Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T21:40:36.246202Z
Paper Citation Record · LEDGER
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks
As of 17 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2505.09326.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
25 of 25 outbound references displayed
- verified exact1
- verified fuzzy10
- unresolved14
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation c856c234-02f7-4457-abe6-ba3d5d45cdd1 · outbound
This paper cites an unresolved cited work.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T21:40:36.551520Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 13cc69b9-f7bd-48ff-8a22-df804b450b14 · outbound
This paper cites Robust Diagrams for Deep Learning Architectures: Applications and Theory.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Robust Diagrams for Deep Learning Architectures: Applications and Theory
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:40:36.540966Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0c1d406d-d4ec-4a46-85d4-c81b36d6a99e · outbound
This paper cites Category Theory for Ar- tificial General Intelligence.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Category Theory for Ar- tificial General Intelligence
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:40:36.529433Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation eae7708b-523e-4123-93af-4612788ad4dc · outbound
This paper cites FlashAttention on a Napkin: A Diagrammatic Approach to Deep Learning IO-Awareness.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks FlashAttention on a Napkin: A Diagrammatic Approach to Deep Learning IO-Awareness
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:40:36.518135Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b2519b06-e51f-4466-9725-aea0bd4845af · outbound
This paper cites Introduction to Categories and Categorical Logic.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Introduction to Categories and Categorical Logic
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:40:36.167660Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 07a7166d-c135-4695-9fe3-f2b1b7882d8a · outbound
This paper cites Ocal, Evan Patterson, and Brandon T.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Ocal, Evan Patterson, and Brandon T
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:40:36.506845Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 01888983-9fbf-4491-ac76-8aa034255733 · outbound
This paper cites GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:40:36.176547Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d2b95dcc-13b7-43c5-bc2f-9b99629daf7f · outbound
This paper cites Physics, Topology, Logic and Computation: A Rosetta Stone.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Physics, Topology, Logic and Computation: A Rosetta Stone
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:40:36.180602Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 201b0fcf-61a4-43c5-aa68-2f270bb6e043 · outbound
This paper cites Categorical Foundations of Gradient-Based Learning.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Categorical Foundations of Gradient-Based Learning
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:40:36.184633Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 64f4af17-c968-4f3f-9682-d41f7f7e429c · outbound
This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:40:36.188621Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 059c1688-d61c-41c2-b59c-aa552b0b7d27 · outbound
This paper cites FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:40:36.192641Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 43430c93-8802-40da-9df9-3101998adea8 · outbound
This paper cites DeepSeek-V3 Technical Report.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks DeepSeek-V3 Technical Report
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:40:36.196795Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bc89ee3c-235a-487a-be7d-0f4656631e4e · outbound
This paper cites Spivak, and Rémy Tuyéras.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Spivak, and Rémy Tuyéras
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:40:36.495631Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 166ea96a-680f-4830-80b6-423ba131e348 · outbound
This paper cites Position: Categorical Deep Learning is an Algebraic Theory of All Architectures.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Position: Categorical Deep Learning is an Algebraic Theory of All Architectures
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:40:36.204545Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 21fa9587-9517-4f55-bf67-a3e540463338 · outbound
This paper cites an unresolved cited work.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Unresolved cited work
Reference 15
- Resolution
- unresolved
- raw_fallback, observed 2026-08-15T21:40:36.484267Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation ec663410-2a74-4935-9023-46548810548a · outbound
This paper cites Deep Residual Learning for Image Recognition.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Deep Residual Learning for Image Recognition
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:40:36.211955Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f7d2b7c6-e31f-45b2-8225-bf45c75a6ad1 · outbound
This paper cites Identity Mappings in Deep Residual Networks.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Identity Mappings in Deep Residual Networks
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:40:36.472152Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d5e7afdb-b955-4812-bcad-0c989ac21505 · outbound
This paper cites Mixtral of Experts.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Mixtral of Experts
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:40:36.219463Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8ee88b12-0299-4abf-a23b-73f44050dc7a · outbound
This paper cites PyTorch: An Imperative Style, High-Performance Deep Learning Library.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks PyTorch: An Imperative Style, High-Performance Deep Learning Library
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:40:36.223162Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b29b90cd-e736-4511-8685-27028c24d99e · outbound
This paper cites A survey of graphical languages for monoidal categories, August 2009.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks A survey of graphical languages for monoidal categories, August 2009
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:40:36.461036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8e548768-a923-4364-a2d1-f1281a668abe · outbound
This paper cites FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T21:40:36.230738Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a76f0358-b665-4f24-84f0-f0c0fc3cfb95 · outbound
This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Gomez, Lukasz Kaiser, and Illia Polosukhin
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:40:36.449962Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation aaaaa918-9f4b-4290-9b17-7991f53bc92d · outbound
This paper cites Categories of Differentiable Polynomial Circuits for Machine Learning.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Categories of Differentiable Polynomial Circuits for Machine Learning
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T21:40:36.285543Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b9732ab7-92e9-4235-80b5-6cc0c69ecdb2 · outbound
This paper cites Neural String Diagrams: A Universal Modelling Language for Categorical Deep Learning.
Accelerating Machine Learning Systems via Category Theory: Applications to Spherical Attention for Gene Regulatory Networks Neural String Diagrams: A Universal Modelling Language for Categorical Deep Learning
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:40:36.438208Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 74f333fd-5f3d-4ac1-b7c7-878663cc1233 · outbound
This paper cites correctness.
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T21:40:36.427170Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
No inbound Pith citation observations are available.