{"as_of":"2026-08-12T03:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a5253d2375ae0239c9ec9947758ac832ed8aa3073878f9f2e0d9bb28cf39d8b5","coverage":[{"denominator":17,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":17,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T05:59:00.619914Z","state":"measured"},{"denominator":17,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":17,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+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/2412.16985/citation-record","integrity":"/paper/2412.16985/integrity","json":"/paper/2412.16985/citation-record.json","paper":"/paper/2412.16985"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:59:00.742169Z","title":"Accessed: December 24, 2024","venue":null,"work_id":"46de4b14-6924-4b04-9a15-69cbff02cd8a","year":2024},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.576801Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:ebcbf9da1742c46a1a14f16f2a20e27895729f96f3f5468d8ddd1e766c54d00f","observation_id":"5df748c7-aaa2-4b7b-8ddd-2c8668f0ee82","resolution":{"observed_at":"2026-08-11T05:59:00.745483Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T05:59:00.735029Z","title":"Magis: Memory optimization via coordinated graph transformation and scheduling for dnn","venue":null,"work_id":"50ddf62d-9712-4aac-a886-b40143f36cb7","year":2024},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.579824Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:36983d31422310c4c555a06926d9962ac4ea2ac27265694aac564ee51eb4bc91","observation_id":"1c009883-92f9-4bf9-afea-22ac8af0caaa","resolution":{"observed_at":"2026-08-11T05:59:00.737685Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:59:00.582998Z","title":"Training deep nets with sublinear memory cost, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.582998Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:c8c86c288dd626f358e2f6287915c6db5da7698f79c5947e5d0c9919cc30a1f5","observation_id":"952e66f6-4257-4a68-918c-fe9043de5b44","resolution":{"observed_at":"2026-08-11T05:59:00.582998Z","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":"2026-08-11T05:59:00.724080Z","title":"Alibaba cloud ecs.gn7-c12g1.3xlarge instance, 2024","venue":null,"work_id":"cc00a141-2a30-4e57-a6a7-db00a7adfbf7","year":2024},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.585593Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:d6b5664929100f4b37cc56ae665d502a0860c8324c83c53072d1f242fedc7b17","observation_id":"9717ab50-42f8-4c2c-8c0d-fe104b40f55a","resolution":{"observed_at":"2026-08-11T05:59:00.726894Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T05:59:00.716247Z","title":"Swapadvisor: Pushing deep learning beyond the gpu memory limit via smart swapping","venue":null,"work_id":"8d56656c-df9a-44ea-99b1-4338ef0710c9","year":2020},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.588085Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:d19301a3d88f7d808cc1f82691363908aaecd6c5f6f7c3cf3af9eea11dab99ac","observation_id":"3aaf8bc8-73de-42b6-adb3-0e1a07e47e60","resolution":{"observed_at":"2026-08-11T05:59:00.719039Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:59:00.590717Z","title":"Gonzalez","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.590717Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:2b352b842bd0f2511ca7b721fc3983943b55b89c908752bfe92a31bc03fc8c6b","observation_id":"4807c271-6f91-4627-ab5d-bb72344d035a","resolution":{"observed_at":"2026-08-11T05:59:00.590717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.09616","last_updated":"2021-03-18T06:20:23Z","snapshot_observed_at":"2026-08-11T15:51:05.764065Z","submitted_at":"2020-06-17T02:49:59Z","title":"Dynamic Tensor Rematerialization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.09616","snapshot_observed_at":"2026-08-11T05:59:00.594255Z","title":"Dynamic tensor rematerialization","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.594255Z"},"links":{"cited_paper":"/paper/2006.09616","citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:f5331b81158e66b8ef6763a27321dac9c661c9e87f4f6ebb448a5a96502956b3","observation_id":"893ed2b8-6724-4130-93e4-840ab070d982","resolution":{"observed_at":"2026-08-11T05:59:00.594255Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T05:59:00.597611Z","title":"Xla : Compiling machine learning for peak performance, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.597611Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:93754fe4ea8d7464d38b033ce5786107b97b7cde5dab63e361022a672b3ed94f","observation_id":"2874dd07-e893-4359-8ecf-a1537101a51c","resolution":{"observed_at":"2026-08-11T05:59:00.597611Z","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":"2026-08-11T05:59:00.702149Z","title":"Olla: Optimizing the lifetime and location of arrays to reduce the memory usage of neural networks, 