{"as_of":"2026-08-18T21:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2447f785bed68b50b0ff3cd4c0a1291bef6f9741c9377778c67e9fefcee6d8e9","coverage":[{"denominator":24,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":24,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T11:02:01.461598Z","state":"measured"},{"denominator":26,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":26,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T19:14:53.759102Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":13,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.09979","snapshot_observed_at":"2026-08-15T19:14:53.759102Z","title":"Deephoyer: Learning sparser neural network with differentiable scale-invariant sparsity measures","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"2506.17155","last_updated":"2025-06-26T21:55:13Z","snapshot_observed_at":"2026-08-18T17:00:41.421344Z","submitted_at":"2025-06-20T16:57:59Z","title":"Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-15T19:14:53.759102Z"},"links":{"cited_paper":"/paper/1908.09979","citing_paper":"/paper/2506.17155"},"observation_digest":"sha256:988a98131a19c49bb3d3856bf083f696d07338881bae53c3761864c1ac52a402","observation_id":"b79f683b-ca43-4db2-98d2-31bc3cd6321c","resolution":{"observed_at":"2026-08-15T19:14:53.759102Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"cited_work":{"arxiv_id":"1908.09979","doi":"10.48550/arxiv.1908.09979","metadata_source":"arxiv_reference","pith_arxiv_id":"1908.09979","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"doi:10.48550/arXiv.1908.09979 , urldate =","venue":"arXiv (Cornell University)","work_id":"0bbd2aab-dcdc-41df-84bc-8a2786207186","year":2020},"citing_paper":{"arxiv_id":"2606.13260","last_updated":"2026-06-11T12:16:35Z","snapshot_observed_at":"2026-08-05T18:30:36.265406Z","submitted_at":"2026-06-11T12:16:35Z","title":"Extracting Governing Equations from Latent Dynamics via Multi-View Contrastive Learning","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-06-27T07:30:17.092770Z"},"links":{"cited_paper":"/paper/1908.09979","citing_paper":"/paper/2606.13260"},"observation_digest":"sha256:159770458f59fe71935025bd23d39c0317c262866c20c880668112f7ca4fe7c6","observation_id":"e1a6acb3-2ed2-4390-8ea3-d2883182c58b","resolution":{"observed_at":"2026-06-27T07:30:40.907482Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1908.09979/citation-record","integrity":"/paper/1908.09979/integrity","json":"/paper/1908.09979/citation-record.json","paper":"/paper/1908.09979"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:02:01.697729Z","title":"For all the tables, the results of previous works are listed on the top, and are ordered based on publication year","venue":null,"work_id":"f3a7fd31-d659-447c-8c5f-b01dfd5b5ad7","year":null},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.456527Z"},"links":{"citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:0bcb30794a34a22d9a2aa28bf219bcb89df4a1071dbf1400724a233dc8a9948d","observation_id":"5a153319-664e-472c-918e-e2b96969192c","resolution":{"observed_at":"2026-08-14T11:02:01.703262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1808.06866","last_updated":"2018-08-21T12:22:38Z","snapshot_observed_at":"2026-08-14T18:38:54.194750Z","submitted_at":"2018-08-21T12:22:38Z","title":"Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.06866","snapshot_observed_at":"2026-08-14T11:02:01.360339Z","title":"Soft ﬁlter pruning for accelerating deep convolutional neural networks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.360339Z"},"links":{"cited_paper":"/paper/1808.06866","citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:bf97da7ef33042a8fd9a4fcff8dac04d3f98b4d793aeba3babeb6b0ee24d0660","observation_id":"8d70a857-c3ae-4a87-82b3-077c1d454463","resolution":{"observed_at":"2026-08-14T11:02:01.360339Z","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":"2026-08-14T11:02:01.742892Z","title":"ILSVRC2012","venue":null,"work_id":"50040d50-12b9-432a-be71-8dfbf3d29988","year":2013},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.441957Z"},"links":{"citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:5f4afee1ac075269ddd12343331aac917d2ef397715b4cf0caeccbedb459bf44","observation_id":"85d14f58-4904-4338-8d49-d8894abef068","resolution":{"observed_at":"2026-08-14T11:02:01.747480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1608.08710","last_updated":"2017-03-10T17:57:56Z","snapshot_observed_at":"2026-08-14T21:42:03.106939Z","submitted_at":"2016-08-31T02:29:59Z","title":"Pruning Filters for Efficient