T16:57:37.108219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.087188Z","title":"Sparsegpt: Massive language models can be accurately pruned in one-shot","venue":null,"work_id":"eeab4667-6274-4c13-92ca-747bf1f6fdd4","year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:29.214424Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:9ff2e53b87e4dedb64eed49c0d9a61cac7d7826b50eff87d5090e09d678055d5","observation_id":"02d83cfa-cdc3-4bb5-b99a-fb6a4782ba62","resolution":{"observed_at":"2026-08-06T16:57:37.091869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.072892Z","title":"Leveraging index compression techniques to optimize the use of co-processors","venue":null,"work_id":"2e44b75b-7d12-4bb7-a9a5-50d883a945e3","year":2024},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:29.292206Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:ede79c2d9b17e7932524f9b18c55f23b1e6771228e7eed44c2717d23a2c496fd","observation_id":"4bdbb461-922d-4b48-9ef7-e9429071805c","resolution":{"observed_at":"2026-08-06T16:57:37.077629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.057599Z","title":"Sparse GPU kernels for deep learning","venue":null,"work_id":"f368d4e4-4ef4-4707-a1b8-14205538df73","year":2020},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:29.372395Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:93015a1701ed69cf3919a18384fac18dd172c4c7eab833dc5cb22ad0427b361e","observation_id":"f04e6b05-ae1f-4b3c-b175-a542ff16c034","resolution":{"observed_at":"2026-08-06T16:57:37.062242Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.043629Z","title":"ggerganov/llama","venue":null,"work_id":"cd8cc466-2a1a-4fdd-a156-430871973bb1","year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:29.505170Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:19865d30e9438dfbdea1a0365a9034fda036158a26fea191a299c94d9fb46679","observation_id":"ced03fe2-8687-4b8a-beb0-a7f9fcee5273","resolution":{"observed_at":"2026-08-06T16:57:37.048160Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.029243Z","title":"L., and Daga, M","venue":null,"work_id":"4b848cb5-b1ab-4e6c-ab1e-eb6a2795ee39","year":2014},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:29.588403Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:687e1d78bf85fee613bc51669152118a06a7b7444243b411b68fd9f7c44d07e0","observation_id":"57e6c840-e4e6-4e2b-a172-e08de5a78e03","resolution":{"observed_at":"2026-08-06T16:57:37.033721Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:37.013786Z","title":"Y., Leng, J., Qiu, Y., Guan, Y., W ang, Z., Jia, X., Li, X., Guo, M., and Zhu, Y","venue":null,"work_id":"48dc95cc-2a85-4c4c-ac20-d1a7d4467077","year":2020},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:29.688320Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:21d03e7d958f331e7bc12e75fd7f799a02d1c8b6d3faa659a602e0435a00ed21","observation_id":"8b4ff62c-ddbe-4048-ba7d-d7c0d0eab7c5","resolution":{"observed_at":"2026-08-06T16:57:37.018716Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.998817Z","title":"In Proceedings of the 24th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, PPoPP 2019, Washington, DC, USA, February 16-20, 2019 (2019), ACM, pp","venue":null,"work_id":"f28da063-a7e5-4449-b6e6-6cbae0941445","year":2019},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:29.789797Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:193b7b595687c53b7a9397c23db40528cfcb82b55ad5b60f528c873d2637996e","observation_id":"6f701053-2b7c-44d3-849d-4b4e92d299a4","resolution":{"observed_at":"2026-08-06T16:57:37.003567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.984965Z","title":"Flashdecoding++: Faster large language model inference with asynchronization, flat gemm optimization, and heuristics","venue":null,"work_id":"fd6822ec-828d-4cc4-a31c-5118e82c00a6","year":2024},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:29.890563Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:9981b9720764a0325bc29c3502895178b4bb7947895f6f14facd4006ef5ad9fa","observation_id":"241a9bab-12fb-49a2-a192-1c1353043314","resolution":{"observed_at":"2026-08-06T16:57:36.989336Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.971444Z","title":"In Proceedings of the 25th ACM SIGPLAN symposium on principles and practice of parallel program- ming (2020), pp","venue":null,"work_id":"5e35b35a-e6e2-4740-9f78-261bc5c553b1","year":2020},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:29.971335Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:3704c5a8bc8bb63e9d3b86624d35628c1bec6c9e5d2848d1cc8dec8506ce0092","observation_id":"66d04aa1-90c5-4445-b1c0-22621663ff4f","resolution":{"observed_at":"2026-08-06T16:57:36.975601Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.957576Z","title":"Maximum bounded 3-dimensional matching is max snp-complete","venue":null,"work_id":"ea31bba0-f919-4ef7-93ba-2163187126b7","year":1991},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:30.042219Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:963f3fa47eb337ecef07664b3eb5d7c0b010497a58a06e51acc2ea137fe08c0d","observation_id":"ba390c32-a1f8-4c43-b859-fd9fa46e476a","resolution":{"observed_at":"2026-08-06T16:57:36.961843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.943789Z","title":"Computational complexity of the perfect matching problem in hypergraphs with subcritical density","venue":null,"work_id":"58550a82-8cec-4ab7-b49f-12381937d6f1","year":2010},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:30.110288Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:dde05acd1678dbcae8792dcfb244052bac5c68632d49db68f027adab2ab0a607","observation_id":"c2a7b3a5-33ed-44cb-b088-a48c1f71cee7","resolution":{"observed_at":"2026-08-06T16:57:36.948405Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.930261Z","title":"Optimizing sparse matrix-vector multiplication using index and value compression","venue":null,"work_id":"d6ed7b29-883b-4075-b18e-3f9b0d1be274","year":2008},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:30.192910Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:abce3ee3c157bbde75b77460d21b8e92994ad2632236900c116d07a2b01045fd","observation_id":"3c631827-6d0e-499c-a6ff-359e5020e677","resolution":{"observed_at":"2026-08-06T16:57:36.934657Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.916536Z","title":"ACM Transactions on Architecture and Code Optimization (2024)","venue":null,"work_id":"9decf830-7e5a-4526-8849-2f762c78173d","year":2024},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:30.292321Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:ec5e718e3d6d4c064640f11b8c9f82cd37e39feac23c23eade00d8f4326edcfa","observation_id":"80d4e512-f945-4554-ac46-978fa9d1234f","resolution":{"observed_at":"2026-08-06T16:57:36.921002Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.902542Z","title":"Csr5: An efficient storage format for cross-platform sparse matrix-vector multiplication","venue":null,"work_id":"85aa893c-c657-42c5-baf5-0935c1448169","year":2015},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:30.369287Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:65406914fd422ac62e04a976e88698c8b9971aaf6e8ca3f8f2d4c945d4a60e75","observation_id":"0204ba87-e55d-4302-a816-413f1822313f","resolution":{"observed_at":"2026-08-06T16:57:36.907128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.889353Z","title":"Spp: Sparsity-preserved parameter-efficient fine-tuning for large language models, 2024","venue":null,"work_id":"749945a8-3dfa-409e-8fc8-910a1cad81d6","year":2024},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:30.445136Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:1c4163efcad99c3419b06004d093a7be6a8a3cafcaaadc509b604262cb29cf74","observation_id":"9653f73c-a23b-4de5-9b01-490916a57d2e","resolution":{"observed_at":"2026-08-06T16:57:36.893724Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.875808Z","title":"Dasp: Specific dense matrix multiply-accumulate units accelerated general sparse matrix-vector multiplication","venue":null,"work_id":"d845bdb6-0a1b-4e72-9706-640455db755c","year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:30.519844Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:6ed560992f8dc60af8fb88de7e35b1cb29f8be32a841ab6acc1aa0b2c478e47d","observation_id":"7222110e-eb3a-4c27-96e4-c5d2073cebdb","resolution":{"observed_at":"2026-08-06T16:57:36.880069Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.862280Z","title":"Llm-rec: Personalized recommendation via prompting large language models","venue":null,"work_id":"9fd4071e-3bfc-4ab7-8b47-759aeab93be2","year":2024},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:30.592794Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:89fb4f7d579793eae7cad4251a653e427edb3e73f0ed254c0078546781172e2b","observation_id":"74dd5b41-ec91-4b1a-94c8-35bb361fd81f","resolution":{"observed_at":"2026-08-06T16:57:36.866773Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.676991Z","title":"Advances