Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2406.17660.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T22:19:37.367714Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T20:28:59.903294Z
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 384b94d9-ee53-4845-80a1-dd8b201f123c · inbound
TensorGRaD: Tensor Gradient Robust Decomposition for Memory-Efficient Neural Operator Training cites this paper.
TensorGRaD: Tensor Gradient Robust Decomposition for Memory-Efficient Neural Operator Training Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:19:37.367714Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8211329e-85a8-4282-82da-d55948a924ab · inbound
PLUMAGE: Probabilistic Low rank Unbiased Min Variance Gradient Estimator for Efficient Large Model Training cites this paper.
PLUMAGE: Probabilistic Low rank Unbiased Min Variance Gradient Estimator for Efficient Large Model Training Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:43:42.491956Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3552efa4-8be1-4205-98fa-b1d15ec007f4 · inbound
Geometrically Principled Randomized Optimization for Efficient LLM Training cites this paper.
Geometrically Principled Randomized Optimization for Efficient LLM Training Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T12:51:25.889874Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1a8a2fb6-a51d-4e35-aafd-8f6c9dde1754 · inbound
Beyond Perplexity: A Geometric and Spectral Study of Low-Rank Pre-Training cites this paper.
Beyond Perplexity: A Geometric and Spectral Study of Low-Rank Pre-Training Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T19:19:23.570105Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ca427d36-c68a-492f-a612-a80c1f77a853 · inbound
Beyond Perplexity: A Geometric and Spectral Study of Low-Rank Pre-Training cites this paper.
Beyond Perplexity: A Geometric and Spectral Study of Low-Rank Pre-Training Grass: Compute Efficient Low-Memory LLM Training with Structured Sparse Gradients
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T20:28:59.905006Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.