Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2404.08763.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:17:30.144622Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-29T19:43:54.683057Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation adcc2da6-36b9-48bc-ad55-27bcf2ebb472 · inbound
A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering cites this paper.
A Sparsity Predicting Approach for Large Language Models via Activation Pattern Clustering CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:17:30.144622Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 42a54f96-0d72-48cb-8149-34954a2b14b5 · inbound
Motivating Next-Gen Accelerators with Flexible (N:M) Activation Sparsity via Benchmarking Lightweight Post-Training Sparsification Approaches cites this paper.
Motivating Next-Gen Accelerators with Flexible (N:M) Activation Sparsity via Benchmarking Lightweight Post-Training Sparsification Approaches CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T13:41:25.906626Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 34e9a64c-e3f1-4c18-ac01-46071528837d · inbound
Resting Neurons, Active Insights: Robustifying Activation Sparsity in LLMs via Spontaneity cites this paper.
Resting Neurons, Active Insights: Robustifying Activation Sparsity in LLMs via Spontaneity CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T22:21:18.996612Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a4d8df31-2d74-4859-86db-9bc08890178a · inbound
Resting Neurons, Active Insights: Robustifying Activation Sparsity in LLMs via Spontaneity cites this paper.
Resting Neurons, Active Insights: Robustifying Activation Sparsity in LLMs via Spontaneity CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T11:54:51.118265Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 386c7bd1-6a43-4b93-99be-ad4a479215f7 · inbound
VisMMOE: Exploiting Visual-Expert Affinity for Efficient Visual-Language MoE Offloading cites this paper.
VisMMOE: Exploiting Visual-Expert Affinity for Efficient Visual-Language MoE Offloading CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T16:36:06.595422Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation b2d07974-1908-40b5-aa13-1ae3d0ae4675 · inbound
Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes cites this paper.
Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
Reference 34
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-20T13:48:19.626769Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 6fa8f132-cc1f-4611-8534-8237ba4dec80 · inbound
Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes cites this paper.
Bug or Feature$^2$: Weight Drift, Activation Sparsity and Spikes CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
Reference 34
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-22T09:16:19.664264Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 8ba0ef28-4555-4dc0-a459-9c22ed4d27f0 · inbound
RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models cites this paper.
RT-Lynx: Putting the GEMM Sparsity In a Right Way for Diffusion Models CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T19:43:54.684701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 9769e374-d25d-4758-9d5a-c6dbe5df9a59 · inbound
Sensitivity-Aware Thresholding and Token Routing for Activation Sparsification in Large Language Models cites this paper.
Sensitivity-Aware Thresholding and Token Routing for Activation Sparsification in Large Language Models CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T01:11:35.358300Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.