Paper Citation Record · LEDGER

Sparsing Law: Towards Large Language Models with Greater Activation Sparsity

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2411.02335.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.02335 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:33:39.281866Z

measured 0 of 1 external citation measurements

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 2026-08-09T06:31:02.800959+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 2026-08-09T06:31:02.800959+00:00.