ConvNets","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.08710","snapshot_observed_at":"2026-08-14T11:02:01.376149Z","title":"Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, and Hans Peter Graf","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.376149Z"},"links":{"cited_paper":"/paper/1608.08710","citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:98a39601577b3162b9de6bfe3d6c1b12d9a7fe01baef6e622cdb1deee6804133","observation_id":"d3005d4e-1a07-4149-a075-dbcc88090af0","resolution":{"observed_at":"2026-08-14T11:02:01.376149Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1712.01312","last_updated":"2018-06-22T14:54:59Z","snapshot_observed_at":"2026-08-14T20:07:02.711956Z","submitted_at":"2017-12-04T19:20:27Z","title":"Learning Sparse Neural Networks through $L_0$ Regularization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.01312","snapshot_observed_at":"2026-08-14T11:02:01.381058Z","title":"Bayesian compression for deep learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.381058Z"},"links":{"cited_paper":"/paper/1712.01312","citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:377827c71841b4a1e4c50f62da7116fea640e1ffec8b7bd256d07bf5f0bc3c9c","observation_id":"80ec97a7-0451-4557-9b28-99d4cdbc7943","resolution":{"observed_at":"2026-08-14T11:02:01.381058Z","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":"2026-08-14T11:02:01.816248Z","title":"Deep supervised learning for hyperspectral data classiﬁcation through convolutional neural net- works","venue":null,"work_id":"c38a54d2-858d-4a20-8d6f-56bf77b94449","year":2015},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.386961Z"},"links":{"citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:894d87eb1d54bea47882bd25c5cf58476230283ea3fb7aba719eca37f9c47e65","observation_id":"af47dfd7-fd36-4cb3-a65d-ce7cbed2b0ab","resolution":{"observed_at":"2026-08-14T11:02:01.821270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1608.01409","last_updated":"2017-07-28T22:26:27Z","snapshot_observed_at":"2026-08-18T17:28:55.516223Z","submitted_at":"2016-08-04T01:16:39Z","title":"Faster CNNs with Direct Sparse Convolutions and Guided Pruning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.01409","snapshot_observed_at":"2026-08-14T11:02:01.397216Z","title":"Faster cnns with direct sparse convolutions and guided pruning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.397216Z"},"links":{"cited_paper":"/paper/1608.01409","citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:4858486331589bda1467a22bb7ba6450a032ad3f2294ec7a551ce615f2025f7c","observation_id":"a730f5b3-27d6-4b14-8973-0886fbabf6ee","resolution":{"observed_at":"2026-08-14T11:02:01.397216Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-08-17T19:17:06.411141Z","submitted_at":"2014-09-04T19:48:04Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.1556","snapshot_observed_at":"2026-08-14T11:02:01.402452Z","title":"Karen Simonyan and Andrew Zisserman","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.402452Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:46c93ab2ccd079ffea0b2244a954f228fa4e3a6babb4c5fe59de3a7b9ae0fc82","observation_id":"6249a67c-c071-4153-9db5-d4cd8263886c","resolution":{"observed_at":"2026-08-14T11:02:01.402452Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.10559","last_updated":"2020-01-15T20:16:50Z","snapshot_observed_at":"2026-08-17T15:25:07.559914Z","submitted_at":"2018-11-26T18:05:18Z","title":"Leveraging Filter Correlations for Deep Model Compression","version":2},"cited_work":{"arxiv_id":"1811.10559","doi":null,"metadata_source":"pith","pith_arxiv_id":"1811.10559","snapshot_observed_at":"2026-08-14T11:02:01.539863Z","title":"Leveraging Filter Correlations for Deep Model Compression","venue":"cs.CV","work_id":"bb5288f0-e456-425a-a93b-2024bfed8567","year":2018},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.407348Z"},"links":{"cited_paper":"/paper/1811.10559","citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:bf26bf23435e7e18d193829c7d4290174b18bd1f7fc694790dcfaca91f6f0adf","observation_id":"1ee39cfa-974f-4c5f-adac-ad834eb5f480","resolution":{"observed_at":"2026-08-14T11:02:01.544496Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1811.08778","last_updated":"2019-05-25T16:58:15Z","snapshot_observed_at":"2026-08-16T08:12:44.293336Z","submitted_at":"2018-11-21T15:20:18Z","title":"Reconstruction of jointly sparse vectors via manifold optimization","version":3},"cited_work":{"arxiv_id":"1811.08778","doi":null,"metadata_source":"pith","pith_arxiv_id":"1811.08778","snapshot_observed_at":"2026-08-14T11:02:01.515785Z","title":"Reconstruction of jointly sparse vectors via manifold