in neural information processing systems 36 (2023), 21702–21720","venue":null,"work_id":"e7b5dfe8-4761-4868-a9f1-e809d6826b39","year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:30.652135Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:c3c465f1aa3b9db49a8f992bf472f494493552f7f8db5bb6a5faa9932dd7a79e","observation_id":"147c739a-f584-4fc4-a0ae-2abc12432e22","resolution":{"observed_at":"2026-08-06T16:57:36.853099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:36.293716Z","title":"Adell: An adaptive warp-balancing ell format for efficient sparse matrix-vector multiplication on gpus","venue":null,"work_id":"803eee37-9267-4e6d-a52b-3eb6fca71d64","year":2013},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:30.792890Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:6fa7200510c22c0b2a6b1cad7e51e177b4c5d1616598d4d51190425dc9e56f93","observation_id":"1fef18ad-bb73-4c57-bd46-bfc9e3d79c97","resolution":{"observed_at":"2026-08-06T16:57:36.493590Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:35.897636Z","title":"Merge-based parallel sparse matrix-vector multi- plication","venue":null,"work_id":"0b171b4f-6b7d-4edf-989e-e82803e1f77f","year":2016},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:30.912617Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:ecda3b68bec51f30ad2804c8ba188c66665d342d692ec585b614f6b97c015a8b","observation_id":"bfa0a9c9-41af-44e9-bd41-56fcef23a7cb","resolution":{"observed_at":"2026-08-06T16:57:36.113989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:35.676451Z","title":"In GPU Technology Conference (2010), vol","venue":null,"work_id":"9754d663-ace5-4bea-b0aa-d7e75a5e9f6e","year":2010},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:31.046779Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:94a5b6035b80b72518ac057fc88a4bc02c7c65fadad0aaeb12d4881bc1a5231e","observation_id":"a7886ae0-cc7d-4f5f-928c-98078b721c07","resolution":{"observed_at":"2026-08-06T16:57:35.740541Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:35.546824Z","title":"In2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS) (2021), IEEE, pp","venue":null,"work_id":"99d0e901-f86d-456b-8dee-061271477975","year":2021},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:31.233990Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:cae67defadfd51943ccf4aec74eee2512f93c8cf0486833e4cebcf96d9f23581","observation_id":"a13808ca-0101-4bb2-9ddf-06cddf59714b","resolution":{"observed_at":"2026-08-06T16:57:35.597180Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.12456","last_updated":"2024-12-12T12:38:12Z","snapshot_observed_at":"2026-08-07T20:41:48.188566Z","submitted_at":"2023-12-16T02:27:00Z","title":"PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.12456","snapshot_observed_at":"2026-08-06T16:57:31.381924Z","title":"Powerinfer: Fast large language model serving with a consumer-grade gpu","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:31.381924Z"},"links":{"cited_paper":"/paper/2312.12456","citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:63285b51ea290c845288952a3cf28f458b975d94e6e2892c14ddaa58614fde6e","observation_id":"5e860b4a-708f-43e3-aad1-8ed942bdf3a0","resolution":{"observed_at":"2026-08-06T16:57:31.381924Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.11695","last_updated":"2024-05-06T17:47:01Z","snapshot_observed_at":"2026-07-06T15:44:42.776459Z","submitted_at":"2023-06-20T17:18:20Z","title":"A Simple and Effective Pruning Approach for Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.11695","snapshot_observed_at":"2026-08-06T16:57:31.512871Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:31.512871Z"},"links":{"cited_paper":"/paper/2306.11695","citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:8ad3fb064e274144de4eb668ce7b6f9a28f81881e40e01a5e4fcf2abb3852790","observation_id":"c498357d-ccaf-46b9-a17f-a4e0c07a3377","resolution":{"observed_at":"2026-08-06T16:57:31.512871Z","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":"2026-08-06T16:57:35.448617Z","title":"In 2011 International conference on parallel processing (2011), IEEE, pp","venue":null,"work_id":"20419fa6-67df-4c0b-a200-402603c3cc79","year":2011},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:31.678902Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:835868b6edde9b6e490ac23d9e9589d24ca7cfc76440cd49beb9e3d35fc22afb","observation_id":"31b7b88b-7f35-485f-a93d-e0f572a4a012","resolution":{"observed_at":"2026-08-06T16:57:35.498328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-06T16:57:31.830414Z","title":"Llama 