Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2411.02335.
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 2026-08-15T19:58:17.689641Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T11:54:51.151809Z
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 c7fb2201-d286-4191-906b-065f1b0dd637 · inbound
Response Uncertainty and Probe Modeling: Two Sides of the Same Coin in LLM Interpretability? cites this paper.
Response Uncertainty and Probe Modeling: Two Sides of the Same Coin in LLM Interpretability? Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:33:39.281866Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 72eb8b80-925b-4b3b-8508-d59bd534c81f · inbound
BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity cites this paper.
BlockFFN: Towards End-Side Acceleration-Friendly Mixture-of-Experts with Chunk-Level Activation Sparsity Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:20:00.312851Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5bb3d8ba-197a-49ec-91e8-f3963f0bdd68 · 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 Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T22:21:19.013049Z
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 a6c70552-4200-465a-b5ea-0c0922422dc2 · 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 Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T11:54:51.153774Z
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 92b8990e-e227-4992-8cf1-27859f06b6a8 · inbound
Unifying Depth and Width Pruning for LLMs via Binary Knapsack Optimization cites this paper.
Unifying Depth and Width Pruning for LLMs via Binary Knapsack Optimization Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:58:17.689641Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.