optimization","venue":"math.NA","work_id":"c365777e-8125-4f3a-85d9-939cb8fdc33d","year":2018},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.412461Z"},"links":{"cited_paper":"/paper/1811.08778","citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:49cb1b3bf76d6bdd655144ce15229058b24c6f6087c12bdf8e8ac6b1c9931ede","observation_id":"8a13540b-f604-42bd-9e4e-bc5c03fc96c8","resolution":{"observed_at":"2026-08-14T11:02:01.522916Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1709.05027","last_updated":"2018-02-11T16:36:32Z","snapshot_observed_at":"2026-08-14T20:32:59.198284Z","submitted_at":"2017-09-15T01:10:23Z","title":"Learning Intrinsic Sparse Structures within Long Short-Term Memory","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1709.05027","snapshot_observed_at":"2026-08-14T11:02:01.421954Z","title":"Learning intrinsic sparse structures within long short-term memory","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.421954Z"},"links":{"cited_paper":"/paper/1709.05027","citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:3e768f019669ec694bd1a49c9c763b314bf99bde41495a46d6946309aee72dbc","observation_id":"a586cd79-5395-4aa9-81ea-444b4050e186","resolution":{"observed_at":"2026-08-14T11:02:01.421954Z","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":"2026-08-14T11:02:01.787255Z","title":"Model selection and estimation in regression with grouped variables","venue":null,"work_id":"855f29c4-822e-49b3-a2a5-9af71c4ee20f","year":2020},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.426716Z"},"links":{"citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:51d02510397023dd64a8acfd13c81a44f3938e15928a6cf377d809a9998e9a9f","observation_id":"6b41a21d-a213-4b80-a2d0-731530f97d22","resolution":{"observed_at":"2026-08-14T11:02:01.791931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:02:01.773035Z","title":"an elementwj in the weight matrixW","venue":null,"work_id":"4debde50-3ec6-47b3-9559-1445ce49b98e","year":2020},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.432098Z"},"links":{"citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:7590db4f6c3a43cf1db320d8de36319556759796a1b47b9ffa3a860842208804","observation_id":"087f38be-f08b-4868-a7b2-b1f4941772fb","resolution":{"observed_at":"2026-08-14T11:02:01.777965Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:02:01.757599Z","title":"All the MNIST experiments are done with a single TITAN XP GPU","venue":null,"work_id":"5bda578f-0986-4958-9aa2-16b11632520c","year":2020},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.437089Z"},"links":{"citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:18c8c1bab518227e73e6711aad731af2b2c836ea5c781f1bc9aee186eec870ed","observation_id":"2ad0aec7-23fe-4a97-b1e1-ce0641a37679","resolution":{"observed_at":"2026-08-14T11:02:01.762891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:02:01.728769Z","title":"torchvision","venue":null,"work_id":"b1efc253-801f-455a-a920-29d4ccb21bd0","year":2020},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.447030Z"},"links":{"citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:976694b81209cf25bc7c4968da9fde599e88ec7b00cc7167fbebcc18710de21c","observation_id":"ca28459a-cf74-44ac-ae49-4053cc46f667","resolution":{"observed_at":"2026-08-14T11:02:01.733220Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:02:01.713215Z","title":"Since most of the weight elements will be zero in the end, we only plot the histogram of nonzero weight elements for better observation","venue":null,"work_id":"7e5ac25a-1d93-4ae4-86ec-fd8c232c8f2e","year":2020},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.451505Z"},"links":{"citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:515058413d9e909ecda093ca420777cafa75ae2dbde185af76f3d9e65ccdf049","observation_id":"151bd09f-2fb5-4e5d-aab4-0c100bb5210e","resolution":{"observed_at":"2026-08-14T11:02:01.718637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:02:01.682714Z","title":"Model Base acc Acc gain #FLOPs reduction Pruning-A (Li et al.,","venue":null,"work_id":"dd2bd4ff-bd76-4bb4-a96f-835ab68aad7d","year":2020},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.461598Z"},"links":{"citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:aa27f732d21572fde59d3c999736d679ddd3f329987471d18e2003a4ab06b561","observation_id":"c0e19583-af74-400d-977b-ec9f79cb5c74","resolution":{"observed_at":"2026-08-14T11:02:01.687707Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-14T11:02:01.366187Z","title":"Adam: A method for stochastic