2: Open foundation and fine-tuned chat models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:31.830414Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:3cb4fcfff39b8adfb34be63abc827501c3a343abd0295a15a1b667dc62172a18","observation_id":"ebc2f897-3a61-4a56-b034-62f6b6b6b329","resolution":{"observed_at":"2026-08-06T16:57:31.830414Z","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":"2026-08-06T16:57:35.339288Z","title":null,"venue":null,"work_id":"d261a026-dd86-435e-afe2-0d066881e084","year":2011},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:31.939265Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:6c17390891e4a04be6382bc5596ed414c0745d4ce0ac81b5ab26a2fb152dbe5a","observation_id":"c648bf5c-9f23-4d22-ba94-2a440a2ef3c5","resolution":{"observed_at":"2026-08-06T16:57:35.387900Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:35.207382Z","title":"W., and Yelick, K","venue":null,"work_id":"72c55b9f-0d0d-42e2-89a8-aacdf94c9f61","year":2005},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:32.064464Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:c0f2c039f23ebeed9c28c658049c747da8e3339dd980e06c976649e8d1974ef5","observation_id":"af78bfaf-f28a-4812-a87d-d0c97c12f52a","resolution":{"observed_at":"2026-08-06T16:57:35.259125Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.14030","last_updated":"2023-11-23T14:36:30Z","snapshot_observed_at":"2026-07-06T16:51:36.124532Z","submitted_at":"2023-11-23T14:36:30Z","title":"PrivateLoRA For Efficient Privacy Preserving LLM","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.14030","snapshot_observed_at":"2026-08-06T16:57:32.216391Z","title":"Privatelora for efficient privacy preserving llm","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:32.216391Z"},"links":{"cited_paper":"/paper/2311.14030","citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:96e09116256e80a2d672e81f029e27c324db133a1b6cddf72c1b4ddc7fa8520e","observation_id":"fd9bd963-9ffc-4a45-9cbc-5c49340c05fb","resolution":{"observed_at":"2026-08-06T16:57:32.216391Z","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":"2026-08-06T16:57:35.049668Z","title":"M.Register tiling for unstructured sparsity in neural network inference","venue":null,"work_id":"ceae2285-d7cf-4be0-a81a-e3faf7046eb2","year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:32.364100Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:24856d283606a2b15223f24c322d281f5b49b511584443f67500b8e1783a19f7","observation_id":"18427a5f-1fb6-4a2a-b5cf-eacdb605087a","resolution":{"observed_at":"2026-08-06T16:57:35.146848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:34.818669Z","title":"Accelerating sparse matrix computations via data compression","venue":null,"work_id":"da3de162-cc63-4c56-a5f6-19f25660cd71","year":2006},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:32.498733Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:574d997b8e460d906a1cdd001f505cb48b0bc366fddc478f9f8a82df9b76ac09","observation_id":"bc708c7e-9cb0-43fa-8382-8f44deeb7737","resolution":{"observed_at":"2026-08-06T16:57:34.946084Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:34.617266Z","title":null,"venue":null,"work_id":"f62f811d-bb25-43b5-ba21-963be7afc5a8","year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:32.675617Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:96d2d7490988642a0e8c195f68b0d8ba14891a57a07739610adad2daaa99650b","observation_id":"d8036e1d-99f5-4bce-a1b8-5ebb9735bdf1","resolution":{"observed_at":"2026-08-06T16:57:34.723427Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06694","last_updated":"2024-04-11T01:18:06Z","snapshot_observed_at":"2026-08-07T03:20:22.127593Z","submitted_at":"2023-10-10T15:13:30Z","title":"Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06694","snapshot_observed_at":"2026-08-06T16:57:32.791550Z","title":"Sheared llama: Accelerating language model pre-training via structured pruning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:32.791550Z"},"links":{"cited_paper":"/paper/2310.06694","citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:f77c7059b76b609810ad8c9a5b81187ba905be41cbb80cb62e64878910f01678","observation_id":"ae5af087-a1b0-45e5-83f0-b0aa3f0d4416","resolution":{"observed_at":"2026-08-06T16:57:32.791550Z","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":"2026-08-06T16:57:34.371461Z","title":"Besa: Pruning large language models with blockwise parameter- efficient sparsity allocation","venue":null,"work_id":"5b44fe5d-3200-478a-88d5-64f29a80e635","year":null},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:32.917819Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:4c85534348bd75c5d521d3776f3804718c6c77518836ee1688d121e3a403001a","observation_id":"f03df9fe-b017-417c-b89e-ea99fa139406","resolution":{"observed_at":"2026-08-06T16:57:34.503129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T16:57:34.112800Z","title":"A survey on large language model (llm) security and privacy: The good, the bad, and the ugly","venue":null,"work_id":"547135d8-87e4-480c-aa44-ce9e99ee85d6","year":2024},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:33.073534Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:c68c3ea6abfc6858485b29c489ca326e1de0ee457b1c6fa2b80557f528113d57","observation_id":"3a3f4dea-9ab7-4c07-9a9d-97e23b7c3b0c","resolution":{"observed_at":"2026-08-06T16:57:34.233921Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.01068","last_updated":"2022-06-21T17:04:40Z","snapshot_observed_at":"2026-08-06T03:13:37.403059Z","submitted_at":"2022-05-02T17:49:50Z","title":"OPT: Open Pre-trained Transformer Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.01068","snapshot_observed_at":"2026-08-06T16:57:33.217115Z","title":"V., et al","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:33.217115Z"},"links":{"cited_paper":"/paper/2205.01068","citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:9d2894e5d4f89c4c2627a649d4f1035ec94c262654ca3bc4192321e8d2649bbe","observation_id":"0438e405-d73c-4f6d-a8f8-526e234a7762","resolution":{"observed_at":"2026-08-06T16:57:33.217115Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08915","last_updated":"2024-02-26T02:51:30Z","snapshot_observed_at":"2026-07-06T16:32:23.448967Z","submitted_at":"2023-10-13T07:38:52Z","title":"Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08915","snapshot_observed_at":"2026-08-06T16:57:33.377605Z","title":"Dynamic sparse no training: Training-free fine-tuning for sparse llms","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:33.377605Z"},"links":{"cited_paper":"/paper/2310.08915","citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:1a99edfffa4c437927ce1f612ec6c191bcbfe62d65cabecd6f94f7ced0368876","observation_id":"839236d8-5228-4f8f-9019-a9802689158d","resolution":{"observed_at":"2026-08-06T16:57:33.377605Z","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":"2026-08-06T16:57:33.914609Z","title":"Acc-spmm: Accelerating general-purpose sparse matrix-matrix multiplication with gpu tensor cores","venue":null,"work_id":"96e299c4-5088-4686-befc-c480a56237f4","year":2025},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:33.512161Z"},"links":{"citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:100c4fe17100d62283d044736ef563e3929a0ba709275cda506cc84d62ff571c","observation_id":"e4a225ad-ab69-455a-b4a7-18e8b33ccf67","resolution":{"observed_at":"2026-08-06T16:57:34.025375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.18223","last_updated":"2026-03-18T05:34:39Z","snapshot_observed_at":"2026-08-06T23:27:24.356320Z","submitted_at":"2023-03-31T17:28:46Z","title":"A Survey of Large Language Models","version":19},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.18223","snapshot_observed_at":"2026-08-06T16:57:33.640328Z","title":"X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., Dong, Z., et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T16:57:33.640328Z"},"links":{"cited_paper":"/paper/2303.18223","citing_paper":"/paper/2507.12205"},"observation_digest":"sha256:f8125086a6e42322a932f27dbbc25a405d00465f33f3f4be0ed8cf511f0ecec7","observation_id":"2e83db51-a3e4-45a8-b62b-8ff6ef5584e5","resolution":{"observed_at":"2026-08-06T16:57:33.640328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.12205","last_updated":"2025-07-16T13:04:06Z","latest_version":1,"primary_category":"cs.DC","snapshot_observed_at":"2026-08-07T12:21:15.238746Z","submitted_at":"2025-07-16T13:04:06Z","title":"Toward Efficient SpMV in Sparse LLMs via Block Extraction and Compressed Storage"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":10,"verified_exact":0,"verified_fuzzy":37},"total_outbound_references":47},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2507.12205."}