Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
OATS: Outlier-Aware Pruning Through Sparse and Low Rank Decomposition
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2409.13652.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T13:45:11.664328Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T21:06:14.426896Z
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 5f47e94f-c121-4f8e-bca6-2792189ad26b · inbound
RainFusion: Adaptive Video Generation Acceleration via Multi-Dimensional Visual Redundancy cites this paper.
RainFusion: Adaptive Video Generation Acceleration via Multi-Dimensional Visual Redundancy OATS: Outlier-Aware Pruning Through Sparse and Low Rank Decomposition
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:45:11.664328Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c4466d57-885c-4e17-b2e8-adf3d8d70b50 · inbound
Amber Pruner: Leveraging N:M Activation Sparsity for Efficient Prefill in Large Language Models cites this paper.
Amber Pruner: Leveraging N:M Activation Sparsity for Efficient Prefill in Large Language Models OATS: Outlier-Aware Pruning Through Sparse and Low Rank Decomposition
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T05:11:11.685207Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cee8349e-911f-4fde-83ae-f7566b637f79 · inbound
ELAS: Efficient Pre-Training of Low-Rank Large Language Models via 2:4 Activation Sparsity cites this paper.
ELAS: Efficient Pre-Training of Low-Rank Large Language Models via 2:4 Activation Sparsity OATS: Outlier-Aware Pruning Through Sparse and Low Rank Decomposition
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T10:56:29.828718Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 1d199569-2ff4-4c7b-b4e0-6c7c5b65f462 · 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 OATS: Outlier-Aware Pruning Through Sparse and Low Rank Decomposition
Reference 78
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T19:43:54.666757Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d1d61899-270a-4eba-9765-3047579d35dd · inbound
GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation cites this paper.
GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation OATS: Outlier-Aware Pruning Through Sparse and Low Rank Decomposition
Reference 84
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T21:06:14.428276Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.