{"as_of":"2026-08-09T21:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:dfa59364efa97afd22d31f7f7bfbad37a201f62ce4bd8541095e6f1928808293","coverage":[{"denominator":13,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T16:55:29.871982Z","state":"measured"},{"denominator":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2507.12419/citation-record","integrity":"/paper/2507.12419/integrity","json":"/paper/2507.12419/citation-record.json","paper":"/paper/2507.12419"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:55:28.899922Z","title":"arXiv:2507.05724","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:28.899922Z"},"links":{"citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:2424147e01fa3ead289c1d4454033238a5942f53a6776d62fed26d69050d4984","observation_id":"1f807eb9-3626-4820-9b0a-d9e2ede04d7e","resolution":{"observed_at":"2026-08-06T16:55:28.899922Z","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":"2026-08-06T16:55:29.006065Z","title":"arXiv:2505.22323","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:29.006065Z"},"links":{"citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:3d8ec95ade0ce78425bfabc75794343023d04e54f5a40891f784d865f8d7d697","observation_id":"c8fd6d23-7202-4416-b379-379c8377e7ec","resolution":{"observed_at":"2026-08-06T16:55:29.006065Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.07366","last_updated":"2025-06-09T02:32:09Z","snapshot_observed_at":"2026-08-09T10:34:39.801838Z","submitted_at":"2025-06-09T02:32:09Z","title":"MoE-GPS: Guidlines for Prediction Strategy for Dynamic Expert Duplication in MoE Load Balancing","version":1},"cited_work":{"arxiv_id":"2506.07366","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.07366","snapshot_observed_at":"2026-08-06T16:55:30.185538Z","title":"MoE-GPS: Guidlines for Prediction Strategy for Dynamic Expert Duplication in MoE Load Balancing","venue":"cs.LG","work_id":"26269cc7-2580-4189-be03-a6efd99965e0","year":2025},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:29.195405Z"},"links":{"cited_paper":"/paper/2506.07366","citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:2448e63d847026292a991890b56b9a0c79af0168301503a87080e43864551294","observation_id":"5e58020c-c82f-4ac7-9063-7090ad4e86d8","resolution":{"observed_at":"2026-08-06T16:55:30.270362Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-06T16:55:29.313331Z","title":"arXiv:2503.07137","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:29.313331Z"},"links":{"citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:523e007fbfed6aeb6250584a4f60faf0fe949f6e0555a1b4470cb48252b7879d","observation_id":"0678f2cf-8a39-4874-9150-f077ca3a01d7","resolution":{"observed_at":"2026-08-06T16:55:29.313331Z","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":"2026-08-06T16:55:29.395673Z","title":"arXiv:2506.14038","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:29.395673Z"},"links":{"citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:375eb73acb4e6888d36cef6226f961cf87224d4c323e149a0a106019d487f050","observation_id":"e2d97c05-fe66-4ddc-8ee9-81f151656035","resolution":{"observed_at":"2026-08-06T16:55:29.395673Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02258","last_updated":"2024-04-02T19:28:11Z","snapshot_observed_at":"2026-07-06T17:54:47.689340Z","submitted_at":"2024-04-02T19:28:11Z","title":"Mixture-of-Depths: Dynamically allocating compute in transformer-based language models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02258","snapshot_observed_at":"2026-08-06T16:55:29.480244Z","title":"arXiv:2404.02258","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:29.480244Z"},"links":{"cited_paper":"/paper/2404.02258","citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:94e29ebd76328e8f27d4dcc04862f045a76fa59f57a0bda96c6970df3d607bc3","observation_id":"850e78e5-ea92-4b7c-9aba-e464294c805d","resolution":{"observed_at":"2026-08-06T16:55:29.480244Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1709.01686","last_updated":"2017-09-06T06:30:51Z","snapshot_observed_at":"2026-07-06T05:58:17.354374Z","submitted_at":"2017-09-06T06:30:51Z","title":"BranchyNet: Fast Inference via Early Exiting from Deep Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1709.01686","snapshot_observed_at":"2026-08-06T16:55:29.689147Z","title":"arXiv:1709.01686","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:29.689147Z"},"links":{"cited_paper":"/paper/1709.01686","citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:d8cfb3d658612d9104aa29674aefa6a2e27cbd32756e6a2e147d488d4ef46e52","observation_id":"59e4af99-7515-45c4-8453-2df2033673e8","resolution":{"observed_at":"2026-08-06T16:55:29.689147Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.15664","last_updated":"2024-08-28T09:31:09Z","snapshot_observed_at":"2026-08-03T02:22:36.564849Z","submitted_at":"2024-08-28T09:31:09Z","title":"Auxiliary-Loss-Free