2022","venue":null,"work_id":"3be7d2ca-2755-47ee-850d-f9545c73b283","year":2022},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.599979Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:9130723b882e8c370dc34aadde20572b8d86eada756552d18666f38c68605662","observation_id":"3df1d322-d041-47f2-9e81-492db945d04b","resolution":{"observed_at":"2026-08-11T05:59:00.705420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T05:59:00.694601Z","title":"Delta: Dynamically optimizing gpu memory beyond tensor recomputation, 2022","venue":null,"work_id":"deb8bf6f-9c4e-4c4a-80db-ea30834851e2","year":2022},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.603454Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:7066c7715efa7755bda8a22b0af21078ea7b21f360d72033d009072e1d35566b","observation_id":"f77dfa2b-77e9-48f5-9bea-954da0463173","resolution":{"observed_at":"2026-08-11T05:59:00.697568Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T05:59:00.687960Z","title":"Bladedisc github repository, 2021","venue":null,"work_id":"0c2eb4d3-f9f3-4922-8a35-0bf06eb35b72","year":2021},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.606288Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:d84d211255fdc48d19a366661a087e65f9398c0b4c958d58dad96dc0a4304a28","observation_id":"900121a3-fc57-45cf-af80-8d30b0285d9a","resolution":{"observed_at":"2026-08-11T05:59:00.690558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T05:59:00.681051Z","title":"meta-llama/llama-2-7b, 2024","venue":null,"work_id":"7814b023-03a5-4960-a44f-b68a893136d8","year":2024},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.608508Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:41485f538cccb479572d37809b585d6111bf1848e5488b97731f1acdea9ea31b","observation_id":"989362f5-744b-4299-b8b9-aed1ba9bac75","resolution":{"observed_at":"2026-08-11T05:59:00.683666Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T05:59:00.674056Z","title":"Dynamic shape in modular, 2024","venue":null,"work_id":"1cbf00ad-9b31-47a6-be98-6c2366bc0380","year":2024},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.610674Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:d09a1cfd73ea7381a4665f37a63b55dfc3983086b96435de65f506304b23e26d","observation_id":"7b80eb24-588d-4cca-83d0-443613e4e931","resolution":{"observed_at":"2026-08-11T05:59:00.676787Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T05:59:00.667352Z","title":"Dynamic shape in pytorch, 2023","venue":null,"work_id":"39d11333-ceff-4be9-862b-8eff07e5f1ad","year":2023},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.613116Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:1d61986e0cfa316a042efa88c6ae0ef4bb40130df433abf10365127ac8bcf6a0","observation_id":"18e0d94c-912c-4020-bcaa-8c5c859bb73a","resolution":{"observed_at":"2026-08-11T05:59:00.669916Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T05:59:00.659739Z","title":"Hierarchical memory- constrained operator scheduling of neural architecture search networks","venue":null,"work_id":"a9550c2c-3329-4790-9208-0b21f10f2c55","year":2022},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.615678Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:6f971f37357657d1901ce07530396d55ebdac0e925e4c7e789188f17172845e7","observation_id":"da6674fc-460f-4b72-b497-c8468c1cccaa","resolution":{"observed_at":"2026-08-11T05:59:00.662714Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T05:59:00.651690Z","title":"Bladedisc: Optimizing dynamic shape machine learning workloads via compiler approach","venue":null,"work_id":"c2bbafc6-ead1-4133-bfa2-64dcb9adc732","year":2023},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.617704Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:7a9e11cb90c0ccc60c677038d7b1f964e64e0ff5ea79374c550513fea805ce47","observation_id":"9735dadd-c389-4c0f-b1d8-3f33b70dac5e","resolution":{"observed_at":"2026-08-11T05:59:00.655332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-11T05:59:00.642311Z","title":"Disc: A dynamic shape compiler for machine learning workloads","venue":null,"work_id":"c29416b3-07e5-4263-a58f-4b2967e12cd8","year":2021},"citing_paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T05:59:00.619914Z"},"links":{"citing_paper":"/paper/2412.16985"},"observation_digest":"sha256:7b1d811877eeef56ceb8144bd890a712ffe13e0450e556fc461d693c43fd29dc","observation_id":"f3f0d8ed-fe31-4510-8497-32b10e69c468","resolution":{"observed_at":"2026-08-11T05:59:00.646757Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.16985","last_updated":"2024-12-22T12:00:45Z","latest_version":1,"primary_category":"cs.DC","snapshot_observed_at":"2026-08-11T05:52:17.250841Z","submitted_at":"2024-12-22T12:00:45Z","title":"BladeDISC++: Memory Optimizations Based On Symbolic Shape"},"reference_resolution":{"displayed":17,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":0,"verified_fuzzy":13},"total_outbound_references":17},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2412.16985."}