optimization","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":2009,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.366187Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:620b0cc3e253f3d34e5661308ee872fb1a2c2fb408ac782d4bc579eb2ebe16ed","observation_id":"a82a4c2b-ff12-445c-a7a8-2e74ff0410f1","resolution":{"observed_at":"2026-08-14T11:02:01.366187Z","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":"2026-08-14T11:02:01.832012Z","title":"Blind deconvolution using a normalized sparsity measure","venue":null,"work_id":"742079c6-2ec3-443c-af1b-0fb1cffc1f06","year":2011},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.371207Z"},"links":{"citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:0ba4aaf2b67a47ffd5db93104f8649ecc8a885bb035addc6e0688b43e5006b61","observation_id":"8bcbfda1-cb84-463c-88a6-15dbc4126d65","resolution":{"observed_at":"2026-08-14T11:02:01.837230Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1312.5602","last_updated":"2013-12-19T16:00:08Z","snapshot_observed_at":"2026-08-17T17:19:33.060917Z","submitted_at":"2013-12-19T16:00:08Z","title":"Playing Atari with Deep Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.5602","snapshot_observed_at":"2026-08-14T11:02:01.391999Z","title":"Playing atari with deep reinforcement learning","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.391999Z"},"links":{"cited_paper":"/paper/1312.5602","citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:e33bb3302a8c50726e80d9713a1ebbb06e43e8ce7a82e6a2535236793d4ac924","observation_id":"736d33fa-a6a5-4050-8b2c-9140cf34a430","resolution":{"observed_at":"2026-08-14T11:02:01.391999Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1510.00149","last_updated":"2016-02-15T06:25:40Z","snapshot_observed_at":"2026-08-04T16:59:47.843960Z","submitted_at":"2015-10-01T09:03:44Z","title":"Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1510.00149","snapshot_observed_at":"2026-08-14T11:02:01.355019Z","title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.355019Z"},"links":{"cited_paper":"/paper/1510.00149","citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:ab85b6d709dd79559b8a89856703ceaada637405dda2ad04dc37c868adf427a7","observation_id":"5ff78d37-1891-4d6b-abe4-9d514a923aec","resolution":{"observed_at":"2026-08-14T11:02:01.355019Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.02017","last_updated":"2018-06-01T04:04:09Z","snapshot_observed_at":"2026-08-18T17:28:15.670137Z","submitted_at":"2017-11-06T17:03:39Z","title":"NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.02017","snapshot_observed_at":"2026-08-14T11:02:01.344633Z","title":"Xiaohan Ding, Guiguang Ding, Yuchen Guo, and Jungong Han","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.344633Z"},"links":{"cited_paper":"/paper/1711.02017","citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:2fc1b22c1be0f8a175a4ed22a715284eea61b7fbfc9cc455d294ec73afb73d1a","observation_id":"d44a482f-51c2-4280-aeb7-6c7ee1e0018b","resolution":{"observed_at":"2026-08-14T11:02:01.344633Z","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":"2026-08-14T11:02:01.801389Z","title":"Learning structured sparsity in deep neural networks","venue":null,"work_id":"098c457a-b04a-4478-b75c-0d44270420a2","year":null},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.417534Z"},"links":{"citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:1ac8110fc28b929ea12842bfaa1f86f465fab1c02a2b90551dab28d0ff09dd4a","observation_id":"3f1953ef-ed8d-407a-931c-e4e36f514b82","resolution":{"observed_at":"2026-08-14T11:02:01.806452Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:02:01.846973Z","title":"A method for ﬁnding structured sparse solutions to nonnegative least squares problems with applications","venue":null,"work_id":"f142b3f0-83a4-4acc-a20d-21e78fbfa1f7","year":2010},"citing_paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures","version":2},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-14T11:02:01.349866Z"},"links":{"citing_paper":"/paper/1908.09979"},"observation_digest":"sha256:4601700d1c2cd5ec39b8a10f6e5c357391bf4932b800d618e4dee1029555d641","observation_id":"b8bdbc8d-6533-4c30-91b3-a7d9b62514d4","resolution":{"observed_at":"2026-08-14T11:02:01.852536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.09979","last_updated":"2020-01-19T18:04:11Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T10:25:27.158095Z","submitted_at":"2019-08-27T01:34:25Z","title":"DeepHoyer: Learning Sparser Neural Network with Differentiable Scale-Invariant Sparsity Measures"},"reference_resolution":{"displayed":24,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":10,"verified_exact":2,"verified_fuzzy":12},"total_outbound_references":24},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 2 inbound Pith citation observations for arXiv:1908.09979."}