Load Balancing Strategy for Mixture-of-Experts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.15664","snapshot_observed_at":"2026-08-06T16:55:29.757099Z","title":"arXiv:2408.15664","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:29.757099Z"},"links":{"cited_paper":"/paper/2408.15664","citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:6aa339396a70f1218347a0d6074b6e242e8e900eb6705601337b032094cc04c5","observation_id":"5aa1de29-f61d-46a1-bdcf-64239a197ace","resolution":{"observed_at":"2026-08-06T16:55:29.757099Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.18945","last_updated":"2025-06-23T02:15:43Z","snapshot_observed_at":"2026-08-09T10:33:57.788178Z","submitted_at":"2025-06-23T02:15:43Z","title":"Chain-of-Experts: Unlocking the Communication Power of Mixture-of-Experts Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.18945","snapshot_observed_at":"2026-08-06T16:55:29.871982Z","title":"arXiv:2506.18945","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:29.871982Z"},"links":{"cited_paper":"/paper/2506.18945","citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:a4ebdc666c43de7a9f29b3a100bb8fa754922068d9ba78150faaa84f974a234b","observation_id":"decfffa8-7372-45d7-acdd-f3e2eaad3d63","resolution":{"observed_at":"2026-08-06T16:55:29.871982Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1308.3432","last_updated":"2013-08-15T15:19:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2013-08-15T15:19:34Z","title":"Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1308.3432","snapshot_observed_at":"2026-08-06T16:55:28.760717Z","title":"arXiv preprint arXiv:1308.3432","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:28.760717Z"},"links":{"cited_paper":"/paper/1308.3432","citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:5efcd1236105c7ce19926faf0c83859e8413e9c5e1345827abf56c64f94ecd24","observation_id":"91df9a36-9bed-4706-aecb-2106f0f64a48","resolution":{"observed_at":"2026-08-06T16:55:28.760717Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1701.06538","last_updated":"2017-01-23T18:10:00Z","snapshot_observed_at":"2026-07-06T05:27:13.416519Z","submitted_at":"2017-01-23T18:10:00Z","title":"Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1701.06538","snapshot_observed_at":"2026-08-06T16:55:29.587301Z","title":"arXiv:1701.06538","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:29.587301Z"},"links":{"cited_paper":"/paper/1701.06538","citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:71063e3a38dc3519bdaedd1c7a446dee3abeb48c03bd9d12f802300be4d4fac4","observation_id":"f71e4539-b7c9-40a7-bb13-9213aeeaf69a","resolution":{"observed_at":"2026-08-06T16:55:29.587301Z","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":"2026-08-06T16:55:29.130082Z","title":"arXiv:2403.07652","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:29.130082Z"},"links":{"citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:e402014294b7a5ddfe39e1b48df1f8cfa78754eab77b7259170347048d6cc484","observation_id":"facd52d0-0dfa-43a5-957a-5da49baca718","resolution":{"observed_at":"2026-08-06T16:55:29.130082Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17553","last_updated":"2025-08-28T07:47:00Z","snapshot_observed_at":"2026-08-07T14:42:35.640311Z","submitted_at":"2025-05-23T06:58:44Z","title":"CoMoE: Contrastive Representation for Mixture-of-Experts in Parameter-Efficient Fine-tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.17553","snapshot_observed_at":"2026-08-06T16:55:28.826327Z","title":"arXiv:2505.17553","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-06T16:55:28.826327Z"},"links":{"cited_paper":"/paper/2505.17553","citing_paper":"/paper/2507.12419"},"observation_digest":"sha256:a45b301b0f4f0a8a18a34b748ad55c3640943705627379be69e32d4d3ec94280","observation_id":"88b3a77b-7faa-477e-84ed-2a2e8063aea2","resolution":{"observed_at":"2026-08-06T16:55:28.826327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.12419","last_updated":"2025-07-16T17:08:46Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-08T21:00:19.071697Z","submitted_at":"2025-07-16T17:08:46Z","title":"Mixture of Raytraced Experts"},"reference_resolution":{"displayed":13,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":12,"verified_exact":1,"verified_fuzzy":0},"total_outbound_references":13},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2507.12419."}